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acosmicdisappointment · 9 months ago

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— enzo.

is that EMILIO SAKRAYA? oh, no, that’s LORENZO "ENZO" PERNAS, a TWENTY-SIX year old PERSONAL TRAINER AT GIMNASIO O2 AIRE who uses HE/HIM pronouns. they currently live in LAS TIERRAS DEL SOL IN QUILPUÈ, and the character they identify with most is THOR ODINSON FROM THE MCU. hopefully they find their own little paradise here in el país de los poetas!

BASICS.

FULL NAME. lorenzo pernas NICKNAME(S). enzo, zolo, lorry (ONLY by his mother) AGE/BIRTHDAY/ZODIAC. 26 / august 16th / leo SEXUALITY. bicurious BIRTHPLACE. berlin, germany HEIGHT. 6'1" EYE COLOR. dark brown ILLNESSES/CONDITIONS. a charismatic manipulative asshole TATTOOS/PIERCINGS/SCARS. eyebrow piercing (left), chest tattoos, minor scars from boxing (faint scar near his left eyebrow now covered by a piercing; facial scar (right side), knuckle scars, large scar from his right shoulder across his back now covered by tattoos) FC. emilio sakraya

PERSONALITY.

fiercely protective brave charismatic loud insensitive arrogant

HISTORY.

tw: manipulation, parental neglect if you will, body image — Enzo was a product of yet another forbidden romance between a wealthy married businessman and a singer/waitress. His father was a well-known charismatic yet manipulative public figure while his mother was a simple and humble individual. At that time, his mother wasn't aware of his father's other family (or that they were the other family) — He witnessed firsthand the power of manipulation. His father used guilt trips, gaslighting, and emotional blackmail to control those around him. He kept telling her that he would leave his family for them but he really wouldn’t. — As a child, Enzo became adept at reading people, understanding their vulnerabilities, and exploiting them to his advantage. This early exposure to manipulation shaped Enzo's worldview, leading him to believe that manipulating others was a necessary skill for survival (yikes) — Enzo constantly fought for affection and attention from his father. This struggle has left him with a deep-seated need for control and validation. — Moving to Valparaiso made it harder for Enzo to win his father's favor. The good boy act obviously didn’t work so he did the total opposite. — Enzo became a little reckless and he found out he thrived on attention. He enjoyed the thrill of keeping people guessing about his intentions, often blurring the lines between friendship and something more. Enzo was skilled at creating a sense of intimacy without ever truly committing, leaving those around him unsure of where they stood. — Enzo's inability to be clear about his boundaries left his partners feeling uncertain about where they stood, leading to misunderstandings and heartache (hi luna) — Somewhere in the middle of all that, Enzo found his love for fitness. The work he does for his body is an extension of his mask. He learned that if he works hard enough, he can use that appearance as leverage to get what he wants and he can use that to further whatever serves his narrative.

EXTRAS.

to read to see to listen

HEADCANONS.

— almost ALWAYS loses his keys (don’t ask him why) — would be the type to randomly challenge you to a fight (literally anywhere and anytime) — absolutely LOVES TO EAT (gym bod who?) — but is allergic to shrimp (the maximum he can eat is 6 pieces) — knows how to sing and play the guitar (y’know boy's down bad when he serenades his partner) — a big attention whore (srsly give him attention and you automatically got him hooked) — often goes shirtless (a way for him to show his bod, he's cocky like that i hate him) — just got back from Germany (he's still trying to get his father's attention poor boy)

WANTED CONNECTIONS/PLOTS.

tortured man club — a little group chat of men who strive to be better both as a partner and a person (or not who knows) enemies — sigh hello to the members of the 'enlozers (enzo is a loser) club™' make him your villain idc ride or die — enzo's a great friend if you give him a chance more tbd! you can definitely slide into my dms to plot

#valpohqintro #➷ — enzo: not so prince charming #enlozers (enzo is a loser) club™

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shadows-echoes · 6 years ago

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Writer’s Questionnaire

tagged by: @negotiator-on-site and @deviantramblings . Thank you guys for the tag! I spent way too long thinking about these tbh.

Short stories, novels, or poems?

For reading? Novels. I love absolutely delving into a world and completely immersing myself in it. In my experience, poems/short stories are like looking through a window: the more you look, the more you’ll probably see. Reading a novel, or an entire series, is more like walking through a door into another world, and that’s exactly what I want from a story. I want it to completely consume me.

With all of that being said, what’s the exact word count that draws the line between a short story and a novel? 10,000 words might be a short story, but is 25,000 still considered a short story? 100,000? 300,000? Where is the line drawn? Tbh, I’m 100% down with any long-ish story that draws me in.

