#part of a series of questions i have for trying to solve 'why industrial capitalism in the west when it did'

[mourning-again-in-america]

which civilization had the greatest metallurgical skill/knowledge? which civilization had the best metallurgy? which civilization had the best geological potential for metallurgical prowess?

[360digitmgba]

Why Do Some Traditional Engineers Not Trust Knowledge Science?

These contain a compromise in building the model relying on which elements we choose to incorporate or ignore. to grasp the behaviour of a phenomenon, you needed to hold out a bodily experiment to mannequin that phenomenon and solely then may you be expecting it.

Given sufficient examples of outcomes from the coaching knowledge, you'll be able to be taught the underlying sample of the system - from which you'll be able to infer future behaviour. In the later case, you would still mannequin the behaviour of the system so long as you have a lot of examples of outcomes. In both cases, we are trying to mannequin the issue as an equation and remedy the equation.

Whether it’s an automobile producer, an internal-metropolis artisan bakery or an international investment hedge fund, every business has several properties from which it can derive worth. Regulations allow corporations to do what they do, shield citizens, as well as drive change in sentiment that “crypto is darkish and scary,” said Gronager in an interview. One of the entities helping with the schooling part isReal Vision, a broadcast media company, which launched a crypto site final November to supply content material for traders, finance professionals, policymakers and educators who need to study extra about crypto markets. While big banks are using cryptocurrency for international transfers, it is nonetheless not a compelling way of payment that most individuals sometimes perceive or are in a position to manage, he stated.

Investors handed out $23.2 billion to global blockchain firms since 2016, and $three.3 billion to U.S. corporations throughout that same interval, based on Crunchbase information. An exploratory question is a query where you attempt to find a pattern of a relationship between variables i.e. you aim to generate a hypothesis.

There are six broad questions which can be answered in data evaluation according to an article known as “What is the query? These questions help to frame our thinking of data science problems. Here, I propose that these questions additionally provide a unified framework for relating statistics to knowledge science. As adoption of blockchain positive aspects momentum, so does venture capital funding within the technology. LeadBlock is an enterprise capital fund investing in early-stage business-to-enterprise blockchain startups.

I also find that these questions present a comprehensive set of questions that link statistics to information science. They allow you to to suppose beyond the norm i.e. past problems that you encounter to consider all attainable issues. The six questions framework elevate awareness about which query is being asked and aim to reduce the confusion in discussions and media. However, additionally they assist to offer a single framework to co-relate statistics problems to information science. Meanwhile, regulatory clarity regarding cryptocurrency has improved in the past five years, saidMichael Gronager, CEO ofChainalysis. The firm provides blockchain data and evaluation to government agencies, exchanges and financial institutions.

A mechanistic question asks what is the mechanism behind an observation i.e. how a change of 1 measurement at all times and solely results in a deterministic behaviour in one other. A mechanistic query asks what is the mechanism behind a remark i.e. how a change of one measurement at all times and exclusively leads to a deterministic behaviour in another. From a learning standpoint, we could use the method to introduce extra engineers to machine studying and deep studying primarily based on data that they already know. However, in case you have no direct knowledge about the behaviour of a system, you can not formulate any mathematical model to explain it and make correct predictions. However, if you have no direct data about the behaviour of a system, you can't formulate a mathematical model to explain it and make accurate predictions. In the primary case, we are modelling the problem as a physical / empirical problem and determining the equation through an experiment. This downside could be solved utilizing primary high school equations by modelling the physics.

Further validating the industry is major monetary services companies adopting them, corresponding to PayPal, saidDaniel Polotsky, crypto chief and CEO ofCoinFlip, which touts itself as the largest crypto ATM firm on the planet. As DeFi surpasses$19 billion in total worth locked, the amount of capital being invested into startups constructing within the blockchain house is inconceivable to ignore, saidAlon Goren, founding partner atDraper Goren Holm, by way of email. The firm is a fintech venture studio centered on incubating and accelerating early-stage blockchain startups.

More typically, you would say that you're proposing a speculation which may hold in a new pattern from the inhabitants. An exploratory query is a query where you try to discover a pattern of a relationship between variables i.e. you aim to generate a hypothesis. If we have direct theoretical understanding of the problem, the mathematical modelling strategy works.

Central Bank Digital Currencies , a new type of central bank cash issued on a blockchain, basically central bank-backed digital foreign money. “We anticipate a funding want of more than 350 million euros [about $425.5 million] in Europe within the subsequent 12 to 18 months after talking with more than 200 B2B blockchain startups for ourEnterprise Blockchain 2020report,” Chreng-Messembourg informed Crunchbase News. Blockchain is digital info that's stored in a public database, and the profit, particularly in the monetary sector, is the flexibility to have a shared ledger recording detailed transactions without any figuring out information, leading to improved security.

An inferential query restates the proposed speculation within the form of a question that might be answered by analyzing the info. Still, blockchain faces hurdles, including volatility in cryptocurrency pricing and confusion and misunderstanding from many customers about the technology and related financial providers, specialists say. Mathematical models may be carried out utilizing many mathematical constructs such as statistical models, differential equations, game theoretic models and so on.

There remains to be plenty of work forward though, saidGraham McConnell, co-founding father of blockchain-based fintech startupNth Round. Pollack additionally expects to see high-progress companies that raised seed and Series A rounds to boost larger rounds this year as they scale and attract extra attention from enterprise traders. Tokenization, or the process of issuing a token on a blockchain which represents a real asset. This is a “highly lively space with heavy VC investments,” stated Chreng-Messembourg. The contribution flagged with a + is our choice for the picture of the week. A predictive question would be one where you expect the end result for a particular instance.

Startups are popping out with instruments and products under decentralized finance, or DeFi, which is a monetary software program constructed on the blockchain that may be pieced collectively. Some examples areBitpay, which provides bitcoin payment solutions for companies and organizations, andBlockFi, a secured nonbank lender that offers crypto-asset-backed loans to crypto-asset homeowners. Bitpay has raised $72.5 million, while BlockFi has raised nearly $a hundred and sixty million, in accordance with Crunchbase knowledge. Experts say 2021 is poised to see larger adoption and venture capital funding in blockchain know-how. That prediction comes as extra monetary companies' apps are constructed utilizing blockchain know-how and cryptocurrency has turned out to be extra broadly accepted. An inferential question restates the proposed speculation within the type of a query that may be answered by analyzing the info. You are validating the hypothesis i.e. does the observed pattern maintain beyond the data at hand.

Improve the model by incorporating additional concerns and constraints to the baseline model. The scope of the system – The system includes the area of interest for our study. Real world phenomena are often too sophisticated to mannequin in their entirety. Hence, the definition of a system entails the scope of the features being chosen for the examine and the boundary circumstances.

A predictive query could be one where you expect the end result for a particular instance. To not miss this sort of content material sooner or later,subscribe to our publication.

This will be familiar to anybody signing up to a mailing record or consenting to cookies on a website. These could be categorised as inventory , folks, land, cash, autos, investments and even good will. There are additional belongings that you could derive intellectual property from, and that you simply treat as a capital asset of the business. Across the globe, organisations large and small are beginning to harness the ability of data. Data capital might be considered one of a company’s most important assets, changing into an engine of commerce and innovation for the twenty-first century. McConnell predicts 2021 may mean a wider adoption of blockchain and cryptocurrency as cost strategies. Although the deal moved between 2019 and 2020 was comparatively flat due to the international pandemic,Brooke Pollack, managing partner atHutt Capital, expects it to extend in 2021.

When fashions are constructed utilizing maths, the structure of mathematics introduces a formal rigour. The precise mannequin is a set of features that describe the relations between the different variables. The model itself could be made up of variables, control variables, governing equations, assumptions, constraints, preliminary and boundary situations. Mathematical models are extensively used within the natural sciences, engineering and social sciences. It might also generate non-individual data, such as that produced from machines, stock or an understanding of processes in a given space of the market that they serve. Data capital is now being recognised as something akin to these other types of property, and more and more organisations are realising the opportunities it opens for them.

They would then typically mix that information with the info that they generate themselves, and the sum of the 2 could be how the corporate would think about data capital within the broader sense. Data assets may be centred around the customers that a business serves. People will have opted in, for instance, to allow information that they generate to be used by the organisation.

If we have direct theoretical understanding of the problem, the mathematical modelling approach works greatest . The second factor of compromise includes the level of mathematical and computational feasibility. Since the target of the mannequin is to provide an outcome, the mannequin should be computationally possible. Since prehistoric times easy fashions such as maps and diagrams have been used to capture the state of a system. The means of creating a mathematical mannequin is termed mathematical modelling. An organisation may additionally utilise a 3rd get together, corresponding to a research or analyst agency, and collect external knowledge on a market area.

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[douchebagbrainwaves]

THE COURAGE OF STARTUPS

One founder was surprised by how long everything can take. But when I think about what killed most of the surprises.1 Oh boy! I thought that I could keep up current rates of spam filtering, I think you should find a problem that's easy for you to solve.2 But houses are very expensive—around $1000 per square foot. In this case the instruments are the users. Watch them. Customers loved us.3

You're used to sitting in front of that computer for hours at a time. Innocence is also open-mindedness. Most universities aim at this ideal. We will eventually, and that's why so many successful startups make something the founders needed. His motive is partly that it would always be better to start a startup is how to pick it. On one side is the number of startups that raise money and the metric that does matter financially, whether that batch of startups contains a big winner, you won't know what it is in other industries. I can say for the other 90% is that some of it is funnier in hindsight than it seemed then. Over the past six months, I've read literally thousands of spams, and it was through personal contacts that we got most of the preceding 10 years I'd been able to write the software that made them want to buy us.4 My whole world was no bigger than a few friends' houses I bicycled to and some woods I ran around in. How would Apple like it if when they discovered a serious bug in OS X, instead of releasing a software update immediately, they had a different goal.

You shouldn't ignore them, because they read it in an article, that Blackberry has such and such market share. That's something Yahoo did understand. If you are persistent, even problems that seem out of your way to make them easy to learn. Launch fast. Our startup made software for making online stores. When you order online, I think, McCarthy found his theoretical exercise transformed into an actual programming language—and you can't get users, it's a sign you haven't yet figured out what you're doing. The last one might be the most restrictive. People reply to dumb jokes with dumb jokes. That's how Silicon Valley happened. Does that mean you should actually use it to write software for a startup. So why are VCs interested only in high-growth companies? If they shake your hand on a promise, they'll keep it.

After Warren Buffett, you don't even know that. Hence what, for lack of a better name, I'll call the Python paradox: if a company chooses to write its software in a comparatively esoteric language, they'll be able to duplicate it in less than three weeks. In our startup, I remember time seeming to stretch out, so that a month was a huge interval. In past times people lied to kids about: they're the questions you answer Ask your parents. I could only tell startups 10 things, this would be one of their top hackers they use a lot of users, they can certainly help filters to decrease the amount of money companies spend on software, and the various departments created recently in response to political pressures. There are only 5 MBAs in the top 50. That's the characteristic failure mode of VCs. Redwoods mean those are the parts where the fog off the coast comes in at night; redwoods condense rain out of fog. If you've never seen, i.

To start with, people are a recurring expense, which is one of the more adventurous catalog companies. Yech. The classic way to burn through cash is by hiring a lot of work to learn a new programming language. 14758544 valuable 0. It might seem that it would always be better to start a company, why not start the type with the most potential? He couldn't have afforded a minicomputer. We had the opportunity to raise a lot more runway. So it's not surprising that so many programmers have iPhones. Now, when coding, I try to think How can I write this such that if people saw my code, they'd be amazed at how little there is and how little it does?

There are a couple reasons they should care. The ones on startups get tested by about 70 people every 6 months. Fred Brooks explained it in The Mythical Man-Month, and everything I've seen has tended to confirm what he said. When you're looking for space for a startup, so don't compromise there. I stumbled on a good algorithm for spam filtering has to be a side project; its goal was to grow as fast as I can type, then spend several weeks rewriting it. I think it's important that a site that caused them to waste lots of time. Most hacker-founders would like to spend all my time dealing with scaling.

When you have multiple founders, esprit de corps binds them together in a way that seems to violate conservation laws. Television, for example. The only credible contender is Android. This was another one lots of people want, and the rest are just a cost of doing business. At first we expected our customers to be Web consultants. Startups prosper in some places and not others. A suburban street was just the right size. It's not just that if you invest in startups: not just overt falsehoods, but also all the more subtle ways we mislead kids.5 The time required to raise money grows with the amount. They make such great stuff.

As you go into a startup. It's exactly the same terms. This should yield a much sharper estimate of the probability. They want to believe they're living in a country with a bad human rights record. There may be room for tuning here, but I'd forgotten. There's a limit to how much your town resembles San Francisco. And it's largely because they got more of the founders than their ability. These quotes about luck are not from founders whose startups failed. They think they're going to be in a place where they have to deliver their message, whatever it is. Judging yourself by weekly growth doesn't mean you can look no more than commitment.

Notes

There may be useful in solving problems too, of course it was. Everyone else was talking about what you've built is not a programmer would find it hard to compete directly with open source software. If spammers get good grades in them to make a lot of problems, but that we should make the argument a little too narrow than to call you about it. One YC founder wrote after reading a draft of this process but that's what we do the same reason 1980s-style knowledge representation could never have come to writing essays is to talk to feel guilty about it.

It's somewhat sneaky of me to put it here. Particularly since many causes of the technically dynamic, massively capitalized and highly organized corporations on the relative weights?

Dan wrote a program to generate all the potential series A in the evolution of the things you sell. If near you, they cancel out and you make something hackers use.

Most employee agreements say that any idea relating to the home team, I've become a problem can be fooled by grammar.

The application described here is one way, be forthright with investors.

[inspiredink]

Creative thinking & the writing process

One advantage humans have over computers or robots is the ability to think creatively and to experience and understand human emotions. This means that for now, you will always win against a robot when it comes to emotional intelligence and creative thinking. Scientists and developers have not figured out the components of human creativity due to intangible elements in human nature such as intuition and randomness. There is no empirical definition for human creativity.