As for writing… Imma keep it real with you chiefs, the shortest stories I’ve ever written are for D:BH. Pretty much every other fic of mine is 25+ pages, and a couple of the longer ones are closer to, or exceed, 180 pages. I haven’t finished those. They’re all drafts, so to speak, and the amount of editing needed makes me balk whenever I think about it, but they’re there. The stories that I’ve actually finished are all short-ish stories lol (at least in comparison to some of the other stuff I’ve written).

What genre do you prefer reading?

FANTASY!!!! We live in a non-fiction world that can be quite depressing at times. If I’m going to fling myself into a story, I want it to be magical. I want it to have something that this world doesn’t. I want magic and dragons and mystery and soulmates and forbidden love and all the crazy shit.

What genre do you prefer writing?

Fantasy/fiction.

Are you a planner or a write-as-I-go kind of person?

It depends on the story. Most times, I’ll write one scene and it develops into an entire plotline as I write it. Other times, like with Of Blood and Biocomponents for example, I’ll spend a lot of time planning everything out before I write it so I can work in a number of clues and Chekov’s guns’, etc.

What music do you listen to while writing?

When I really need to focus, I’ll listen to anything instrumental. That can range from soundtracks (e.g. from The Last of Us, LotR, Hans Zimmer’s stuff), to more individualized and upbeat songs (e.g. Lindsey Stirling, Peter Gundry, Max Richter, Hidden Citizens) to classical (e.g. Chopin, Wieniawski, Mozart), or even just ambiance rain sounds on youtube etc. Otherwise, when I need to get in the mood for a certain scene I have entire playlists dedicated to evoking a certain emotion (e.g angst -obviously-, sadness, love, adrenaline rushes).

Fave books/movies?

I don’t really have any favorite movies so I’m just going to list a whole bunch of books/series I love:

ACoTaR by Saraj Maas

Shatter Me by Tahereh Mafi

Learning Not to Drown by Anna Shinoda

Feminist Fight Club by Jessica Bennett

ASoIaF by George Rmartin Rmartingeorge Martin

The Mortal Instruments by Cassandra Clare

Speak by Laurie Halse Anderson (a classic that breaks my heart)

Night by Elie Wiesel (a classic that breaks my soul)

1984 by George Orwell (a classic we practically live in rn and it terrifies me)

Some Quiet Place by Kelsey Sutton

The Hunt by Andrew Fukuda (the plot twist at the end of this series blew me the fuck away. It’s been years and I still haven’t found my wig)

Any current WIPs?

Only around like… 16? (Excluding all of the half-formed ideas and prompts in my “Graveyard” folder, that is). Which is incredibly surprising to me? I thought it’d be way more. However, most of those WIPs are all… heartbreakingly long and only half-finished, so like ¯\_(ツ)_/¯

If someone were to make a cartoon out of you, what would your standard outfit be?

Lace-up combat boots, black jeans, and a random, probably blank, t-shirt.

Create a character description for yourself:

Hi, I’m Jayde, an average human person who thinks obsessively writing and learning new stuff are fun activities. I look like Idc but I actually care too much; I’m a ride-or-die bitch. Intovert™ (I would much rather have a first conversation w/ someone be about the trolly problem or systems theory instead of the weather). Often low-key enraged by society.

Do you like incorporating people you actually know into your writing?

Aspects of them? Of course. Actually writing them into a story? Nope. I totally draw on my experiences with certain people to help me write. That’s a given with any writer. However, unless I’m writing a biography on them with a full Chicago-style bibliography then I leave real people the heck alone.

Are you kill-happy with characters?

Depends on the characters. I have killed off a couple, but my soul is fueled on angst and there’s only so much of that a single death can provide. Nah, it’s usually better if people are alive and just… injured or... problematic.

Coffee or tea while writing?

I’m usually most productive writing-wise at night, so it’s either decaffeinated green tea or hot chocolate for me (bc I do try to have some kind of sleep schedule even if I fail with that goal).

Slow or fast writer?

So, so slow.

Where/who/what do you find inspiration from?

Anything, really. Sometimes an idea will just pop into my head and I’ll have to write it. Other times, it’ll start with a feeling, a situation, or an experience that slowly morphs into a fic the more I think about it.

If you were put into a fantasy world, what would you be?

Idk what I would be, but I’d love to be literally anything/anyone with some kind of magic or special ability. Like, bruh, I’m already human, gimme something else. Gimme some of the good shit.

Most fave book cliche? Least fave book cliche?

(Well-written) LOVE TRIANGLES AND MUTUAL PINING!!!!

I’m so fuckn horny on main for a good love triangle. When they’re done badly, they’re atrocious. That’s a given. But when they’re done well??? Hot damn. Like the kind of love triangles in ACoTaR, the Shatter Me series, or even the Trylle series (which first got me into it all). The kind where problems develop naturally between the MC and the first love interest, where the MC has to work with the “bad guy” for some reason or other and it turns out he’s actually super fuckn dope (*cough* Rhysand *Cough*). The kind where the more MC learns about the people she’s/he’s/they’re around, the more their feelings start to shift based on that knowledge.

I do not mean the kind where the MC just can’t make up her/his/their mind bc omg Hot Person #1 is so hot and looks to be carved from marble, but omg Hot Person #2 is also so hot, looks to be carved from marble, and is also mysterious.

As for a cliché I hate (if the poorly written love triangle doesn’t count in and of itself), I seriously dislike the damsel-in-distress thing. Don’t get me wrong, that card can be very well played in some cases, but when it’s the only card in the whole damn deck for 200, 300, 400+ pages? Nah, brah. I’m out. I’m certainly not asking for BAMF MC every time, but like,,, at least give the MC a goddamn spine you absolute cowards.

Fave scenes to write?

Pining and angst, baby.

Most productive time of day for writing?

The ungodly hours between night and day, when the outside world falls quietly into slumber and one’s imagination runs wild in the dark.

Reason for writing?

I started writing because I had some ideas and realized that nobody could/would write them in the exact way I imagined them except for me? I’ve continued writing because it has almost become a coping mechanism to explore and organize my thoughts and feelings and daydreams in some kind of coherent way. Plus it’s fun.

Tagging: @deviantsupporter @deviancy-wasteland @sunstrain @writerscavity @aerynwrites

#tag game #writing

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nicaurybenitezcortorreal-blog · 7 years ago

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9 IT projects primed for machine learning

Machine learning is fast becoming a reality for forward-thinking organizations. But for most businesses, the best way to take advantage of the capabilities of machine learning technologies remains something of a mystery. Still, the drumbeat to experiment keeps getting louder.

And the truth is, your competitors may already be laying the groundwork. IDC forecasts revenues for AI systems worldwide will almost double to $12.5 billion this year, and keep growing at a similar rate until they hit $46 billion in 2020. Some of that spending will go on hardware to run machine learning systems, but even if you don’t have the budget and the data scientists to build systems from scratch there are still plenty of tools and services that will let you use machine learning in practical ways that help your business.

[ Cut through the hype with our practical guide to machine learning in business and find out whether your organization is truly ready for taking on artificial intelligence projects. | Get an inside look at 3 machine learning success stories. | Get the latest insights with our CIO Daily newsletter. ]

Here are nine IT projects that almost any organization will find useful in getting started experimenting with machine learning technologies.

1. A customer service chatbot

If you have a list of frequently asked questions for customers to look up, you can turn that into a chatbot that can answer support questions using the Microsoft QnA Maker. It doesn’t have to be customer support, of course; you could create a bot to answer questions from new employees about HR benefits or how to contact the help desk.

Feed in the URL of your FAQ or upload spreadsheets and documents that have questions and answers and QnA Maker creates pairs of those questions and answers that you can review and train, and then call as an API. If you want to have a more interesting interface than just text replies, you can use the .NET SDK and the Microsoft Bot Framework to create a bot that shows pictures and rich content.

If you prefer the serverless approach, QnA Maker is one of the templates in the Azure Bot Service, so you can create a bot that works on email, GroupMe, Facebook Messenger, Kik, Skype, Slack, Microsoft Teams, Telegram, text/SMS and Twilio.

In the longer term, chatbots will evolve into intelligent agents more like Amazon Alexa and Microsoft Cortana. But rather than just answer individual questions, agents create a “goal-directed” conversation that works through the customer’s problem to help them solve it, which is what you need for ticket sales or diagnosing why a projector can’t connect. Microsoft has just added a customer care solution to Dynamics 365, in which a virtual agent suggests solutions, passes the customer on to human support, along with conversation details and the suggestions it made, if it can’t resolve the issue and learns what to do next time. HP, Macy’s and Microsoft’s own support service are already using this agent for online support.

2. Marketing automation and analytics

Marketing is often the first department to experiment with new technology, which is why marketing services like Adobe Marketing Cloud, Dynamics 365 and Salesforce are starting to offer machine learning predictions for everything from recommending related products for customers, to showing personalized search results, to classifying sales leads, to warning you when a deal is going cold, to finding alternate contacts at a potential customer company, even suggesting how and when to reach out to them. After all, predictive models for customer churn can help you with forecasting and planning.