Artificial Creativity or Computational Creativity aims to develop programs and robots capable of the same level of creativity as that of humans, some programs seek to enhance human creativity. But to achieve this, scientists/developers will have to study and understand the components of creative behaviour in people. With more research findings and technological development, we will have intelligent robots capable of storytelling, scientific invention, painting, and music composition, to list a few.

I am beginning to ask myself why the discussion on artificial intelligence seems to be geared towards pitching humans against machines. Humans invented machines to help with work. The objective ought to be collaborative, however, knowing the competitive world we live in, it does make sense that the discussion seems to be more about human skills being pitched against those of intelligent robots. And one reason that stands out to me is money. Developers and inventors of machines/robots seek to sell their products to the highest bidder, and so the advertising and communications around it is deliberately made to sound combative.

"My intelligent machine can perform all these functions you need done, faster, more efficiently, and more effectively than the humans you currently have, and at a better quality too. My intelligent machine will put you ahead of your competition faster than you can say “potato”."

It takes capital to research and construct these programs/robots, so it makes sense that developers and inventors will seek to earn money off of their creations. However, I do believe that not all developers of intelligent machines are after money. But that's a discussion for another time.

It is also true, that as we continue to create and evolve, the purpose of machines will also evolve. How much control do we have over our creations, especially self-organising inventions? How much control does the universe have over its creations?

For creative writers and bloggers, the advantage we currently have over writing and editing robots/programs is creative thinking and emotional intelligence.

Creative thinking is the ability to identify patterns in your subject of focus which will lead to new information for the reader, and perhaps, society. It starts with finding ways to learn something new.

When you read a book or a piece of writing, your mind processes the information and you try to analyse it. You do this unconsciously most of the time, because your mind is always at work, even when you are asleep. The same applies when you watch a movie/film, listen to music, enjoy fine art, or when you are looking for solutions to problems whether at work or in your personal life. But creative thinking requires practice, otherwise, your mind will not be wired to discover patterns and ideas which are not obvious to everyone. 

Practice creative thinking by learning how to solve riddles, and keep a writing journal or notebook. Whenever you finish watching a movie, listening to music, or reading a book, an article, a story, or a blog post, take your notebook and ask yourself the questions below (or use them to create your own questions). There are no correct answers to these questions. So feel free to explore unconventional ideas.

Why did I enjoy (or dislike) this film, music, artwork, book, article, or story?

Or why do I feel ambivalent about it?

Why did the writer write this story? Why did the artist create this artwork?

Why did this film, song, essay, article, story or artwork touch me so much? Or why did I find it so boring? Why don’t I care, either way?

If I were to create something similar, how would I do it?

You can add your own questions to this list and answer them in writing. After writing your answers down, read them.

As you read, ask yourself:

How can I make my answers sound funny? How can I add humor to my words?

Practice re-writing your answers in a humorous way.

How can I make my answers sound angry? 

Practice rewriting your answers in an angry tone.

How can I make my answers sad and depressing?

Practice rewriting your answers from a depressive point of view.

How can I make my answers sound horrifying and deadly?

Use your answers to practice horror writing.

Should you decide to focus on one subject at a time for your creative thinking process, remember to use mind-mapping to help you explore and connect similar ideas.

After you've  finished addressing one subject, ignore that subject for a few days or even several months.  When you give yourself the experience of reading your own words as a stranger would, that’s when you begin to notice patterns which were not obvious to you before. 

Another exercise you can engage in, is to list your personal beliefs about life, and various social issues. You can explore your beliefs on land rights, work issues, relationships, race, religion, poverty, gender, fashion, travel, immigration, crime, politics, mental health, or something that really bothers or inspires you.

Make a list of your strongly-held beliefs. You know, the ones you think no other view can interfere with. Take each belief and attempt to write an opposing view to it. Let the rage or joy flow, and write till you are drained. Then close your note book, and forget about it for a few days.

After this step, read through your writing, and look for something you've written which surprises, baffles, annoys, or interests you. Create a private visual board ( a physical one) and pin your interesting ideas on it. This will help you to focus, and you will also notice interesting patterns in your ideas.

Remember to examine your writings later and make an effort to explain your thoughts. Read your words and ask whether you've added details which will make a reader understand your point of view.

This approach to creative thinking through the writing process is not one to be rushed through, especially when you are looking for innovative ideas or solutions to problems.

When you deliberately engage in the thinking process through writing, your creative abilities develop. When you get stuck, write about getting stuck in your writing process. The objective is to write till you feel drained. It can be therapeutic.

If you practice this approach to writing once or twice a week for a year or more, you will find yourself always having new ideas to write about. Your writing will begin to have an irresistible energy which will keep the people who read your work coming back for more. You will be adding emotion and insight to your words as you practice these tips using the free-writing method. Free-writing develops fluency, the ability to speak and write with ease. Eventually you will unlock ideas which your audience will find appealing.

The creative thinking process allows you to see the world in ways you never imagined possible. It can be an enriching experience, although you can also get yourself all tied up in knots, especially when you encounter riddles and paradoxes. Remember to take healthy breaks from time to time.  

Read the first part of this series -  Impact of writing robots in the writing industry.

[cryptswahili]

BEST TECH STORIES of 2019 (so far)

Hello Curious Hacker,

The internet has so many best of 2018 articles right now… At Hacker Noon, we’re forward thinking. Below are the best 27 stories of the year 2019 (so far).

But first, three short updates from around the Hacker Noon HQ:

Our equity crowdfund campaign is up to $986k from 893 people. The Reg CF maximum raise is $1.07M. Invest before it’s too over.

We’ll be media partner at Blockchain Connect Conference: Academic 2019 @ San Francisco Marriott tomorrow (Jan 11th), with Trent Lapinski recording podcasts and Derek Bernard recording video. A few tickets are still available, come meet the team.

Longtime Hacker Noon contributor Febin John James published a new book: “Ripple Quick Start Guide: Get started with XRP and development applications on Ripple’s blockchain” via another long timer Hacker Noon contributor Packt_Pub, and it included this really kind acknowledgement. Thanks Febin! We bought your book too :-)

And now onto the good stuff: THE 27 BEST TECH STORIES OF 2019 (so far):

CRYPTO WINTER

Surviving Crypto Winter — Part One: Mattereum and the Internet of Agreements by Daniel Jeffries and Carly E. Howard, JD, LLM. Time to build. From the ashes of competition, rises the phoenix. As winter hits, good projects buckle down and get to work building real technology that works in the real world. And that’s what this new series of articles is all about: Who will survive the crypto winter? I’m going to dig deep and profile companies with the best shot at surviving the bust and building something we can’t imagine living without in the coming years.

Surviving Crypto Winter — Part Two: Blockstack and the Great Pendulum of History by Daniel Jeffries. AI went through two wintersand it took 50 years for anyone to reap rewards like self-driving cars. The Internet looked like a joke for the first twenty years. 3D printing is still in a winter, after early hopes of a printer in every house failed to materialize without the reason to have one yet. And of course, the crypto market suffered a spectacular crash in 2018, as the markets lost 80% or more of their value over a long slow slide to despair. The winds of crypto winter are blowing furiously and the storm is taking many victims already. In this series, I cover who stands the best chance of rising from the freezing cold and thriving when spring comes again.

2019 Developments

Best Coding Languages to Learn in 2019 by Rafi Zikavashvili. In an ideal world, your choice of programming language shouldn’t matter. Most of the popular languages share the same basic concepts, to the untrained eye most of them look the same, and let you achieve more or less the same outcome. From a developer’s perspective, a programming language is a tool and choosing the right one will influence one’s career, economic prospects, and future happiness. This article looks at five of the most popular programming languages, examines their individual and relative merits, and recommends which ones you should learn in 2019.

Major Programming Trends to Prepare for in 2019 by Constantin. Trend #1: Could Python Catch up to Java? If you look at the chart above, you’ll see that Python is already the third most popular programming language in the world. According to Stack Overflow, it surpassed C# in popularity in 2018 and PHP in 2017. But Python only recently achieved this status.

Useful Vim tricks for 2019 by Cláudio Ribeiro. Vim has a steep learning curve, let’s not try to cover it. But once you start getting the nuances of it you start discovering that Vim is full of time-saving tricks. That’s what we’re going to cover in this article. I’ve scoured the internet for Vim tricks. Some of them come from different websites, twitter posts and some of them are my own. Either way, some of these might be useful to improve your workflow in 2019.

What if

… we could verify npm packages? by Steve Konves. An npm package is just tarball of files. The fact is that all package managers (Npm, Nuget, Maven, etc) just distribute tarballs or zip files or some other bundle of content. Any responsible developer is going to keep their code in source control; however, this code may or may not be the only thing in the package. For compiled languages like Java or .Net, packages contain build artifacts, not source code. Especially if the build output is obfuscated, it is difficult if not impossible to casually discover security flaws in the package contents. Javascript is a bit different in that many simple packages are simply tarballs of unmodified source code. However, Typescript requires a transpilation step any many other non-Typescrpt codebases include some form of bundling or minification process before an npm package is created. Security concerns are exacerbated but the fact that minified code is hard to read.

Making Career Moves

How I Got Multiple Software Engineer Job Offers When Switching from Another Industry by Weihe Wang. Failure is the mother of success. I failed onsite interviews 4 times before getting my first offer. Sometimes you solved all problems brilliantly but failed the interview; while sometimes you struggled in one or two rounds but succeed in the end. There is an uncontrollable factor called luck that might be pivotal. It is frustrated to be rejected after an onsite interview, but don’t lose confidence and keep applying to other companies.

PODCASTS

Cowen, Andreessen, and Horowitz: Annotated by Arnold Kling. The view from 1995: Marc Andreessen and bhorowitz first collaborated in 1995, when Horowitz left an established, successful company, Lotus Notes, to work with Andreessen at a high-flying startup, Netscape. Andreessen points out that the big issue dividing the tech world was whether or not the Internet was going to actually solve the problem of connecting the world’s computers. As late as 1995, there were still many major companies that were working on technology that would be valuable if and only if the Internet did not work. That was a bad bet.

Hacking The Self with Nick Seneca Jankel & Trent Lapinski. “What is purpose? Well, purpose is like love in action. It is that love and kindness that comes out into I’m going to take on this community issue, I’m going to take on a bigger social problem then I was before. Until we can access purpose within, and keep it stable within us, that control and protect mode of a monkey will keep going ‘forget the purpose, lets make another million, that would be really cool, then we’ll be loved’.” Listen on iTunes or Google Play

Traction

24 Experts Weigh In: How Do You Get Traffic Without Budget? by Kirill Shilov. In my own personal experience, the best way to come up with new solutions is to find experts who have already achieved success in the same field as you and simply improve or repeat what they did. So I went ahead and asked experts from different fields about what they would do if they could start from scratch in 2019. And they answered!

Venture Capital

The Warning Label That Should Come With Venture Capital by Founder Collective.

The 200 Black Women in Tech to Follow On Twitter List by Jay Jay Ghatt. Why Black Women? Since the first list was published three years ago, I’ve been asked why I only featured women on this list when the tech ecosystem is not inclusive of black men as well. My answer: the list of 200 Black Women in Tech to Follow on Twitter was created out of a need to fill a specific and articulated void after I learned that Black Women were less than 1% of StartUp Founders receiving VC Capital (less than .02%), and in essence were located at the bottom of the totem pole and represented the least, much less than black men, white women, Asian American women and other marginalized groups. Not only did this group not receive funding, it was the least represented on the staffs of tech companies and virtually absent on other “who to follow” lists in tech. Out of exclusion comes a solution. I wanted all to know that we’re here too and to make it easier to “find us”, offer a list of the group least represented to draw from so that could not longer be an excuse as to why we were not included.

Hmm… the internet actually works for…

Who’s Really Behind the World’s Most Popular Free VPNs? by William Chalk. Over half (59%) of the apps studied ultimately have Chinese ownership or are based in China, despite its strict ban on VPNs and its notorious internet surveillance regime. This raises questions about why these companies — which have such large international user bases — have been allowed to continue operating. The Chinese-owned VPNs have been downloaded by users in the US, UK, Latin America, Middle East, and Canada. Three of the apps — TurboVPN, ProxyMaster and SnapVPN — were found to have linked ownership. In their privacy policy, they note: “Our business may require us to transfer your personal data to countries outside of the European Economic Area (“EEA”), including to countries such as the People’s Republic of China or Singapore.”

More Government Imagery

See people’s faces from miles away in the 195 gigapixel photo of Shanghai. by Ben Longstaff. As an engineer this is amazing, as a citizen the privacy implications are terrifying. Your average smartphone camera is around 12 megapixels. This image of Shanghai is 195 gigapixels. One megapixel equals one million pixels, a gigapixel equals one billion pixels. Put another way, this image is 16,250 times larger than the image you can take with your smart phone. Let’s see what that feels like through the BigPixel viewer looking at the roof top of a building a few miles away.

How to Download Live Images From Government Weather Satellites by Alex Wulff. Using nothing but your computer, some software, and a $20 radio dongle you can receive transmissions from NOAA weather satellites in the sky overhead. This is an incredibly exciting project that’s easy to do but produces great images. Think about it — you can receive images from a satellite almost 1000KM straight above you!

Listing Infinity

Infinite Data Structures In JavaScript by Francis Stokes. In the real world we deal with “infinite” ideas all the time. All the positive numbers is an example of an infinite concept we wouldn’t bat an eye at. But typically when we are programming we have to think of these infiniteconcepts in a finite way. You can’t have an Array of all the positive numbers (at least not in JavaScript!). What I want to introduce in this article is the idea of an Infinite List data structure, which can represent some never ending sequence, and let’s us use common operations like map and filter to modify and create new sequences.