If your marketing team isn’t already looking at these tools, this is a good way to apply machine learning directly to your bottom line. If they are, find out what’s working and look for other departments that could benefit from similar analytics. AXA is using a TensorFlow deep machine learning model with 70 variables to predict which customers are likely to have accidents that will cost the insurer more than $10,000, so it can optimize policy prices. Older models weren’t accurate enough to be useful, but with prediction accuracy improving from 40% to 78%, it might be good enough to consider when targeting potential customers.

3. Fraud detection

Spotting fraudulent and anomalous transactions is a classic data analytics problem, but if you’re doing it at a large scale, machine learning helps spot problematic activity such as scammers making multiple payments just under a trigger limit, new merchants exhibiting unusual behaviour and apparently legitimate customers who are connected to a network of scammers. Fraud.net uses Amazon Machine Learning to train multiple machine learning models to spot a range of fraudulent activity rather than trying to create a single model to score every possible kind of fraud; on any given day the merchants they protect might be facing a hundred different fraud schemes, each with dozens of variations.

Machine learning isn’t just useful for catching fraud by existing customers — insurers want to spot new applicants who plan to claim for a car that’s already been damaged before they issue a policy. And don’t just think about blocking bad transactions. Ford’s credit division is using machine learning tools from ZestFinance to predict the likelihood of specific borrowers paying back a loan so it can lend to people with lower credit scores. With car sales in the U.S. falling generally (and a slightly larger decline for Ford itself), finding buyers they’d otherwise turn down could be a big help to the business. Machine learning can help you tell good customers from bad risks more quickly.

4. ERP inventory planning

Supply chain automation isn't new, but machine learning is making it much more common. Instead of just historic sales data, machine learning lets you use data about the way customers research purchases on line, the impact of weather on shopping habits and other internal and external trends to manage inventory by forecasting demand. Amazon claims it can predict exactly how many shirts of a particular color and size it will sell every day; Target credits machine learning predictive models with 15-30% growth in revenue. Online German retailer Otto uses machine learning to predict what will sell in the next 30 days with 90% accuracy, reducing the amount of surplus stock by a fifth and lowering returns by more than 2 million products a year; the automated purchasing system orders 200,000 items a month from third-party suppliers, choosing the colors and styles that are predicted to sell.

5. Logistics route planning

The travelling salesman problem is a computer science classic: What’s the shortest route between all the places your sales team needs to go on a round trip? Whether it’s getting salespeople to prospects, deliveries to customers or picking the business location that will attract the most customers, routing and travel planning has a big impact on your business. You can use the predictive traffic services in the Bing and Google Maps APIs to create isochrone maps that show you not just distance but travel time, to compare how many customers an engineer could reach in a 15-minute drive from various starting points, or find the best time of day to make deliveries. (Use the preview Bing Maps Truck Routing API to get routings for commercial and service vehicles that are larger than the average car.)

Add in asset tracking and location triggers and you can create your own logistics solution. Or you can make shipping more profitable by quoting rates that accurately reflect your costs, rather than losing margin by underpricing or losing business by quoting too high. Business communications giant R.R. Donnelley used R and Azure Machine Learning Studio to lower the cautious estimates that kept it from winning freight bid by combining historical data with variables like the weather, fuel costs and market conditions to develop a better pricing model. The automated system that generates real-time quotes for a given route is more accurate; the company is already winning 4% more of its bids and expects to quadruple the size of its truckload brokerage business. The same kind of predictive analytics would be useful for any contract bids where you have enough data to build a good model.

6. IoT predictive maintenance

If you wait until machinery breaks to fix it, you have downtime and unhappy customers; if you take systems offline to do maintenance too often, you reduce your production yields. When ThyssenKrup started analyzing the maintenance records from the 1.1 million elevators it installs and services, it discovered that the maintenance window could be quite a bit longer than it was. When the company used Microsoft’s Azure IoT Suite to remotely monitor sensors, predict failures and pre-emptively service equipment, it didn’t just increase customer satisfaction by fixing problems before they caused a breakdown; they reduced costs by fixing more issues on the first visit, and by being able to predict better what spare parts they needed to carry in inventory. Do the same thing with a manufacturing line and you can improve production yields. According to Accenture’s 2016 report on industrial IoT, predictive maintenance could reduce the cost of scheduled repairs by 12%, bring down maintenance costs by 30% and reduce breakdowns by up to 70%.