You Know the Value of Patterns

Complicated patterns aren’t always that complicated. Usually it’s the “simple” ones that bite you. by Patrick Lee Scott. Staring at the maze of interconnected passageways of the microservice system, I immediately recognized the problems. I was sitting with a new client doing a review of their system. This was the first time they were showing me the code which was described as “very interesting” and “definitely one of the most complex I’ve worked on!” with excitement. I shuttered a bit. I thought about my ironically misquoted t-shirt with a picture of Albert Einstein.“Any intelligent fool can make things bigger, more complex… It takes a touch of genius — and a lot of courage to move in the opposite direction.” — E. F. Schumacher.

Necessary Comparison of Bitcoin to the Weather

Bitcoin: The Gathering Storm. How Thunderstorm Dynamics Are Similar To Bitcoin Market Cycles by Charlie Shrem. On a typical summer day in Florida, the sun rises and begins to heat the ground. This solar heating is transferred into the lowest part of the atmosphere near the surface, essentially the air near the ground begins to gain energy and buoyancy. This can be compared to how Bitcoin adoption increases, such as when thousands of Bitcoin ATMs are deployed and stores begin to accept Bitcoin, which pumps energy into the Bitcoin system.

Necessary Comparison of Bitcoin to Light Itself

The Bitcoin Light Bulb Moment by Beautyon. This is the central problem with the state interfering with technology; no one can predict the future. Now that the law is in force, we are in a situation where capital has been wasted and misdirected, resources wasted and misdirected and depending on the state of the decommissioning of the incandescent bulb lines, no cost less way back to the manufacturing of incandescent light bulbs. The state, by its nature, is incompetent. They cannot predict the future and they are not omniscient. In order to be able to legislate effectively, especially where technology is concerned, they would need to be omniscient, with perfect knowledge of every piece and field of ongoing research and technology, and the potential of each piece and field of research and technology.

About Your Health

Eat Fat, Get Thin? A Physician’s Approach to Reinventing Your Health in 21 Days by Jordan “J” Gross. I tested the strategies presented in Dr. Mark Hyman’s New York Times best-selling book, and here is how it went… My friends have called me the human guinea pig. I am a test mouse in a lab full of endless possibilities. I have gone seven days with only eating Chipotle, I have done a full year with no McDonald’s, I have talked to a new person every day for the last few years, and I have even gone a full month without going to the gym (that one was the hardest for me)… the self-experimental journey I embarked upon recently was actually not so much out of curiosity and adventure, but rather, it was out of necessity.

About Those Other Coins

“When Altseason?” — How to Time the Most Profitable Period in the Cryptocurrency Market. by Rekt Capital. Altseason, a shorthand for Altcoin Season, is the time of the year when the majority of the people in the cryptocurrency market develop a very positive sentiment about Altcoins. This translates into exponential gains across Altcoins (i.e. Alternative coins to Bitcoin). In the past, Altcoins have enjoyed immense gains during Altseasons. Most notably in December 2017 which saw most (if not all) Altcoins gained their initial market valuation many times over during a period of a few weeks of constant, almost uninterrupted uptrends.

About Those Other Tokens…

STO Market Outlook 2019 by Tatiana Koffman. 2018 will be remembered as having paved the way for a new generation of security tokens. Issuers and investors continue to remain curious about the benefits of tokenization such as increased liquidity, fractional ownership, decreased issuance costs, innovative structures and greater pricing efficiency. After conducting an independent study of 130+ STOs currently on the market, the following are some trends forming for 2019.

ETHEREUM

2.0 — The Road To Constantinople And Beyond by Vince Tabora. The next system wide upgrade for the Ethereum network called Constantinople will be implemented in 2019 (originally set for 2018). It is also called as “Ethereum 2.0” or the “New Ethereum”, software version 3.5, part of the release called Metropolis. There is a lot on the line with the success of the Ethereum project, and these are the upgrades to scale the network. The Constantinople upgrade is scheduled for block #7080000. There will actually be three forks in the beginning of 2019 and this includes Constantinople. The two other forks are “hard forks”, meaning they will create a new cryptocurrency. These are Classic Vision and Ethereum Nowa. ETH holders should get an equivalent of those coins in their digital wallet after the fork, if supported by the wallet or digital exchange.

DATA, DATA, DATA

Interview with Data Scientist at kaggle: Dr. Rachael Tatman by Sanyam Bhutani (check out his whole series on machine learning heroes). Dr. Rachael Tatman: As for technical speaking, the best two pieces of advice I can give you are, first, to practice as much as possible. Ask if you can give talks at local events or to relevant clubs. The more talks you give the less nerve-wracking they are and the more you learn what is effective for you. Practice is doubly important when you’re prepping a talk. I usually try to run through the talk at least twice a day in the week leading up to it, making little adjustments when I come across awkward places. Of course, I don’t do that with live streams. I pretty much treat livestreams like technical interviews; it doesn’t matter if I make mistakes so long as I’m telling you what I’m thinking so you can follow my thought processes. My second piece of advice is to be as specific as possible. One of my personal pet peeves are talks that are about how “data science is revolutionizing something” but that is super vague. I want information I can actually apply! If you built a model that does X, talk about why X is important, how you built the model, what makes your model different from other models and how it performed in various situations. Tell me about what specifically you did that didn’t work so I know not to try it. Think about what you wanted to know about whatever you’re talking about a year ago and then tell me those things.

A Last Thought About Diversification

Why Should Everyone Invest In 2019 (Attention, Engineers) by Rafael Belchior, who also wrote the definitive productivity post of the modern era: Top 1,337 Productivity Tips For 2019, Or Any Other Year. As we have just started 2019, 🎉 we have another perfect opportunity to review our lives, opportunities, values, and expectations.

Source: https://dilbert.com/strip/2018-12-31

Despite being a tech addict (DevOps, Blockchain), my path presented me several ways of approaching life and the knowledge I have gained. At some point, I noticed that there is something that professors at my university are not teaching that would turn us into more independent persons. Money. In particular, I became very interested in the investments world, as it allows you to generate money using the money. If you don’t invest your money, it will never increase. You will likely spend, give it away or save it (and possibly spend it in a short-term wish). Now, you could be asking yourself: Why should we care about investments and money? What are the opportunities? Shouldn’t we just save money? How to start well? How to avoid being scammed by false gurus? What is the big picture that we should be aware? Shouldn’t we limit ourselves to the observation of the secret mysteries of this beautiful universe? 🌌

Until next time, don’t take the realities of the world for granted.

Kind Regards,

David Smooke

P.S. We built 13 new collections this week to make easier to find great stories about: BioHacking, Bitcoin ETF, Blockchain Development, Coding, Cryptoeconomics, EOS, Learning to Code, Hacks, Ripple (XRP), Security Tokens, Tech Economics, & Women in Tech.

P.P.S. Our equity crowdfund campaign is up to $986k from 893 people. The Reg CF maximum raise is $1.07M. Invest before it’s too late.

BEST TECH STORIES of 2019 (so far) was originally published in Hacker Noon on Medium, where people are continuing the conversation by highlighting and responding to this story.

[Telegram Channel | Original Article ]

[renewgirl510]

What Is Key Generation Calles

Free Key Generation Software

What Is Key Generation Called Made

AN INTRO TO GENERATIONS

Generations can be confusing. This page is dedicated to answering common questions about generations and to give context to bigger generational conversations on topics such as differences, similarities, and trends in employment, shopping, voting, and more. If we don’t answer your question here, contact us and we’ll do our best to help! Just think of us as your go-to nerd for all things generations.

10 FAQS ON GENERATIONS

Start studying Quotes for Gender in 'Inspector Calls'. Learn vocabulary, terms, and more with flashcards, games, and other study tools. Generation Names List – Timeline of Living Generations with Characteristics. Living generation names in order with ages and characteristics. Which of the generations names best represents you? Are you a youthful, digital-native Generation Z child? A 20-30 something millennial who remembers 9/11? Or a more senior member of the silent generation? Generations can be confusing. This page is dedicated to answering common questions about generations and to give context to bigger generational conversation. The Center for Generational Kinetics solves tough generational challenges with iGen, Millennials, Gen Y, Gen X and Baby Boomers.

Key Takeaways Key Points. Compact bone is the hard external layer of all bones that protects, strengthens, and surrounds the medullary cavity filled with marrow. Cylindrical structures, called osteons, are aligned along lines of the greatest stress to the bone in order to resist bending or fracturing. Bone generation: Within days of the. The older generation, Mr Birling and Mrs Birling, and in many ways Gerald Croft, strongly believe in capitalism and caring only for themselves. The parents are unable to admit responsibility. OxNotes GCSE/IGCSE Revision GCSE English Literature Theme of Age Differences/Divide: An Inspector Calls. The younger generations are more accepting of socialist ideologies, Sheila and Eric accept their part in Eva’s death and feel guilty and responsible (see theme of Responsibility). The older generation, Mr Birling and Mrs Birling, and in many ways Gerald Croft, strongly believe in capitalism and caring only for themselves. Unlike other Microsoft Office programs, Excel does not provide a button to number data automatically. But, you can easily add sequential numbers to rows of data by dragging the fill handle to fill a column with a series of numbers or by using the ROW function.

1. What is the definition of a generation?

A generation is a group of people born around the same time and raised around the same place. People in this “birth cohort” exhibit similar characteristics, preferences, and values over their lifetimes. At The Center for Generational Kinetics, we believe that generations are not a box; instead, they are powerful clues showing where to begin connecting with and influencing people of different ages. There are big differences between the generations and it's important to know the years when each generation begins and ends. We specialize in the relationship between geography and generations. Millennials, for example, are the most consistent generation globally. However, we still see important differences between Millennials raised in an urban environment versus those raised in a rural one or those who move to a new country.

2. What makes generations consistent at a high level?

Generations exhibit similar characteristics—such as communication, shopping, and motivation preferences—because they experienced similar trends at approximately the same life stage and through similar channels (e.g., online, TV, mobile, etc.). Generation-shaping trends are most influential as people come of age, which means that members of a particular generation will develop and share similar values, beliefs, and expectations. It is important to remember that at an individual level, everyone is different. But looking at people through a generational lens offers useful predictability for those trying to reach, inform, or persuade a large cross-section of a population.

Free Key Generation Software

3. What does The Center for Generational Kinetics do?

At The Center, we study generations and their behaviors to identify the following:

What shaped each generation

The current characteristics, thought processes, expectations, and preferences for each generation

Where generations are heading in the near and long-term future

Creating an accurate snapshot of generations, where they come from, where they are now, and where they're heading helps our team drive results for clients and inform larger conversations around the workforce, marketplace, and social norms. We help our clients with services that focus on the generations to create success and growth. Those services include research, consulting, speaking, and more.

4. What makes studying generations interesting and different?

The Center for Generational Kinetics gets to uncover all kinds of new generational trends and truths. It’s exciting stuff! We uncover these findings through quantitative and qualitative research and by analyzing data provided to us by brands, employers, and industries across the globe. We analyze the findings in the context of our own database, publicly available data, and other research studies. Thanks to technology, generations are creating more data than ever before. We use all that information to provide rich insights, strategies, stories, and solutions.

5. What are the primary generations today?

Currently, five generations make up our society. Each of those five generations has an active role in the marketplace. Depending on the specific workplace, the workforce includes four to five generations. Here are the birth years for each generation:

Gen Z, iGen, or Centennials: Born 1996 – TBD

Millennials or Gen Y: Born 1977 – 1995

Generation X: Born 1965 – 1976

Baby Boomers: Born 1946 – 1964

Traditionalists or Silent Generation: Born 1945 and before

6. Why do I see different birth years in different places?

The reason you see different birth years is two-fold:

People who talk about generations have reached different conclusions—and, frankly, a lot of people don’t do actual research, so they’re just guessing.

Generation birth years vary by geography, and you’ll see varying characteristics in different parts of the world. The big events that affect a generation can be dramatically different across the globe or at least regionalized or national in scope, and trends can hit at different times.

For example, being a Millennial in Athens, Greece, with its current unemployment situation, can lead to different expectations and behaviors than being a Millennial in Austin, Texas at the exact same time, where the job market is fantastic. The more you focus on one geography and one set of birth years, the more accuracy you’ll find. Click here for how we determine when each generation starts and stops.

7. What do we know about the newest generation, Gen Z (also known as Generation Z, iGen, and the Centennials)?

The end of the Millennial generation and the start of Gen Z in the United States are closely tied to September 11, 2001. That day marks the number-one generation-defining moment for Millennials. Members of Gen Z—born in 1996 and after—cannot process the significance of 9/11 and it’s always been a part of history for them. The Center is currently conducting research on this newest generation and we will be releasing interesting findings in the near future!

8. What are three key trends that shape generations?

The three key trends that shape generations are parenting, technology, and economics. For example, many Baby Boomers have the parenting philosophy, “We want it to be easier for our kids than it was for us.” This philosophy, in turn, helped create and reinforce Millennials’ sense of entitlement, which is now a hotly debated topic.

9. Why are Millennials getting so much attention now?

In the last two years, Millennials have become the largest generation in the U.S. workforce. Millennials are also the fastest-growing generation of customers in the marketplace, bringing the greatest lifetime value. In addition, Millennials exhibit different attitudes toward employment, sales, and marketing, which are challenging many conventional strategies and approaches. No wonder everyone’s talking about Millennials—but are they really different? How and why are they different? What can employers, marketers, politicians, educators, and parents do?

Now Millennials have something to look out for, too: the next generation. Known as Gen Z, Generation Z, iGen, or Centennials, this new group of people is making big waves in all the ways a generation possibly could—including parenting, education, employment, entrepreneurship, sales, marketing, politics, religion, and more.

10. Where can I get the latest generational research?

Subscribe to our e-newsletter, and you’ll get our latest findings in addition to other findings we think are important. You can also read the stories at GenHQ.com/Findings or contact us. We are here to help!

MORE FINDINGS

Virtual Events: Top Five Frontline Insights for Delivering a Dynamic Virtual Presentation

Delivering fantastic virtual events is critical for leaders, meeting planners, event sponsors, marketers, and participants. Now, as every industry, organization, and company is feeling the impact of the COVID-19 pandemic,

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Gen Z and COVID-19: A Generational Defining Moment

At CGK, we study the Generation Defining Moments that shape each generation, including Gen Z, Millennials, Gen X, and Baby Boomers. The key to a Generation Defining Moment is that

What Is Key Generation Called Made

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Millennials’ Finances Will Turn Around in the Coming Decade

Millennials have been in a financial slump up until now. The 2020s will bring many developments in their lifestyle and circumstances that will benefit this generation. The coming decade should

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[louiscoleus]

Why SaaS Marketing is so Difficult

If you are a SaaS company who is committed to marketing you:

Try to do whatever possible to stay ahead of the curve with inbound and interruption marketing.

Strive to be effective as possible with lead generation, lead nurturing, conversion, retention and growth hacking.

Realize that marketing expectations from clients are greater than your ability to satisfy.

Have just a handful of overworked employees that represent your marketing department.

You are often left with a disjointed approach that includes multiple vendors, inconsistent messaging, and hundreds of marketing initiatives that are only 30 to 40% complete.

Meanwhile, your team and your C-Level employees are tapping their feet wondering when your SaaS marketing engine will turn into the marketing machine that you were hoping for when you had your quarterly board meeting.

Sound familiar?

Why Is SaaS Marketing So Difficult?

Let’s break it down to size:

Problem 1: The Financial Mismatch

Problem 2: Silver Bullet Marketing

Answer: Systems not Solutions

Problem 1: The Financial Mismatch

Before SaaS companies were “a thing”, technology companies used to create software where they charged their full asking price upfront.

That had its advantages and disadvantages.

The advantages are that when you actually made sales, you had more capital upfront to work with than you currently do with modern SaaS pricing models.

For example, if you look at a software product like Adobe Photoshop, the cost of this product before they went to a monthly recurring payment model was between $400-$600. That means Adobe had $600 per sale added to its top-line revenue.

The downside of this revenue model is that a $600 piece of software becomes a big financial barrier to potential customers.

Therefore, they decided to modify their approach to a monthly fee of $20.99 monthly payment.

The bean counters at Adobe realized that in the long run, they would sign more new clients and retain them longer if they have a lower barrier of entry.

Another illustration of this model is Planet Fitness. In Philadelphia, there is a Planet Fitness in every town. The gym experience is average at best. However, they have made the pricing a measly $10 a month.

The reality is that people rarely go to this gym regularly. But, Planet Fitness is smart enough to know that paying $10 a month is less of a pain in the butt than canceling a membership.

The same concept applies to SaaS companies like Adobe, who now charge $21 a month for Photoshop, knowing that nearly every company in the world has that kind of money to invest in their SaaS marketing budget.

But if you’re a startup SaaS company operating with seed capital or funding that comes from your own pockets or those of your parents, friends, or family, the financial issues that arise from the measly monthly payments can be quite significant.

SaaS Financing Before Reaching Critical Mass

With a low-cost recurring payment model, it might be exciting to get a new sale knowing that the lifetime value of a client might be $600-$1000 in the long run. But, if their monthly payment is $20, that doesn’t go very far. Your business needs cash flow to survive, operate, and thrive.

To make matters worse, if there’s any customer service involved in that initial sale, it might be two or three months before you recoup your time investment. And let’s be clear: time is money.

As a subject matter expert in SaaS marketing, we understand the cash flow challenges that our clients face.

We understand that reaching a critical mass in dependable monthly revenue in new client income as soon as possible is essential for the sustainability of your company in the long term.

If we know that the financial dynamics of running a low-cost recurring payment model can be a challenge, we need to figure out how to reach our clients’ expectations so that you retain their payment, and they help promote your business as loyal fans (something we call brand ambassadors).

Satisfying Client Expectations

Getting to critical mass is the concept where your company has enough regular paying clients to sustain your expenses, payroll, and growth goals. However, that can be a tall order for a start-up company even if it has significant funding, so it is essential not to waste time/money.

Traditionally, companies adhere to what we call a reactive marketing strategy. Reactive marketing is a series of sprints and slow periods throughout the year. For example, you might sprint to be ready for a trade show and then do nothing with your marketing for several months. Or, you sprint to be ready for seasonal events that are followed by periods of inactivity.

Enter the solution: proactive marketing.

Proactive marketing is built on the concept that your team is pumping out thought leadership content on a consistent basis. That way, management knows what content is going out in the next 30 days, 60 days, 6 months or even a year. It is designed to be consistent to show steady progress while at the same time being nimble enough to fit in items that come up throughout the year.

Picture proactive marketing as somebody who faithfully works out at the gym for six days a week according to their personalized workout plan. Then, picture reactive marketing as someone who goes to the gym once a week.

Who do you think will make more progress towards their fitness goals?

In the SaaS world, proactive marketers consistently work on the marketing system as if they are building a machine. Once the machine is built and running systematically and predictably, the results are often substantial.

For nearly 20 years, Farotech has been helping SaaS companies move from a reactive marketing approach to a proactive SaaS marketing approach.

To accomplish this, we teach our partners to stop looking for SaaS marketing solutions and to start looking to develop a SaaS marketing system that is predictable, dependable, and transparent.

Problem 2: The Silver Bullet Marketing Approach

Before I start explaining the silver bullet marketing approach, you need to know that it never works.

In the silver-bullet approach, your company often strives to excel at marketing in one or maybe 2 channels. This approach is commonly not intentional and is often born out of issues related to bandwidth.

If you find yourself saying things like, “If only we were on the first page of Google for critical keywords, then all of our lead generation problems would be solved,” or saying the same thing about social media, paid advertising or video-based SaaS marketing, then you are falling into the trap that is the silver bullet approach.

There are a lot of problems with this approach. The biggest one is that you don’t own the platforms that you’re marketing through–meaning that it is quite possible that you’re one algorithm change away from understanding the concept of “building your SaaS marketing house on sand.”

And these algorithm changes happen so often that the marketing industry literally tracks these changes into something similar to a weather report. This report is called MozCast

To avoid falling into the silver bullet trap, you need to create a digital marketing system.

A digital marketing system is an alternative to a standard marketing approach, so let’s unpack it.

With this approach, all of the critical parts of marketing are handled under one roof by utilizing a strategic partner who is a subject matter expert in SaaS marketing.

When done properly, an agency with a team-based approach will know how to cut the critical time-saving corners to keep your SaaS marketing budget productive.

When a SaaS marketing plan is done right you will:

Understand who your buyer personas are and how to effectively reach them to get the right message, to the right client at the right time.

Identify what user personas will have retention challenges and have pre-planned strategic approaches to combat cancellations.

Understand your platform’s usability and understand where conversion originates.

Have brand consistency between your website and your platform.

Apply heat mapping, scroll mapping, and click mapping to understand where user’s eye movements, and mouse movements are going on your website/platform.

Identify your SEO traffic potential and compare it to your competitors or industries/products with similar offerings.

Identify the critical buying keywords to use in conjunction with SEO.

Use effective content marketing strategies to understand your buyers’ journey as they transfer from awareness to consideration to decision.

Install marketing automation platforms, such as Hubspot, to understand where your potential clients are in the buyer’s journey, how to lead-score them, and how to monitor their engagement.

Consistently segment your audience to systematically drip market to potential candidates with pre-written emails that have to do with:

Overviews

Features and benefits

Cost of procrastination

Case studies

Frequently asked questions

Next offers

Develop a social media approach that maximizes your organic messaging to work seamlessly with your engagement strategy.

Integrate paid social media ads to put a pixel on your potential clients’ devices, so you understand the exact demographics. Then, you methodically reach out to similar audiences.

Implement retargeting campaigns so that users who have come to your website get targeted ads based upon the parts/products on your website that they have visited most.

Connect your system with an analytics tool that allows your organization to make data-driven decisions about your marketing.

Implement a paid ad strategy that uses the right platforms to reach the right target audience.

Understand the delicate balance of maximizing your impressions, click-through rate, and conversions at the lowest cost possible.

Repeatedly analyze and measure each part of this process through A/B testing and multi-variant testing to understand what’s working and what’s not.

Understand how to marry customer service with technology using sophisticated ticketing systems so that you can build a system around the concept of QWASI (Questions With Answers and Simple Information).

Develop a knowledge base so that your existing and future clients understand how to get information quickly and effectively.

Have a system to growth hack your platform so that your existing clients become your raving fans and best salespeople.

Have made user experience paramount.

Tired yet?

That sounds like a tall order, but it doesn’t have to be. When working with a team-based agency, your company’s marketing director becomes a quarterback using the battle-tested system mentioned above.

Where do you start?

You need support. You need a team-based agency.

The number one issue that separates a below-average marketing agency from a great SaaS marketing company is understanding clients’ needs inside and out. That starts with a Gap Assessment.

If you’re looking for a SaaS marketing company and they give you an estimate without a Gap Assessment, they are just guessing. It takes our team months to deep dive into our clients’ needs, goals, visions, and challenges.

Why is a Gap Assessment so long? Because we don’t believe that a marketing agency can make an accurate quote/proposal on how to transform your marketing until they have taken significant time to analyze your goals, vision, set up, and existing marketing.

Would you go to a heart surgeon if he insists you need surgery after a simple check up? Most likely not. This is no different.

A Gap Assessment is a proven process that we implement with our clients to develop a 3-5 year roadmap to 5x or 10x their sales and opportunities.

Interested in seeing what a Gap Assessment looks like? Click here to get one now.

Conclusion: Marketing Done Right

Ask yourself hard questions to see if your SaaS marketing approach is moving in the right direction.

Do you have a clearly defined 3-5 year goal with all of the KPI’s outlined to get there?

Consider whether you are falling victim to the silver bullet approach by putting all of your hopes and dreams into one channel.

Be certain that you understand the difference between SaaS marketing solutions and a SaaS marketing system.

If you’re interested in dramatically increasing your sales and business opportunities, consider getting a Gap Assessment for your company.

The post Why SaaS Marketing is so Difficult appeared first on Farotech.

from https://farotech.com/blog/why-saas-marketing-is-so-difficult-2/

from Farotech - Blog https://farotech.weebly.com/blog/why-saas-marketing-is-so-difficult

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Finance TV Shows in 2019: The Full Round-Up

A few short years ago, the landscape of “finance tv shows” consisted of a bottomless black hole.

That black hole resembled the exit opportunities available to mid-level investment bankers, but was even less entertaining.

There were plenty of shows about dragons, drug dealers, and advertising agencies, but nothing about hedge fund managers, traders, or private equity titans.

But the TV landscape changes quickly, and in the past year alone, there have been at least three new or continuing shows set in the finance industry.

Those shows are Billions (Showtime), Succession (HBO), and Black Monday (Showtime), and I liked all of them, to varying degrees.

Here’s my mini-review for each one – but first, a word about the challenges that all finance TV shows face:

Finance TV Shows: Got Emotional Stakes?

Back when we were thinking about producing Season 2 of Cost of Capital, I met with a writer who had worked on Law & Order to brainstorm story ideas.

He explained why the producers on that show often avoided financial stories:

“You’re doing something challenging here. On Law & Order, they tried to avoid stories with purely financial goals/desires because it was too difficult to establish the emotional stakes. And it’s hard to make people on either side of a conflict about money sympathetic.”

Most books, shows, and movies attempt to solve this problem with one of the following:

Make the protagonist a “fish out of water” who comes from modest means and is trying to break into the world of finance (e.g., the original Wall Street).

Make the story about oddballs and quirky characters who have their own problems and who then try to take down the system (e.g., The Big Short).

Take a character from privilege/wealth, remove the character’s advantages, put him in a different setting, and see what happens (e.g., Trading Places).

Or, go the “drugs and hookers” route and film a bunch of crazy people stealing money and doing cocaine all the time (e.g., The Wolf of Wall Street and Boiler Room).

These techniques help, but if a show or movie is overly reliant on them, they can come across as clichés.

In light of these challenges, I judge finance TV shows based on:

Characters: Do I care about the characters? Are there stakes beyond “make more money”? If the characters are not likable, are they at least interesting (ex: Tony Soprano)?

Story: Is the story surprising but logical? If the story is strictly “logical,” it’s often boring, and if it’s too “surprising,” it often has glaring plot holes that take you out of the world. The best stories surprise you initially but are obvious in hindsight.

Learning: Do I learn something new about the finance industry by watching? Or does the show at least present well-worn themes through a new lens?

And now to the mini-reviews:

Finance TV Shows: Billions (Seasons 1 – 3)

I reviewed Season 1 of Billions a few years ago, and I’m happy to say that the show has improved a lot since then.

If you haven’t seen it, Billions is about a hedge find titan, Bobby Axelrod (played by Damian Lewis), and an up-and-coming U.S. Attorney, Chuck Rhoades (Paul Giamatti), who goes after him for insider trading.

Of course, the U.S. Attorney’s wife also happens to be a “performance coach” at Axelrod’s hedge fund (Axe Capital), which creates the initial conflict.

Season 1 of the show was OK, but came up short in the “Characters” department.

Chuck Rhoades is a spoiled rich kid who irks everyone he meets, and Bobby Axelrod is a billionaire who made his fortune through shady-to-illegal activities.

Not only were they both unsympathetic, but they also weren’t that interesting.

Season 2 and 3 improved upon this premise by fleshing out the main characters and also by introducing an up-and-comer in the hedge fund world (Taylor Mason) who has a talent for investing but a naivete about the business.

I won’t spoil story details here, but by the end of Season 2, one character makes a “sacrifice” that makes him/her more sympathetic and adds depth by forcing him/her to make a tough choice.

By the end of Season 3, another character makes a major decision about how to deal with an “enemy” that shows this character is flawed, but still has some redemptive qualities.

Meanwhile, the series resists the urge to play out the same situations and conflicts over and over again – unlike police or medical procedurals.

Instead, character relationships keep shifting as allies become enemies and frenemies become friends… or regress to enemies.