7. Machine learning for security

In the complex world of security, machine learning isn’t a silver bullet, but it can help you spot attacks that might otherwise be lost in the logs and alerts triggered by normal activities. Despite the name, Windows Defender Advanced Threat Protection isn’t anti-virus software; it’s a machine learning service that analyzes the behavior of PCs on your network running Windows 10 Enterprise and tells your security team whether an attack is a malicious process, social engineering or a document exploit. You’ll still need to dig into logs and deal with the consequences, but machine learning security tools can help cut through the noise.

8. Unbias your recruitment

There’s a growing push for diversity in business, but the way your recruitment team words job postings can actually discourage a wider mix of applicants. Try the Textio service which uses AI to flag corporate jargon, clichés, cheesy stereotypes and other offputting phrases in job postings and recruitment emails to help you get a wider pool of people applying. SAP SuccessFactors has a similar tool.

9. Image recognition for manufacturing safety

Building sites and manufacturing lines are full of equipment that’s dangerous in the wrong hands. Using cameras and sensors, you can use image and facial recognition to detect when that equipment is being used unsafely, or by someone who hasn’t passed their safety training. Hitachi has built a deep learning system with DFKI, the German Research Center for Artificial Intelligence, that uses wearables and eye-tracking glasses. Microsoft demoed a similar solution at its Build conference using Azure Functions, Microsoft Cognitive Services and Azure Stack. A full workplace safety solution might be challenging to build, but you can start with smartphone apps like The Safety Compass, which works with Intellect SEEC’s machine learning Risk Analyst to let workers mark hazards in a workplace by snapping a photograph and filling in the details; other workers will get a warning when they get close to the hazard.

Next read this:

Source

http://cio.com/article/3231650/artificial-intelligence/9-it-projects-primed-for-machine-learning.html

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aws-certification · 5 years ago

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How Cloud Training Accelerates Cloud Adoption

Cloud training is essential if your organisation is one of the many considering a Cloud-First strategy. According to IDC’s Cloud View Survey, 70% of CIOs identified themselves as having this kind of strategy.

Over the next couple of years, even more organisations will move toward working completely in the cloud. Companies like Netflix and Time Inc. already do.

Moving to cloud is about more than technology though. Organisations need employees with a deep technical understanding of cloud.

This is why cloud training is so critical. Businesses shifting workloads to cloud can leverage cloud training to accelerate adoption, overcome concerns, and extend the benefits of cloud.

Contents

The Seven Stages of Cloud Adoption

The Importance of Cloud Training

Case Study: NAB Moves to Cloud

What is a Comprehensively Trained Organisation?

Cloud Training and C- Level Executives

Exploring the Benefits of Comprehensive Cloud Training

Equipping your Employees with the Right Skills

Different Types of Cloud Training

Developing a Cloud Training Plan for your Business

Dive Deeper into the Benefits of Cloud Training

What is Cloud-First?

Before we go any further, it’s important we define what we mean when we use the term Cloud-First.

In a Cloud-First strategy, when you review existing processes or create new ones, you consider cloud based solutions before others. In this kind of strategy the question for any app or workload isn’t “why cloud?” it’s “why not cloud?”.

The Seven Stages of Cloud Adoption

An easy way to picture a business’s path to Cloud-First is to divide the process into seven stages. Organisations move from one stage of adoption to the next. It’s only rarely that they regress to an earlier stage or skip one completely.

Obviously cloud training plays an important role in this journey, but we will touch on that later.

The stages of cloud adoption are:

No interest in cloud

Organisation educates themselves about cloud

Organisation evaluates cloud for specific workloads

Organisation plans to implement cloud services

Organisation uses cloud for 1-2 workloads

Organisation uses cloud for several workloads

Organisation uses cloud for all (or nearly all) workloads

According to research carried out by IDC, roughly 65% of organisations fall into stages five, six and seven. This means they are using cloud for at least one workload.

Only about 5% of organisations are at stage one, which means they have no interest in cloud computing.

The Importance of Cloud Training

Some businesses easily leverage cloud, quickly gaining benefits from limited integration; however, most organisations have more complex needs. Their cloud environments require careful planning and management from individuals who have undergone cloud training.

Without the right people with the right skills cloud adoption is slow and prone to mistakes. This makes it harder to keep C-level execs and other key decision makers on board. Cloud training provides the deep understanding of cloud technology that is required to cultivate such skills.

Case Study: NAB Moves to Cloud

To maintain a reputation as Australia’s number one bank for business, NAB has adopted an ambitious Cloud-First strategy. By investing $4.5BN over 3-years, NAB aims to have 35% of their 2,500 applications in the cloud by 2020. To reach this lofty goal they have invested heavily in cloud training.