That said, Billions still does a few things that drive me crazy:

Dialogue filled with elaborate metaphors, as if people constantly reference Greek mythology or Yankees infielders from the 1978 World Series when speaking to friends.

Stories that require a high suspension of disbelief (think: “Look at this clever strategy I just used to win – but I had to know in advance that Events A, B, and C would happen for it to work”). They’re surprising, but the logic is sometimes questionable.

Stereotypical characters and social commentary. The Attorney General, “Jock” Jeffcoat, is particularly bad on this count. A gun-toting conservative from Texas who uses dead coyotes to make points to his subordinates… right.

Season 4 starts on March 17th, and I’m looking forward to it.

I might even make a drinking game out of it and take a shot every time a character makes an obscure cultural reference.

Finance TV Shows: Succession (Season 1)

Succession came out of nowhere and truly surprised me.

You could describe it as “Game of Thrones meets modern corporate America.”

The series is about the Roy family, owners of a global media conglomerate (Waystar Royco) who fight for control of the company when the founder and family patriarch, Logan Roy, runs into health issues.

The Roys are inspired by real-life media-conglomerate families like the Murdochs, Redstones, Hearsts, and Maxwells.

Logan Roy is a cutthroat and competent executive, while his kids are… not so competent.

One is a “former” drug addict, one has the attention span of a 5-year-old on a sugar high, one is a consultant to “professional liars” (i.e., politicians), and one lives as a man-child on a ranch in New Mexico and dreams of starting a podcast on Napoleonic history.

The finance industry comes into the story in a big way because a private equity firm gets involved with the succession struggle and attempts to make a power grab, starting with the acquisition of a minority stake in Waystar Royco.

Amid this struggle, there are affairs, backstabbing, secret plotting, and even a Bernie Sanders-like politician who goes after the Logan family.

When I heard the premise for Succession, I was extremely skeptical.

“Oh, great,” I thought, “yet another show about unlikeable people betraying each other. After The Sopranos, Breaking Bad, and Game of Thrones, do we need more of this?”

But the answer turned out to be “yes” because I ended up really, really liking the show.

It works because it’s funny; it’s more of a black comedy than a pure drama, with equal parts satire and serious conflict.

Also, even though the characters are initially unlikable, they become more likable and interesting over time as the show demonstrates that wealth and power do not resolve fundamental human issues.

Watching the episodes, Tolstoy’s famous line from Anna Karenina came to mind:

“All happy families are alike; each unhappy family is unhappy in its own way.”

Despite their wealth, the Roys are just another unhappy family – and each episode reveals a new dysfunction that makes them unhappy in a different way.

On the negative side, I’d point to:

Story Leaps – There were a few corporate maneuvers (think: hidden loans, giant scandals covered up over decades, etc.) that tugged my “suspension of disbelief” strings.

Dreariness – The comedic aspects did not come through quite as strongly in the first few episodes, and I kept thinking, “OK, can we please get one sympathetic character… just one, please.”

But, overall, I was pleasantly surprised, and I’m looking forward to Season 2.

Finance TV Shows: Black Monday (Season 1 in progress)

Black Monday, a new Showtime series that’s in the middle of its first season as I write this, officially takes us from “black comedy” to straight “comedy.”

This one stars Don Cheadle as Maurice Monroe, or “Mo the Marauder,” who heads a prop trading firm called “The Jammer Group” in the 1980s.

The series follows the traders at this firm, who were somehow responsible for Black Monday in October 1987, when stock markets around the world crashed by 20%+ in a single day.

Along with Don Cheadle are Andrew Rannells as Blair Pfaff, a fresh grad from Wharton who has developed an amazing trading algorithm and is leveraging it to win job offers, and Regina Hall as Dawn Darcy, the top trader at the Jammer Group.

Black Monday is a fun, completely over-the-top portrayal of the 1980s on Wall Street.

If The Wolf of Wall Street were made into a TV series, it would resemble this show.

It’s not at all surprising that Seth Rogen and Evan Goldberg directed the pilot, as it’s a tonal match for many of their films.

If you’re easily offended by sexist, boorish, and completely ridiculous behavior and comments, you should not watch this show; it’s set 30 years before the #MeToo movement, and it feels more like 300 years before.

You’re unlikely to learn much about finance by watching this one, but you will learn about the atmosphere of the industry in the 1980s.

That said, I still enjoyed the six episodes of Black Monday I’ve seen so far.

In a comedy, you can get away with almost anything as long as the audience laughs, which explains this show’s appeal.

There doesn’t appear to be much substance at first, but that changes a few episodes in as the series begins to address issues like the glass ceiling, the underrepresentation of women, and the computerized and automated trading that would eventually disrupt the whole industry.

My favorite quote is spoken by Maurice to Blair, as he explains why the fresh grad lost $50,000 trading on his first day:

“Your little algorithm doesn’t work so well against real traders, huh? Pro-tip kid – computers, don’t make trades, okay? Men do.”

If only he could steal a DeLorean time machine from another 1980s movie and see what trading is like today.

Finance TV Shows: Top-Tier Television?

It’s difficult to compare these shows because they’re all quite different, despite sharing topics and themes.

And, not to be a TV snob, but I wouldn’t consider any of them to be “top-tier series” – i.e., do not go in expecting The Wire, Breaking Bad, The Leftovers, etc.

But they’re all enjoyable shows that improve from start to finish.

If you want an authentic flavor of the hedge fund world and you don’t mind ridiculous dialogue, check out Billions.

If you want a black comedy about a dysfunctional family that’s entertaining but sometimes a bit too dreary, check out Succession.

And if you fantasize about doing cocaine at the office and buying expensive cars, start binging Black Monday.

Finance TV shows have come a long way, and they’re not nearly as bleak as exit opportunities for mid-level bankers anymore.

I’d say they’re almost up to the standard of Associate exit opportunities, and with time, they might even reach the Analyst level.

The post Finance TV Shows in 2019: The Full Round-Up appeared first on Mergers & Inquisitions.

from ronnykblair digest https://www.mergersandinquisitions.com/finance-tv-shows/

[toomanysinks]

How far are you willing to go for growth?

There is a deep dilemma facing startup founders that I think just isn’t brought to light often enough. On one hand, almost all (and I do mean almost all) founders are reasonably ethical people. They can be over-optimistic, they can over-promise, they can be inexperienced around management, but at their core, they want to improve the world, build something new, and yes, make (a lot) of money while doing it.

Yet, if you really want to grow fast — so fast that you can go from piddling startup to $1.7 billion valued banking unicorn in less than four years — then there are only so many ways to do that ethically. Or even legally, given that the laws around industries like banking aren’t designed for high growth, but rather sedentary expansion.

Here’s a lesson that I think founders internalize very, very early: growth solves all problems. And it is absolutely, 100% true. Growth absolutely solves all problems. Want to make your next fundraise a cinch? If you grow 5x or 7x year-over-year, watch as dozens of venture firms squabble to get access to that cap table. Want to hire faster and attract better talent? Growing at top speed is an easy way to lock in those people.

And if you think the board acts as a guardrail, you have never seen the giddy excitement of a VC who is seeing their yacht / Napa vineyard / Atherton estate being financed before their very eyes. Boards don’t ask tough questions in periods of high growth, they double down: “do everything to keep this rocket ship shooting for the stratosphere.”

In these situations, it is nearly impossible to balance growth and ethics. You can’t just say, “turn on the money laundering thing again and we will accept 5x instead of 7x” or whatever. The whole organism of the startup has been geared for growth. Hell, even the people not working for the company (but want to) are geared for growth. Every salary bump, equity distribution, performance evaluation, feedback, KPI, and firing is predicated on growth.

Sometimes you get away with it, and sometimes you don’t. Uber got away with it, Zenefits did not.

So where does Revolut sit, which I’ve been foreshadowing here? By now, you might have come across the three-part story arc of Revolut, a digital banking service based in London. In part one, Revolut is a fintech darling founded in July 2015 that has since raised $336 million in venture capital within four years at a $1.7 billion valuation according to Crunchbase.

Insane growth, huge market, real product. It’s the best first act for a startup one can possibly hope for.

Then the bad news started hitting hard this week. In act two, we get this Wired exposé by Emiliano Mellino that discusses the atrocious working conditions of the company along with deeply questionable employee interview tactics:

She did a 30-minute job interview over Google Hangouts with the London-based head of business development, Andrius Biceika, and was immediately told she had passed to the next round, which would involve a small test. “The surprise came when I received the task and it asked me to get the company as many clients as possible, with each one depositing €10 into the app,” says Laura.

And using fear to goad performance:

Last spring, CEO Nikolay Storonsky sent an announcement to all staff through the company’s Slack messaging service, saying that any members of staff “with performance rating [sic] ‘significantly below expectations’ will be fired without any negotiation after the review”.

…

Around this time, CEO Nikolay Storonsky gave an interview to Business Insider where he said Revolut’s philosophy was to “get shit done”, a slogan that is emblazoned on the company’s London office walls in bright neon lights. In an echo to what was going on in these calls, Storonsky would go on to say in the interview that the company attracted people that want to grow and “growing is always through pain”.

Well, there is more growth to come, because act three is going to bring a very painful episode for the company. My colleague Jon Russell noted that Revolut’s CFO has resigned in the wake of a Daily Telegraph investigation showing that Revolut had switched off the anti-money-laundering safeguards at the company, because, well, it got in the way of growth.

Let’s be clear: we all love a rapidly-growing startup. We all want to invest or join a winner. But what are we willing to forego to get it? Are we willing to push ethical boundaries? Are we willing to use dark patterns to force those numbers higher? Are we willing to break the law and potentially go to prison? Our love of growth often knows no bounds.

In context, I’m sure Revolut’s decision came easily, but of course, for disinterested observers, the idea that you would switch off the AML system at a banking startup just looks like complete stupidity. Yet, I am not sure I am ready to blame the employees of Revolut (or its leaders frankly) before I place the blame on a culture that demands extreme growth, and dislikes it when the consequences come to bear. You can’t get extreme growth without something breaking. We need to decide which value is more important for us.

Extra Crunch ethics series

Not sure we are going to be able to answer all the questions posed by Revolut, but Extra Crunch will be hosting a series of dialogues around tech ethics in the coming weeks that will try to parse some of the tough challenges that come from technology and startups these days. Stay tuned.

Why fundamental self-interest causes US infrastructure to fall flat on its face

Simon McGill via Getty Images

Written by Arman Tabatabai

Yesterday, DJ Gribbin, a fellow at Brookings and a senior US government infrastructure official, published an op-ed in which he attributes the US’ infrastructure struggles largely to 1) a misunderstanding of federal fund availability, 2) the fragmentation and variability of local infrastructure needs, and 3) misaligned incentives for local politicians and contractors.

Local politicians push heavily for the federal government to cover a portion of their bill, advertising the money as free to their constituents. In reality, investing federal funds is a zero-sum game that requires either more taxation, higher debt, or pulling money from elsewhere. What results are the competitive bid and bureaucratic review processes we discussed earlier this week that ultimately lead to gamesmanship and misinformation.

The federal-local coordination has grown more difficult as projects have become more localized with region-specific needs and benefits, compared to national projects of old like the highway system. Now, executing local developments depends on coordination between federal, state, and local governments, leading to the political pissing contests we all know and love.

In Gribbin’s mind, the biggest flaw in the US’ approach to infrastructure – also raised in our conversation with infrastructure expert Phil Plotch — is the misaligned incentive system that encourages bad behavior from all parties.

The complexity of approval and funding processes causes local politicians to either delay projects as they lobby for federal funding or to “overpromise and underdeliver” on costs and benefits to push a project through.

Similarly, competitive RFP bidding used to reduce cost estimates encourages contractors to similarly overpromise, leading to plan revisions, construction issues, and delays that seem to be inevitable for every major project. Clearly more needs to be done to align the incentives of each of these players.

Software and infrastructure

JayLazarin via Getty Images

Written by Arman Tabatabai

New York City rail operators grew frustrated this week with the contractors hired to install a new safety system. Fumbled management and failed execution on what was thought to be a simple tech integration have caused multi-year delays, potentially pushing completion past the deadline set by the Federal Railroad Administration for railroads across the country to upgrade their safety systems.

Only about one-tenth of the mandated rails had successfully upgraded their system as of last year as local agencies continue to struggle with designing software and hardware platforms compatible with other trains that may use their lines. That pattern is also found in New York. From the Wall Street Journal article:

The projects have suffered a series of setbacks because of understaffing by the contractors as well as software and hardware failures. Those failures include the recall of antennas that were installed on more than 1,000 rail cars and that were later found to be defective.

“It was a novice error and we did not believe we had hired novices,” MTA board member Susan Metzger said.

The New York project mimics issues plaguing projects throughout the US, where contractors use the “overpromise, underdeliver” strategy to win competitive bids. Add in software incompetence, and you get the mess that New York is facing now.

DC commutes suck more than in NYC and SF, even before Amazon materializes

Richard Sharrocks via Getty Images

Written by Arman Tabatabai

According to a new data set from Bloomberg, the cost of commuting into Washington D.C. is higher than any other metro in the US. Though density is clearly a factor here, workers in the greater D.C. area face the longest commute time in the country at nearly 80 minutes on average. Bloomberg then derived a “score” for the opportunity cost of commutes based on average annual incomes and average total annual commuting hours per worker, weighted based for other externalities such as how early or late average departures were.

D.C. is in the midst of seriously expanding its Metrorail system but, unsurprisingly, the project has gone far from smoothly. Bloomberg’s findings stress the need for an improved transit system in the region but based on precedent and progress to date it’s unclear if and when the full expansion will be complete and at what ungodly cost.

We’re planning on diving deeper into D.C.’s Metrorail expansion project as we read The Great Society Subway by Zachary Schrag, which just arrived at Extra Crunch HQ this week.

Obsessions

We have a bit of a theme around emerging markets, macroeconomics, and the next set of users to join the internet.

More discussion of megaprojects, infrastructure, and “why can’t we build things”

Thanks

To every member of Extra Crunch: thank you. You allow us to get off the ad-laden media churn conveyor belt and spend quality time on amazing ideas, people, and companies. If I can ever be of assistance, hit reply, or send an email to danny@techcrunch.com.

This newsletter is written with the assistance of Arman Tabatabai from New York

source https://techcrunch.com/2019/03/01/how-far-are-you-willing-to-go-for-growth/

[fmservers]

How far are you willing to go for growth?

There is a deep dilemma facing startup founders that I think just isn’t brought to light often enough. On one hand, almost all (and I do mean almost all) founders are reasonably ethical people. They can be over-optimistic, they can over-promise, they can be inexperienced around management, but at their core, they want to improve the world, build something new, and yes, make (a lot) of money while doing it.

Yet, if you really want to grow fast — so fast that you can go from piddling startup to $1.7 billion valued banking unicorn in less than four years — then there are only so many ways to do that ethically. Or even legally, given that the laws around industries like banking aren’t designed for high growth, but rather sedentary expansion.

Here’s a lesson that I think founders internalize very, very early: growth solves all problems. And it is absolutely, 100% true. Growth absolutely solves all problems. Want to make your next fundraise a cinch? If you grow 5x or 7x year-over-year, watch as dozens of venture firms squabble to get access to that cap table. Want to hire faster and attract better talent? Growing at top speed is an easy way to lock in those people.

And if you think the board acts as a guardrail, you have never seen the giddy excitement of a VC who is seeing their yacht / Napa vineyard / Atherton estate being financed before their very eyes. Boards don’t ask tough questions in periods of high growth, they double down: “do everything to keep this rocket ship shooting for the stratosphere.”

In these situations, it is nearly impossible to balance growth and ethics. You can’t just say, “turn on the money laundering thing again and we will accept 5x instead of 7x” or whatever. The whole organism of the startup has been geared for growth. Hell, even the people not working for the company (but want to) are geared for growth. Every salary bump, equity distribution, performance evaluation, feedback, KPI, and firing is predicated on growth.

Sometimes you get away with it, and sometimes you don’t. Uber got away with it, Zenefits did not.

So where does Revolut sit, which I’ve been foreshadowing here? By now, you might have come across the three-part story arc of Revolut, a digital banking service based in London. In part one, Revolut is a fintech darling founded in July 2015 that has since raised $336 million in venture capital within four years at a $1.7 billion valuation according to Crunchbase.

Insane growth, huge market, real product. It’s the best first act for a startup one can possibly hope for.

Then the bad news started hitting hard this week. In act two, we get this Wired exposé by Emiliano Mellino that discusses the atrocious working conditions of the company along with deeply questionable employee interview tactics:

She did a 30-minute job interview over Google Hangouts with the London-based head of business development, Andrius Biceika, and was immediately told she had passed to the next round, which would involve a small test. “The surprise came when I received the task and it asked me to get the company as many clients as possible, with each one depositing €10 into the app,” says Laura.

And using fear to goad performance:

Last spring, CEO Nikolay Storonsky sent an announcement to all staff through the company’s Slack messaging service, saying that any members of staff “with performance rating [sic] ‘significantly below expectations’ will be fired without any negotiation after the review”.

…

Around this time, CEO Nikolay Storonsky gave an interview to Business Insider where he said Revolut’s philosophy was to “get shit done”, a slogan that is emblazoned on the company’s London office walls in bright neon lights. In an echo to what was going on in these calls, Storonsky would go on to say in the interview that the company attracted people that want to grow and “growing is always through pain”.

Well, there is more growth to come, because act three is going to bring a very painful episode for the company. My colleague Jon Russell noted that Revolut’s CFO has resigned in the wake of a Daily Telegraph investigation showing that Revolut had switched off the anti-money-laundering safeguards at the company, because, well, it got in the way of growth.

Let’s be clear: we all love a rapidly-growing startup. We all want to invest or join a winner. But what are we willing to forego to get it? Are we willing to push ethical boundaries? Are we willing to use dark patterns to force those numbers higher? Are we willing to break the law and potentially go to prison? Our love of growth often knows no bounds.

In context, I’m sure Revolut’s decision came easily, but of course, for disinterested observers, the idea that you would switch off the AML system at a banking startup just looks like complete stupidity. Yet, I am not sure I am ready to blame the employees of Revolut (or its leaders frankly) before I place the blame on a culture that demands extreme growth, and dislikes it when the consequences come to bear. You can’t get extreme growth without something breaking. We need to decide which value is more important for us.

Extra Crunch ethics series

Not sure we are going to be able to answer all the questions posed by Revolut, but Extra Crunch will be hosting a series of dialogues around tech ethics in the coming weeks that will try to parse some of the tough challenges that come from technology and startups these days. Stay tuned.

Why fundamental self-interest causes US infrastructure to fall flat on its face

Simon McGill via Getty Images

Written by Arman Tabatabai

Yesterday, DJ Gribbin, a fellow at Brookings and a senior US government infrastructure official, published an op-ed in which he attributes the US’ infrastructure struggles largely to 1) a misunderstanding of federal fund availability, 2) the fragmentation and variability of local infrastructure needs, and 3) misaligned incentives for local politicians and contractors.

Local politicians push heavily for the federal government to cover a portion of their bill, advertising the money as free to their constituents. In reality, investing federal funds is a zero-sum game that requires either more taxation, higher debt, or pulling money from elsewhere. What results are the competitive bid and bureaucratic review processes we discussed earlier this week that ultimately lead to gamesmanship and misinformation.

The federal-local coordination has grown more difficult as projects have become more localized with region-specific needs and benefits, compared to national projects of old like the highway system. Now, executing local developments depends on coordination between federal, state, and local governments, leading to the political pissing contests we all know and love.

In Gribbin’s mind, the biggest flaw in the US’ approach to infrastructure – also raised in our conversation with infrastructure expert Phil Plotch — is the misaligned incentive system that encourages bad behavior from all parties.

The complexity of approval and funding processes causes local politicians to either delay projects as they lobby for federal funding or to “overpromise and underdeliver” on costs and benefits to push a project through.

Similarly, competitive RFP bidding used to reduce cost estimates encourages contractors to similarly overpromise, leading to plan revisions, construction issues, and delays that seem to be inevitable for every major project. Clearly more needs to be done to align the incentives of each of these players.

Software and infrastructure

JayLazarin via Getty Images

Written by Arman Tabatabai

New York City rail operators grew frustrated this week with the contractors hired to install a new safety system. Fumbled management and failed execution on what was thought to be a simple tech integration have caused multi-year delays, potentially pushing completion past the deadline set by the Federal Railroad Administration for railroads across the country to upgrade their safety systems.

Only about one-tenth of the mandated rails had successfully upgraded their system as of last year as local agencies continue to struggle with designing software and hardware platforms compatible with other trains that may use their lines. That pattern is also found in New York. From the Wall Street Journal article:

The projects have suffered a series of setbacks because of understaffing by the contractors as well as software and hardware failures. Those failures include the recall of antennas that were installed on more than 1,000 rail cars and that were later found to be defective.

“It was a novice error and we did not believe we had hired novices,” MTA board member Susan Metzger said.

The New York project mimics issues plaguing projects throughout the US, where contractors use the “overpromise, underdeliver” strategy to win competitive bids. Add in software incompetence, and you get the mess that New York is facing now.

DC commutes suck more than in NYC and SF, even before Amazon materializes

Richard Sharrocks via Getty Images

Written by Arman Tabatabai

According to a new data set from Bloomberg, the cost of commuting into Washington D.C. is higher than any other metro in the US. Though density is clearly a factor here, workers in the greater D.C. area face the longest commute time in the country at nearly 80 minutes on average. Bloomberg then derived a “score” for the opportunity cost of commutes based on average annual incomes and average total annual commuting hours per worker, weighted based for other externalities such as how early or late average departures were.

D.C. is in the midst of seriously expanding its Metrorail system but, unsurprisingly, the project has gone far from smoothly. Bloomberg’s findings stress the need for an improved transit system in the region but based on precedent and progress to date it’s unclear if and when the full expansion will be complete and at what ungodly cost.

We’re planning on diving deeper into D.C.’s Metrorail expansion project as we read The Great Society Subway by Zachary Schrag, which just arrived at Extra Crunch HQ this week.

Obsessions

We have a bit of a theme around emerging markets, macroeconomics, and the next set of users to join the internet.

More discussion of megaprojects, infrastructure, and “why can’t we build things”

Thanks

To every member of Extra Crunch: thank you. You allow us to get off the ad-laden media churn conveyor belt and spend quality time on amazing ideas, people, and companies. If I can ever be of assistance, hit reply, or send an email to danny@techcrunch.com.

This newsletter is written with the assistance of Arman Tabatabai from New York

Via Danny Crichton https://techcrunch.com

[theinvinciblenoob]

Alice Lloyd George Contributor

Alice Lloyd George is an investor at RRE Ventures and the host of Flux, a series of podcast conversations with leaders in frontier technology.

More posts by this contributor

Solving the mystery of sleep

A conversation with Dean Kamen on the myth of “Eureka!”

From Elon’s Neuralink to Bryan Johnson’s Kernel, a new wave of businesses are specifically focusing on ways to access, read and write from the brain.

The holy grail lies in how to do that without invasive implants, and how to do it for a mass market.

One company aiming to do just that is New York-based CTRL-labs, who recently closed a $28 million Series B. The team, comprising over 12 PHDs, is decoding individual neurons and developing an electromyography-based armband that reads the nervous signals travelling from the brain to the fingers. These signals are then translated into desired intentions, enabling anything from thought-to-text to moving objects.

Scientists have known about electrical activity in the brain since Hans Berger first recorded it using an EEG in 1924, and the term “brain computer interface” (BCI) was coined as early as the 1970s by Jacques Vidal at UCLA. Since then most BCI applications have been tested in the military or medical realm. Although it’s still the early innings of neurotech commercialization, in recent years the pace of capital going in and company formation has picked up. 

For a conversation with Flux I sat down with Thomas Reardon the CEO of CTRL-labs and discussed his journey to founding the company. Reardon explained why New York is the best place to build a machine learning based business right now and how he recruits top talent. He shares what developers can expect when the CTRL-kit ships in Q1 and explains how a brain control interface may well make the smartphone redundant. An excerpt is published below. Full transcript on Medium.

AMLG: I’m excited to have Thomas Reardon on the show today. He is the co-founder and CEO of CTRL-labs a company building the next generation of non-invasive neural computing here in Manhattan. He’s just cycled from uptown — thanks for coming down here to Chinatown. Reardon was previously the founder of a startup called Avegadro, which was acquired by Openwave. He also spent time at Microsoft where he was project lead on Internet Explorer. He’s one of the founders of the Worldwide Web Consortium, a body that has established many of the standards that still govern the Web, and he’s one of the architects of XML and CSS. Why don’t we get into your background, how you got to where you are today and why you’re the most excited to be doing what you’re doing right now.

W3 is an international standards organization founded and led by Tim Berners Lee.

TR: My background — well I’m a bit of an old man so this is a longer story. I have a commercial software background. I didn’t go to college when I was younger. I started a company at 19 years old and ended up at Microsoft back in 1990, so this was before the Windows revolution stormed the world. I spent 10 years at Microsoft. The biggest part of that was starting up the Internet Explorer project and then leading the internet architecture effort at Microsoft so that’s how I ended up working on things like CSS and XML, some of the web nerds out there should be deeply familiar with those terms. Then after doing another company that focused on the mobile Internet, Phone.com and Openwave, where I served as CTO, I got a bit tired of the Web. I got fatigued at the sense that the Web was growing up not to introduce any new technology experience or any new computer science to the world. It was just transferring bones from one grave to another. We were reinventing everything that had been invented in the 80s and early 90s and webifying it but we weren’t creating new experiences. I got profoundly turned off by the evolution of the Web and what we were doing to put it on mobile devices. We weren’t creating new value for people. We weren’t solving new human problems. We were solving corporate problems. We were trying to create new leverage for the entrenched companies.

So I left tech in 2003. Effectively retired. I decided to go and get a proper college education. I went and studied Greek and Latin and got a degree in classics. Along the way I started studying neuroscience and was fascinated by the biology of neurons. This led me to grad school and doing a Ph.D. which I split across Duke and Columbia. I’d woken up some time in like 2005 2006 and was reading an article in The New York Times. It was something about a cell and I scratched my head and said, we all hear that term we all talk about cells and cells in the body, but I have no idea what a cell really is. To the point where a New York Times article was too deep for me, and that almost embarrassed me and shocked me and led me down this path of studying biology in a deeper almost molecular way.

AMLG: So you were really in the heart of it all when you were working at Microsoft and building your startup. Now you are building this company in New York — we’ve got Columbia and NYU and there’s a lot of commercial industries — does that feel different for you, building a company here?

TR: Well let’s look at the kind of company we’re building. We’re building a company which is at its heart about machine learning. We’re in an era in which every startup tries to have a slide in their deck that says something about ML, but most of them are a joke in comparison. This is the place in the world to build a company that has machine learning at its core. Between Columbia and NYU and now Cornell Tech, and the unbelievably deep bench of machine learning talent embedded in the finance industry, we have more ML people at an elite level in New York than any place on earth. It’s dramatic. Our ability to recruit here is unparalleled. We beat the big five all the time. We’re now 42 people and half of them are Ph.D. scientists. For every single one of them we were competing against Google, Facebook, Apple.

AMLG: Presumably this is a more interesting problem for them to work on. If they want to go work at Goldman in AI they can do that for a couple of years, make some dollars and then come back and do the interesting stuff.

TR: They can make a bigger salary but they will work on something that nobody in the rest of the world will ever get to hear about. The reason why people don’t talk about all this ML talent here is when it’s embedded in finance you never get to hear about it. It’s all secret. Underneath the waters. The work we’re doing and this new generation of companies that have ML at their core — even a company like Spotify is, on the one hand fundamentally a licensing and copyright arbitrage company, but on the other hand what broke out for Spotify was their ML work. It was fundamental to the offer. That’s the kind of thing that’s happening in New York again and again now. There’s lots of companies — like a hardware company — that would be scary to build in New York. We have a significant hardware component to what we’re doing. It is hard to recruit A team world-class hardware folks in New York but we can get them. We recently hired the head of product from Peloton who formerly ran Makerbot.