At AWS Re:invent 2018, NAB’s former Cloud Chief, Yuri Misnik, talked about the need to “establish a training program that prepares our workforce with the necessary skills to enable our path to the cloud”. This program also gives employees the opportunity to “quickly ramp up on AWS technologies and develop skills that will enable them to innovate digital experiences for customers”.

For this reason the NAB Cloud Guild was established. This is a cloud training program designed to give employees opportunities to develop cloud computing skills. From beginners to professional developers, NAB Cloud Guild provides employees with the opportunity to acquire or build their cloud skills. This supports NAB’s digital transformation.

Currently NAB’s cloud migration is well ahead of schedule, with over 500 workloads moved to the cloud as of October 2019. This has only been possible through a significant investment in cloud training.

What is a Comprehensively Trained Organisation?

Investment in cloud training impacts how quickly organisations can adopt cloud. Although adoption isn’t the goal, the quicker a business can adopt cloud the more rapidly they will gain the benefits. Research shows businesses that invest in comprehensive cloud training benefit most and gain those benefits faster.

Comprehensively Trained Organisations are those that offer eight or more hours of training in a topic. This cloud training happens across multiple target audiences (IT teams, non-IT employees and teams etc.) across four or more topics.

Minimally Trained Organisations only offer cloud training for a single target audience on a single training topic.

Training and C-level Executives

Sure, you know the advantages of shifting to the cloud, but the minute things get difficult others may become sceptical. Without buy-in from upper management, there will be no trust in cloud based solutions (and no money to try them).

If business leaders, IT leaders, and C-level executives don’t have a common understanding of the true capabilities of a cloud-based infrastructure, the organisation may hesitate.

You need to build trust in the cloud to make this shift. Comprehensive cloud training is the best way to do this.

Organisations that want to get the most out of cloud should train a wide range of stakeholders on cloud fundamentals. Deep cloud training should be offered to key technical teams.

Find out more about getting executives excited about cloud here.

Exploring the Benefits of Comprehensive Cloud Training

Comprehensively trained organisations see significant benefits over those that are only minimally trained. These include*:

Simpler IT infrastructure: They are 2.2x more likely to agree that cloud can simplify and standardise IT infrastructure and applications

New capabilities, faster: They are 2.5x more likely to agree that cloud accelerates the addition of new technical and business capabilities

Improved use of resources: They are 4x more likely to agree that cloud improves the use of IT resources

Improved ability to scale: They are 3.7x more likely to understand how to successfully increase and decrease capacity on demand

Quicker to innovate: They are 2.7x more likely to agree that cloud jump-starts innovation

Improved global reach: They are 5.3x more likely to agree that cloud improves global reach of products and services, better serving clients

Across all of the concerns related to cloud adoption, comprehensively trained organisations have a lower sense of concern. They also have a greater belief that cloud can be customised to reduce any of these concerns.

For example, organisations that have undertaken comprehensive cloud training are better able to realistically assess security concerns. This includes implementing safeguards and building improved security processes when necessary.

*Source Train to Accelerate your Cloud Strategy, IDC white paper

Equipping your Employees with the Right Skills

For each employee that interacts with cloud you need to answer this question: what kind of cloud training do they need?

Put simply, the more important a skill, the more you need to invest in cloud training. This is where Global Knowledge’s Criticality of Skills Index comes in. This handy tool assists you in identifying the optimal training type based on what type of skills different employees need.

Learn more about the criticality of skills index here.

Different Types of Cloud Training

Now you understand the importance of comprehensive cloud training, let’s take a look at the specific types of training available. Not all cloud training is created equal, so it’s important to understand the pros and cons of each type.

Self-guided study: There’s a wide range of white papers, blog posts, webinars and other cloud computing resources available. These are perfect for IT professionals who want to dive deep into specific technical topics. Although this type of training is highly accessible and free, it lacks structure and external guidance.

Experiential learning: This occurs on teams when staff gain the practical knowledge needed to develop and operate in real cloud environments. Three to six months of hands-on experience will generally give an employee a good baseline of working knowledge. This can then be expanded on with formal training.

E-Learning: Online modules are a great fit for students that want to learn at their own pace in a structured environment. E-learning is generally cheaper than in-person equivalents but it lacks access to hands-on activities. Hands-on activities are critical to solidifying a student’s knowledge of cloud topics.

Blended training: This type of cloud training has been growing increasingly popular, combining e-learning modules with virtual classroom training. Although linked to better outcomes than e-learning alone, the lack of in-person elements means it is not as immersive as in-person training.