AMLG: We support that and believe there’s a budding pool here. And I guess the third bench is neuro, which Columbia is very strong in.

Larry Abbott helped found the Center of Theoretical Neuroscience at Columbia

TR: Yes as is NYU. Neuroscience is in some sense the signature department at Columbia. The field breaks across two domains — the biological and the computational. Computational neuroscience is machine learning for real neurons, building operating computational models of how real neurons do their work. It’s the field that drives a lot of the breakthroughs in machine learning. We have these biologically inspired concepts in machine learning that come from computational neuroscience. Colombia has by far the top computational neuroscience group in the world and probably the top biological neuroscience group in the world. There are five Nobel Prize winners in the program and Larry Abbott the legend of theoretical neuroscience. It’s its an unbelievably deep bench.

AMLG: How do you recruit people that are smarter than you? This is a question that everyone listening wants to know.

Patrick Kaifosh, Thomas Reardon, Tim Machado the co-founders of CTRL-labs

TR: I’m not dumb but I’m not as smart as my co-founder and I’m not as smart as half of the scientific staff inside the company. I affectionately refer to my co-founder as a mutant. Patrick Kaifosh, who’s chief scientist. He is one of the smartest human beings I’ve ever known. Patrick is one of those generational people that can change our concept of what’s possible, and he does that in a first principles way. The recruiting part is to engage people in a way that lets them know that you’re going to take all the crap away that allows them to work on the hardest problems with the best people.

AMLG: I believe it and I’ve met some of them. So what was the conversation with Kaifosh and Tim when when you first sat down and decided to pursue the idea?

TR: So we were wrapping up our graduate studies, the three of us. We were looking at what it would be like to stay in academia and the bureaucracy involved in trying to be a working scientist in academia and writing grants. We were looking around at the young faculty members we saw at Columbia and thought, that doesn’t look like they’re having fun.

AMLG: When you were leaving Columbia it sounds like there wasn’t another company idea. Was it clear that this was the idea that you wanted to pursue at that time?

TR: What we knew is we wanted to do something collaborative. We did not think, let’s go build a brain machine interface. We don’t actually like that phrase, we like to call them neural interfaces. We didn’t think about neural interfaces at all. The second idea we had, an ingredient we put into the stew and started mixing up was, was that we wanted to leverage experimental technologies from neuroscience that hadn’t yet been commercialized. In some sense this was like when Genentech was starting in the mid 70s. We had found the crystal structure of DNA back in the late 40s, there had been 30 years of molecular biology, we figured out DNA then RNA then protein synthesis then ribosome. Thirty years of molecular biology but nobody had commercialized it yet. Then Genentech came along with this idea that we could make synthetic protein, that we could start to commercialize some of these core experimental techniques and do translation work and bring value back to humanity. It was all just sitting there on the shelf ready to be exploited.

We thought OK what are the technologies in neuroscience that we use at the bench that could be exploited? For instance spike sorting, the ability to listen with a single electrode to lots of neurons at the same time and see all the different electrical impulses and de-convolve them. You get this big noisy signal and you can see the individual neurons activity. So we started playing with that idea, lets harvest the last 30 or 40 years of bench experimental neuroscience. What are the techniques that were invented that we could harvest?

AMLG: We’ve been reading about these things and there’s been so much excitement about BMI but you haven’t really seen things in market things that people can hack around with. I don’t know why that gap hasn’t been filled. Does no one have the balls to go take these off the shelf and try and turn them into something or is it a timing question?

The brain has upper motor neurons in the cortex which map to lower motor neurons in the spinal cord, which send long axons down to contact the muscles. They release neurotransmitters that turn individual muscle fibres on and off. Motor units have 1:1 correspondence with motor neurons. When motor neurons fire in the spinal cord, an output signal from the brain, you get a direct response in the muscle. If those EMG signals can be decoded, then you can decode the zeros and ones of the nervous system — action potential

TR: Some of this is chutzpah and some of it is timing. The technologies that we are leveraging weren’t fully developed for how we’re using them. We had to do some invention since we started the company three years ago. But they were far enough along that you could imagine the gap and come up with a way to cross the gap. How could we, for instance, decode an individual neuron using a technology called electromyography. Electromyography has been around for probably over a century and that’s the ability to — 

AMLG: Thats what we call EMG.

TR: EMG. Yes you can record the electrical activity of a muscle. EKG electrocardiography is basically EMG for the heart alone. You’re looking at the electrical activity of the heart muscles. We thought if you improve this legacy technology of EMG sufficiently, if you improve the signal to noise, you ought to be able to see the individual fibers of a muscle. If you know some neuroanatomy what you figure out is that the individual fibers correspond to individual neurons. And by listening to individual fibers we can now reconstruct the activity of individual neurons. That’s the root of a neural interface. The ability to listen to an individual neuron.

EEG toy “the Force Trainer”

AMLG: My family are Star Wars fans and we had a device one Christmas that we sat around playing with, the force trainer. If you put the device around your head and stare long enough the thing is supposed to move. Everything I’ve ever tried has been like that has been like that Force Trainer, a little frustrating — 

TR: Thats EEG, electroencephalography. That’s when you put something on your skull and record the electrical activity. The waves of activity that happen in the cortex, in the outer part of your brain.

AMLG: And it doesn’t work well because the skull is too thick?

TR: There’s a bunch of reasons why it doesn’t work that well. The unfortunate thing is that when most people hear about it that’s one of the first things they think about like, oh well all my thinking is up here in the cortex right underneath my skull and that’s what you’re interfacing with. That is actually —

AMLG: A myth?

TR: Both a myth and the wrong approach. I’m going have to go deep on this one because it’s subtle but important. The first thing is let’s just talk about the signal qualities of EEG versus what we’re doing where we listen to individual neurons and do it without having to drill into your body or place an electrode inside of you. EEG is trying to listen to the activity of lots of neurons all at the same time tens of thousands hundreds of thousands of neurons and kind of get a sense of what the roar of those neurons is. I liken it to sitting outside of Giant Stadium with a microphone trying to listen to a conversation in Section 23 Row 4 seat 9. You can’t do it. At best you can tell is that one of the teams scored you hear the roar of the entire stadium. That’s basically what we have with EEG today. The ability to hear the roar. So for instance we say the easiest thing to decode with EMG is surprise. I could put a headset on you and tell if you’re surprised.

AMLG: That doesn’t seem too handy.

TR: Yup not much more than that. Turns out surprise is this global brain state and your entire brain lights up. In every animal that we do this in surprise looks the same — it’s a big global Christmas tree that lights up across the entire brain. But you can’t use that for control. And this cuts to the name of our company, CTRL-labs. I don’t just want to decode your state. I want to give you the ability to control things in the world in a way that feels magical. It feels like Star Wars. I want you to feel like the Star Wars Emperor. What we’re trying to do is give you control and a kind of control you’ve never experienced before.

The MYO armband by Canadian startup Thalmic Labs

AMLG: This is control over motion right? Maybe you can clarify — where I’ve seen other companies like MYO, which was an armband, it was really motion capture where people were capturing how you intended to gesture, rather than what you were thinking about?

TR: Yeah. In some sense we’re a successor to MYO (Thalmic Labs) — if Thalmic had been built by neuroscientists you would have ended up on the path that we’re on now.

Thomas Reardon demonstrating Myo control

We have two regimes of control, one we call Myo control and the other we call Neuro control. Myo control is our ability to decode what ultimately becomes your movements. The electrical input to your muscles that cause your muscles to contract, and then when you stop activating them they slowly relax. We can decode the electrical activity that goes into those muscles even before the movement has started and even before it ends and recapitulate that in a virtual way. Neuro control is something else. It’s kind of exotic and you have to try it to believe it. We can get to the level of the electrical activity of neurons — individual neurons — and train you rapidly on the order of seconds to control something. So imagine you’re playing a video game and you want to push a button to hop like you’re playing Sonic the Hedgehog. I can train you in seconds to turn on a single neuron in your spinal cord to control that little thing.

AMLG: When I came to visit your lab in 2016 the guy had his hand out here. I tried it — it was an asteroid field.

TR: Asteroids, the old Atari game.

Patrick Kaifosh playing Asteroids — example of Neuro Control [from CTRL-labs, late 2017]

AMLG: Classic. And you’re doing fruit ninja now too? It gets harder and harder.

TR: It does get harder and harder. So the idea here is that rather than moving you can just turn these neurons on and off and control something. Really there’s no muscle activity at that point you’re just activating individual neurons, they might release a little pulse, a little electrical chemical transmission to the muscle, but the muscle can’t respond at that level. What you find out is rather than using your neurons to control say your five fingers, you can use your neurons to control 30 virtual fingers without actually moving your hand at all.

AMLG: What does that mean for neuroplasticity. Do you have to imagine the third hand fourth hand fifth hand, or your tail like in Avatar?

TR: This is why I focus on the concept of control. We’re not trying to decode what you’re “thinking.” I don’t know what a thought is and there’s nobody in neuroscience who does know what a thought is. Nobody. We don’t know what consciousness is and we don’t know what thoughts are. They don’t exist in one part of the brain. Your brain is one cohesive organ and that includes your spinal cord all the way up. All of that embodies thought.

Inside Out (2015, Pixar). Great movie. Not how the brain, thoughts or consciousness work

AMLG: That’s a pretty crazy thought as thoughts go. I’m trying to mull that one over.

TR: It is. I want to pound that home. There’s not this one place. There’s not a little chair (to refer to Dan Dennett) there’s not like a chair in a movie theater inside your brain where the real you sits watching what’s happening and directing it. No, there’s just your overall brain and you’re in there somewhere across all of it. It’s that collection of neurons together that give you this sense of consciousness.

What we do with Neuro Control and with CTRL-kit the device that we’ve built is give you feedback. We show you by giving you direct feedback in real time, millisecond level feedback, how to train a neuron to go move say a cursor up and down, to go chase something or to jump over something. The way this works is that we engage your motor nervous system. Your brain has a natural output port — a USB port if you will — that generates output. In some sense this is sad for people, but I have to tell you your brain doesn’t do anything except turn muscles on and off. That’s the final output of the brain. When you’re generating speech when you’re blinking your eyes at me when you’re folding your hands and using your hands to talk to me when you’re moving around when you’re feeding yourself. Your brain is just turning muscles on and off. That’s it. There is nothing else. It does that via motor neurons. Most of those are in your spine. Those motor neurons, it’s not so much that they’re plastic — they’re adaptive. So motor control is this ability to use neurons for very adaptive tasks. Take a sip of water from that bottle right in front of you. Watch what you’re doing.

Intention capture — rather than going through devices to interact, CTRL-labs will take the electrical activity of the body and decode that directly, allowing us to use that high bandwidth information to interact with all output devices. [Watch Reardon’s full keynote at O’Reilly]

AMLG: Watch me spill it all over myself — 

TR: You’re taking a sip. Everything you just did with that bottle you’ve never done that before. You’ve never done that task. In fact you just did a complicated thing, you actually put it around the microphone and had to use one hand then use the other hand to take the cap off the bottle. You did all of that without thinking. There was no cognitive load involved in that. That bottle is different than any other bottle, its slippery it’s got a certain temperature, the weight changes. Have you ever seen these robots try to pour water. It’s comical how difficult it is. You do it effortlessly, like you’re really good —

AMLG: Well I practiced a few times before we got here.

TR: Actually you did practice! The first year two years of your life. That’s all you were doing was practicing, to get ready for what you just did. Because when you’re born you can’t do that. You can’t control your hands you can’t control your body. You actually do something called motor babbling where you just shake your hands around and move your legs and wiggle your fingers and you’re trying to create a map inside your brain of how your body works and to gain control. But gain flexible, adaptive control.

AMLG: That’s the natural training that babies do, which is sort of what you’re doing in terms of decoding ?

TR: We are leveraging that same process you went through when you were a year to two years old to help you gain new skills that go beyond your muscles. So that was all about you learning how to control your muscles and do things. I want to emphasize what you did again is more complex than anything else you do. It’s more complex than language than math than social skills. Eight billion people on earth that have a functioning nervous system, every other one of them no matter what their IQ can do it really well. That’s the part of the brain that we’re interfacing with. That ability to adapt in real time to a task skillfully. That’s not plasticity in neuroscience. It’s adaptation.

AMLG: What does that mean in terms of the amount of decoding you’ve had to do. Because you’ve got a working demo. And I know that people have to train for their own individual use right?

Myo control attempts to understand what each of the 14 muscles in the arm are doing, then deconvolve the signal into individual channels that map out to muscles. If they can build an accurate online map CTRL-labs believes there is no reason to have a keyboard or mouse 

  TR: In Myo control it works for anybody right out of the box. With Neuro control it adjusts to you. In fact the model that’s built is custom to you, it wouldn’t work on anybody else it wouldn’t work on your twin. Because your twin would train it differently. DNA is not determinative of your nervous output. What you have to realize is we haven’t decoded the brain —  there’s 15 billion neurons there. What we’ve done is created a very reduced but highly functional piece of hardware that listens to neurons in the spinal cord and gives you feedback that allows you to individually control those neurons.

When you think about the control that you exploit every day it’s built up of two kinds of things what we call continuous control — think of that as a joystick, left and right, and much left how much right. Those are continuous controls. Then we have discrete controls or symbols. Think of that as button pushing or typing. Every single control problem you face, and that’s what your day is filled with whether taking a sip of water walking down the street getting in a car driving a car. All of the control problems reduce to some combination of continuous control (swiping) and discrete control (button pushing.) We have this ability to get you to train these synthetic forms of up down left right dimensions if you will, that allows you to control things without moving but then allow you to move beyond the five fingers in your hand and get access to say 30 virtual fingers. What that opens up? Well think about everything you control.