In-person instructor led training: In-person training provides students with time to focus on learning the cloud while having access to a qualified trainer. Students can ask questions directly and skills taught will be contextualised so they are immediately applicable to a working environment. Research has shown that this kind of cloud training delivers the best learning outcomes.

Private group training: This is instructor led training for the employees of one organisation. It is conducted onsite and the content delivered is catered specifically to the needs of that organisation. We offer private onsite training options for groups of 15 or more students studying the same course.

Developing a Cloud Training Plan for your Business

Integrating training into your organisation’s larger cloud strategy is key to hitting your objectives. Accordingly, you should engage with a cloud training provider as early as possible in your cloud adoption journey.

This is where we come in.

We work with your organisation to determine who on your team would benefit most from each type of training. We can also create a customised training plan based on your team’s cloud knowledge and goals. This gives you the ability to align cloud training to your objectives, minimise disruption and forecast your training spend.

Dive Deeper into the Benefits of Cloud Training

Congratulations, you now have an understanding of the benefits cloud training can bring. Your next step is to download the ‘Train to Accelerate your Cloud Strategy’ white paper from IDC.

This white paper is a deep dive into the insights explored in this blog post. It also contains case studies from organisations that have gained the benefits of comprehensive cloud training.

from Bespoke Training https://ift.tt/32TYdTa

#Bespoke Training

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topjobshub-blog · 5 years ago

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The Booming World Of Mobile Apps

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latestnews2018-blog · 6 years ago

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Robotics-as-a-service is on the way and inVia Robotics is leading the charge

New Post has been published on https://latestnews2018.com/robotics-as-a-service-is-on-the-way-and-invia-robotics-is-leading-the-charge/

Robotics-as-a-service is on the way and inVia Robotics is leading the charge

The team at inVia Robotics didn’t start out looking to build a business that would create a new kind of model for selling robotics to the masses, but that may be exactly what they’ve done.

After their graduation from the University of Southern California’s robotics program, Lior Alazary, Dan Parks, and Randolph Voorhies, were casting around for ideas that could get traction quickly.

“Our goal was to get something up and running that could make economic sense immediately,’ Voorhies, the company’s chief technology officer, said in an interview.

The key was to learn from the lessons of what the team had seen as the missteps of past robotics manufacturers.

Despite the early success of iRobot, consumer facing or collaborative robots that could operate alongside people had yet to gain traction in wider markets.

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Willow Garage, the legendary company formed by some of the top names in the robotics industry had shuttered just as Voorhies and his compatriots were graduating, and Boston Dynamics, another of the biggest names in robotics research, was bought by Google around the same time — capping an six-month buying spree that saw the search giant acquire eight robotics companies.

“In the midst of all this we were looking around and we said, ‘God there were a lot of failed robotics companies!’ and we asked ourselves why did that happen?” Voorhies recalled. “A lot of the hardware companies that we’d seen, their plan was: step one build a really cool robot and step three: an app ecosystem will evolve and people will write apps and the robot will sell like crazy. And nobody had realized how to do step 2, which was commercialize the robot.”

So the three co-founders looked for ideas they could take to market quickly.

The thought was building a robot that could help with mobility and reaching for objects. “We built a six-degree-of-freedom arm with a mobile base,” Voorhies said.

However, the arm was tricky to build, components were expensive and there were too many variables in the environment for things to go wrong with the robot’s operations. Ultimately the team at inVia realized that the big successes in robotics were happening in controlled environments.

“We very quickly realized that the environment is too unpredictable and there were too many different kinds of things that we needed to do,” he said.

Parks then put together a white paper analyzing the different controlled environments where collaborative robots could be most easily deployed. The warehouse was the obvious choice.

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Back in March of 2012 Amazon had come to the same conclusion and acquired Kiva Systems in a $775 million deal that brought Kiva’s army of robots to Amazon warehouses and distribution centers around the world.

“Dan put a white paper together for Lior and I,” Voorhies said, “and the thing really stuck out was eCommerce logistics. Floors tend to be concrete slabs; they’re very flat with very little grade, and in general people are picking things off a shelf and putting them somewhere else.”

With the idea in place, the team, which included technologists Voorhies and Parks, and Lazary, a serial entrepreneur who had already exited from two businesses, just needed to get a working prototype together.

Most warehouses and shipping facilities that weren’t Amazon were using automated storage and retrieval systems, Voorhies said. These big, automated systems that looked and worked like massive vending machines. But those systems, he said, involved a lot of sunk costs, and weren’t flexible or adaptable.

And those old systems weren’t built for random access patterns and multi-use orders which comprise most of the shipping and packing that are done as eCommerce takes off.