AMLG: I’m picturing 30 virtual fingers right now —and I do want to get into VR, there’s lots of forms one can take in there. The surprising thing to me in terms of target uses and there’s so many uses you can imagine for this in early populations, was that you didn’t start the company for clinical populations or motor pathologies right? A lot of people have been working on bionics. I have a handicapped brother— I’ve been to his school and have seen the kids with all sorts of devices. They’re coming along, and obviously in the army they’ve been working on this. But you are not coming at it from that approach?

TR: Correct. We started the company almost ruthlessly focused on eight billion people. The market of eight billion. Not the market of a million or 10 million who have motor pathologies. In some sense this is the part that’s informed by my Microsoft time. So in the academy when you’re doing neuroscience research almost everybody focuses on pathologies, things that break in the nervous system and what we can do to help people and work around them. They’ll work on Parkinsons or Alzheimers or ALS for motor pathologies. What commercial companies get to do is bring new kinds of deep technology to mass markets, but which then feed back to clinical communities. By pushing and making this stuff work at scale across eight billion people, the problems that we have to solve will ultimately be the same problems that people who want to bring relief to people with motor pathologies need to solve. If you do it at scale lots of things fall out that wouldn’t have otherwise fallen out.

AMLG: It’s fascinating because you’re starting with we’re gonna go big. You’ve said you would like your devices, whether sold by you or by partners, to be on a million people within three or four years. A lot of things start in the realm of science but don’t get commercialized on a large scale. When you launched Explorer, at one point it had 95 percent market share so you’ve touched that many people before — 

Internet Explorer browser market share, 2002–2016

TR: Yes and it’s addicting, when you’ve been able to put software into a billion plus hands. That’s the kind of scale that you want to work on and that’s the kind of impact that I want to have and the team wants to have.

AMLG: How do you get something like this to that scale?

TR: One user at a time. You pick segments in which there are serious problems to solve and proximal problems. You’ve talked about VR. We think we solve a key problem in virtual reality augmented reality mixed reality. These emerging, immersive computing paradigms. No immersive computing technology so far has won. There is no default. There’s no standard. Nobody’s pointing at any thing and saying “oh I can already see how that’s the one that’s going to win.” It’s not Oculus it’s not Microsoft Hololens it’s not Magic Leap. But the investment is still happening and we’re now years into this new round of virtual realities. The investment is happening because people still have a hunger for it. We know we want immersive computing to work. What’s not working? It’s kind of obvious. We designed all of these experiences to get data, images, sounds into you. The human input problem. These immersive technologies do breakthrough work to change human input. But they’ve done nothing so far to change human output. That’s where we come in. You can’t have a successful immersive computing platform without solving the human output problem of how do I control this? How do I express my intentions? How do I express language inside of virtual reality? Am I typing or am I not typing?

AMLG: Everyone’s doing the iPad right now. You go into VR and you’re holding a thing that’s mimicking the real world.

TR: What we call skeuomorphic experiences that mimic real life, and that’s terrible. The first developer kits for the Oculus Rift you know shipped with an Xbox controller. Oh my god is that dumb. There’s a myth that the only way to create a new technology is to make sure it has a deep bridge to the past. I call bullshit on that. We’ve been stuck in that model and it’s one of the diseases of the venture world, “we’re Uber for neurons” and it’s Uber for this or that.

AMLG: Well ironically people are afraid to take risks in venture. If you suddenly design a new way of communicating or doing human output it’s, “that’s pretty risky, it should look more like the last thing.”

TR: I’m deeply thankful to the firms that stepped up to fund us, Spark and Matrix and most recently Lux and Google Ventures. We’ve got venture folks who want to look around the bend and make a big bet on a big future.

via TechCrunch

[disc-golf]

The 4 Most Important Reasons to Take a Vacation This Year

Nobody needs to tell you to take a vacation.

Or do they?

If you’re one of the 23% of Americans workers who take all of their PTO, then hats off to you. You get it.

But I’m betting you’re in the 77% camp—the employees who either don’t take all of their allotted time off, or end up working when they should be relaxing.

Instead of berating you for an inability to balance self-care and an iron-clad work ethic, let me say this: Vacation is the key to your sanity.

No really, it is. Before you close your screen and shuffle off to meetings or pressing emails, consider these very clear benefits to taking time off.

Rest

“Every person needs to take one day away. A day in which one consciously separates the past from the future. Jobs, family, employers, and friends can exist one day without any one of us, and if our egos permit us to confess, they could exist eternally in our absence. Each person deserves a day away in which no problems are confronted, no solutions searched for. Each of us needs to withdraw from the cares which will not withdraw from us.” ―Maya Angelou

You could live your life like a gladiator, vowing never to give up or walk away. But we all know that the human body physically needs rest. As the illustrious Maya Angelou said above, “Everyone needs to take one day away.”

Let me be more specific.

Rest reduces stress—that pesky byproduct of work that inhibits our ability to function at peak efficiency. When stress is the norm, some gradation of our fight or flight response is always in play; our heart beat is elevated, our blood pressure rises, our minds concentrate narrowly on solutions to single stress triggers instead of leveraging high-level thinking for more effective problem-solving.

Clearly, we aren’t at our best. But when we allow ourselves to rest—that is, relaxing away from work and other life pressures—we give our bodies a chance to move from “fight or flight” to well-adjusted normality. And when our bodies are functioning at normal levels and our minds are freed up to think more broadly, we are also able to sleep better.

Sleep, as most of us know, is key to proper physical and mental function. Among some of the primary benefits are:

Reduction of inflammation and the possibility of heart disease

Boosted immune system

Memory improvement

Don’t take my word for it, though. The National Institutes of Health have studied this for decades, and their overwhelming opinion is simple: Rest reduces stress which improve the ability to sleep which, in turn, makes us much healthier, happier, and more productive humans.

Experiencing a new environment and new adventures

”Jobs fill your pockets, but adventures fill your soul.” —Jaime Lyn

The last time I traveled to Europe, I was overwhelmed with ideas for writing projects. Heck, I conceived of entire miniseries with a flamboyant Parisian protagonist, hellbent on solving cold crimes in the love capital of the world.

Whether or not my series came to life is almost irrelevant (I’m still debating whether or not my protagonist should have a mustache); many of my character and plot ideas came from simple observations on the streets of Paris.

Now I’m convinced that those ideas would never have occurred to me sitting in front of my computer at home or rifling through books about travel. I needed to experience the travel firsthand.

While routines are tops for daily productivity, they can get stale. If you’re not careful, they can zap your creativity and push you into a rut of automatic motion. And sure, some of those routine habits are good, but to move ahead in life, you need to think outside the box.

This is a huge benefit of vacation. Changing scenery and experiencing new activities and adventures is a major boost to creativity. Not only this, but the challenges you face in a new setting, surrounded by different people, force you to adapt and be flexible—both invaluable skills in the office and at home.

Perhaps the greatest advantage to a change in scenery, however, is new perspective. Whether you’re traipsing through a South American jungle, trying a new cocktail on the beach, or wandering through the streets of a major European city, your perspective changes—you see people in new settings; you appreciate customs and cultures that you’ve never known before; and you learn to communicate with people whose lives are vastly different than your own.

New experiences, in short, feed your soul in a way most of our daily routines just don’t.

Spending time with close friends or loved ones

“At the end of your life, you will never regret not having passed one more test, not winning one more verdict, or not closing one more deal. You will regret time not spent with a husband, a friend, a child, a parent.” —Barbara Bush

There’s no shortage of evidence that time spent with family promotes a happy, healthy life—both for parents and children. Positive behavior is encouraged, emotional bonds are strengthened, self-esteem and self-worth are boosted, and memories are created that inform future behavior and emotional development.

But there’s something else to this time with loved ones that’s key for a workaholic. It’s easy in professional settings to feel the burden of expectation without support. Reconnecting with a spouse and children reinforces the support that is always present at home—as long as you let them in to support you. That support is emotional as much as it is mental; the ability to share work frustration in the right setting allows you to parse office challenges that you’d otherwise be left alone to handle. And trust me on this: Your family will thank you for making them a part of your WHOLE life, not just your home life.

On a much bigger scale, however, this connection can help you get to the root of mental blocks and emotional obstacles—the underlying elements that make any part of life difficult. A loving, caring relationship with friends and family give them the opportunity to hold up a mirror and show you yourself in a way that you couldn’t by dithering in self-doubt. While sometimes painful, this helps to overcome mental/emotional obstacles for improved health and happiness .

Lastly, time with family and friends is always a good way to remind you of your “why”—as Simon Sinek so famously puts it. These moments of connection are the opportunity to remember your underlying purpose and direction. Why are you working so hard in your career? Why did you choose it to begin with? Is it really the right fit for you? Have you even stopped to think about that? What are your priorities and goals?

Hard questioning and the revelations that follow are not always the most exciting or “fun” elements of a vacation, but they reset your compass in a way that the daily grind never would.

Enjoying quality alone time

“We need solitude, because when we’re alone, we’re free from obligations, we don’t need to put on a show, and we can hear our own thoughts.”  ―Tamim Ansary

Some of us are extraverts. Some are introverts. I’m in that awkward, fence-riding place where time spent with others both gives and saps a certain measure of energy.

But the interesting thing about both extraverts and introverts is that we all need alone time. Some of that is about reminding yourself of your needs, your purpose, your “why.” Some of it is processing information and experiences that you simply haven’t given yourself time to process. It’s no secret, after all, that our world is overburdened with information and that our ability to process it is stunted by the perceived urgency of everything. Is it any wonder we’re so stressed out?

But being alone is also about fundamentally restructuring the pieces of our lives in an arrangement that makes sense for US. It’s about acknowledging the extent to which our priorities get out of whack—often because of others’ influence and exhortation—and starting the process of reorganizing goals, priorities, and values.

#

If it needs be said, vacations are about more than endless umbrella cocktails and sun-soaked days. They are critical to our wellbeing in the present, and give us the health and perspective to take big swings in life further down the road.

Make that case to your boss the next time he argues with you a few days of PTO.

Time to turn your “why” into a purpose-driven Morning Routine.

Sign up now to get our FREE Morning Routine guide—the #1 way to increase productivity, energy, and focus for profitable days. Used by thousands of fitness, business, and finance industry leaders to leapfrog the competition while making time for the people who really matter. Learn more here.

The post The 4 Most Important Reasons to Take a Vacation This Year appeared first on Early To Rise.

[bythebayio]

Bradford Cross, DCVC, will not invest in your AI startup. Here’s why

A founding partner at DCVC, a seed and Series A venture capital firm whose portfolio includes Buoyant, Mesosphere, Circle CI, Mattermark, Gusto, Kaggle, Feedzai and many others, Bradford Cross invests in machine learning and AI-driven companies. Speaking at AI By The Bay about Machine Learning Startups that he previously founded and ran, Bradford is also part of AI VC panel on March 8. In advance of his appearance at AI By The Bay in San Francisco next week, Bradford has shared with us what still fascinates him about machine learning and AI and why he won’t invest in your AI startup.   

As a founder of two machine learning startups, what attracts you most in machine learning and AI?

BC: I’ve actually founded many AI companies beginning in 2002. First I founded two hedge funds, then Flightcaster and Prismatic, and now more as part of a bigger project that I can’t discuss at the moment.

I’ve always loved to build systems. As a kid I used to get remote control cars whenever possible, so that i could take them apart and build strange new things of questionable utility. Growing up, I was programming, building robots, and reading about space. I Was just your typical science and math kid with a penchant for dreaming big and tinkering.

AI is the ultimate domain for systems tinkerers. I think it is the most important field of our lifetimes both because the AI systems we’re building will have a big impact on their own, and because of how AI levers-up every other technical field. We will continue to deliver superior results to existing problems, and open up solutions to totally new problems that can’t even be envisioned without AI.

What’s not to be attracted to?!

Is there something in machine learning and AI that still fascinates you?

BC: I love this work and never cease to be fascinated every day. The list of topics i want to learn about is constantly growing. Despite the volume of reading I do, my reading list feels like it has somehow been monotonically increasing since 1999.

AI is such a broad and deep area across all the math, prob, stats, and CS that you can dig into. Then of course there are all the applications, and fields like NLP and Computer Vision.

I personally get most excited about interesting new applications that compose many datasets and methods -- using things like NLP and Computer Vision to extract features from text and images, then join those data with other datasets to tackle new prediction, classification, and ranking problems.

What’s not to be fascinated about?!

As an investor at DCVC, has the way you look at machine learning and AI-powered startups changed in comparison to when you were a part of the startups you founded?

BC: Yes, since I was very early in this new generation of AI startups (2008) and investing in them via DCVC (2011), I have seen a lot of data and have a fair bit of pattern matching. The most important things to weed out are 1) hammers looking for nails -- technical teams that are working forward from tech they think is interesting instead of working backward from a market need, 2) AAI (artificial artificial intelligence) startups that are riding the mania and just dropping in buzzwords.

Ultimately I want to see a strong market need that requires the core product value to be powered by AI, and a compounding effect of proprietary models built on proprietary data so that this core product value will be defensible over time.

What AI startup would you invest in now, what does it take to be the company that will get your attention? What metrics/aspects do you look at?

BC: I look at TAM, catalysts, whitespace, and the ability to have a compounding effect of proprietary models built on proprietary data. I think that team-product-fit and team-market-fit ultimately drive product-market-fit, so i want to see the right team for the product and market.

The only metric I care about is growth -- show me the number you are trying to grow, how fast it is growing, and explain why.

Whom would you like to connect with at AI By The Bay and who should speak to you after your session?  

BC: Anyone interested in working at a top secret AI incubator building vertical AI startups that solve the world’s largest and most timely industry problems. :)

I think that AI is in a mania, so I will probably not invest in your startup. Even if I were interested, you can almost certainly get a late entrant AI VC to supply you with a higher valuation.

Meet Bradford Cross at AI By The Bay on March 8 at the AI.Vision day.