With those sunk costs though, warehouses are reluctant to change the model. The innovation that Voorhies and his team came up with, was that the logistics providers wouldn’t have to.

“We didn’t like the upfront investment, not just to install one but just to start a company to build those things,” said Voorhies. “We wanted something we could bootstrap ourselves and grow very organically and just see wins very very quickly. So we looked at those ASRS systems and said why don’t we build mobile robots to do this.”

In the beginning, the team at inVia played with different ways to build the robot.l first there was a robot that could carry several different objects and another that would be responsible for picking.

The form factor that the company eventually decided on was a movable puck shaped base with a scissor lift that can move a platform up and down. Attached to the back of the platform is a robotic arm that can extend forward and backward and has a suction pump attached to its end. The suction pump drags boxes onto a platform that are then taken to a pick and pack employee.

“We were originally going to grab individual product.s. Once we started talking to real warehouses more and more we realized that everyone stores everything in these boxes anyway,” said Voorhies. “And we said why don’t we make our lives way easier, why don’t we just grab those totes?”

Since bootstrapping that initial robot, inVia has gone on to raise $29 million in financing to support its vision. Most recently with a $20 million round which closed in July.

“E-commerce industry growth is driving the need for more warehouse automation to fulfill demand, and AI-driven robots can deliver that automation with the flexibility to scale across varied workflows. Our investment in inVia Robotics reflects our conviction in AI as a key enabler for the supply chain industry,” said Daniel Gwak, Co-Head, AI Investments at Point72 Ventures, the early stage investment firm formed by the famed hedge fund manager, Steven Cohen.

Given the pressures on shipping and logistics companies, it’s no surprise that the robotics and automation are becoming critically important strategic investments, or that venture capital is flooding int the market. In the past two months alone, robotics companies targeting warehouse and retail automation have raised nearly $70 million in new financing. They include the recent raised $17.7 million for the French startup Exotec Solutions and Bossa Nova’s $29 million round for its grocery store robots.

Then there are warehouse-focused robotics companies like Fetch Robotics, which traces its lineage back to Willow Garage and Locus Robotics, which is linked to the logistics services company Quiet Logistics.

“Funding in robotics has been incredible over the past several years, and for good reason,” said John Santagate, Research Director for Commercial Service Robotics at Research and Analysis Firm IDC, in a statement. “The growth in funding is a function of a market that has become accepting of the technology, a technology area that has matured to meet market demands, and vision of the future that must include flexible automation technology. Products must move faster and more efficiently through the warehouse today to keep up with consumer demand and autonomous mobile robots offer a cost-effective way to deploy automation to enable speed, efficiency, and flexibility.”

The team at inVia realized it wasn’t enough to sell the robots. To give warehouses a full sense of the potential cost savings they could have with inVia’s robots, they’d need to take a page from the software playbook. Rather than selling the equipment, they’d sell the work the robots were doing as a service.

“Customers will ask us how much the robots cost and that’s sort of irrelevant,” says Voorhies. “We don’t want customers to think about those things at all.”

Contracts between inVia and logistics companies are based on the unit of work done, Voorhies said. “We charge on the order line,” says Voorhies. “An order line is a single [stock keeping unit] that somebody would order regardless of quantity… We’re essentially charging them every time a robot has to bring a tote and present it in front of a person. The faster we’re able to do that and the less robots we can use to present an item the better our margins are.”

It may not sound like a huge change, but those kinds of efficiencies matter in warehouses, Voorhies said. “If you’re a person pushing a cart in a warehouse that cart can have 35 pallets on it. With us, that person is standing still, and they’re really not limited to a single cart. They are able to fill 70 orders at the same time rather than 55,” he said.

At Rakuten logistics, the deployment of inVia’s robots are already yielding returns, according to Michael Manzione, the chief executive officer of Rakuten Super Logistics.

“Really [robotics] being used in a fulfillment center is pretty new,” said Manzione in an interview. “We started looking at the product in late February and went live in late March.”

For Manzione, the big selling point was scaling the robots quickly, with no upfront cost. “The bottom line is ging to be effective when we see planning around the holiday season,” said Manzione. “We’re not planning on bringing in additional people, versus last year when we doubled our labor.”

As Voorhies notes, training a team to work effectively in a warehouse environment isn’t easy.

“The big problem is that it’s really hard to hire extra people to do this. In a warehouse there’s a dedicated core team that really kicks ass and they’re really happy with those pickers and they will be happy with what they get from whatever those people can sweat out in a shift,” Voorhies said. “Once you need to push your throughput beyond what your core team can do it’s hard to find people who can do that job well.”

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thehowtostuff-blog · 6 years ago

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