#Data Mining Tools Market
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Green energy is in its heyday.
Renewable energy sources now account for 22% of the nation’s electricity, and solar has skyrocketed eight times over in the last decade. This spring in California, wind, water, and solar power energy sources exceeded expectations, accounting for an average of 61.5 percent of the state's electricity demand across 52 days.
But green energy has a lithium problem. Lithium batteries control more than 90% of the global grid battery storage market.
That’s not just cell phones, laptops, electric toothbrushes, and tools. Scooters, e-bikes, hybrids, and electric vehicles all rely on rechargeable lithium batteries to get going.
Fortunately, this past week, Natron Energy launched its first-ever commercial-scale production of sodium-ion batteries in the U.S.
“Sodium-ion batteries offer a unique alternative to lithium-ion, with higher power, faster recharge, longer lifecycle and a completely safe and stable chemistry,” said Colin Wessells — Natron Founder and Co-CEO — at the kick-off event in Michigan.
The new sodium-ion batteries charge and discharge at rates 10 times faster than lithium-ion, with an estimated lifespan of 50,000 cycles.
Wessells said that using sodium as a primary mineral alternative eliminates industry-wide issues of worker negligence, geopolitical disruption, and the “questionable environmental impacts” inextricably linked to lithium mining.
“The electrification of our economy is dependent on the development and production of new, innovative energy storage solutions,” Wessells said.
Why are sodium batteries a better alternative to lithium?
The birth and death cycle of lithium is shadowed in environmental destruction. The process of extracting lithium pollutes the water, air, and soil, and when it’s eventually discarded, the flammable batteries are prone to bursting into flames and burning out in landfills.
There’s also a human cost. Lithium-ion materials like cobalt and nickel are not only harder to source and procure, but their supply chains are also overwhelmingly attributed to hazardous working conditions and child labor law violations.
Sodium, on the other hand, is estimated to be 1,000 times more abundant in the earth’s crust than lithium.
“Unlike lithium, sodium can be produced from an abundant material: salt,” engineer Casey Crownhart wrote in the MIT Technology Review. “Because the raw ingredients are cheap and widely available, there’s potential for sodium-ion batteries to be significantly less expensive than their lithium-ion counterparts if more companies start making more of them.”
What will these batteries be used for?
Right now, Natron has its focus set on AI models and data storage centers, which consume hefty amounts of energy. In 2023, the MIT Technology Review reported that one AI model can emit more than 626,00 pounds of carbon dioxide equivalent.
“We expect our battery solutions will be used to power the explosive growth in data centers used for Artificial Intelligence,” said Wendell Brooks, co-CEO of Natron.
“With the start of commercial-scale production here in Michigan, we are well-positioned to capitalize on the growing demand for efficient, safe, and reliable battery energy storage.”
The fast-charging energy alternative also has limitless potential on a consumer level, and Natron is eying telecommunications and EV fast-charging once it begins servicing AI data storage centers in June.
On a larger scale, sodium-ion batteries could radically change the manufacturing and production sectors — from housing energy to lower electricity costs in warehouses, to charging backup stations and powering electric vehicles, trucks, forklifts, and so on.
“I founded Natron because we saw climate change as the defining problem of our time,” Wessells said. “We believe batteries have a role to play.”
-via GoodGoodGood, May 3, 2024
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Note: I wanted to make sure this was legit (scientifically and in general), and I'm happy to report that it really is! x, x, x, x
#batteries#lithium#lithium ion batteries#lithium battery#sodium#clean energy#energy storage#electrochemistry#lithium mining#pollution#human rights#displacement#forced labor#child labor#mining#good news#hope
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whats wrong with ai?? genuinely curious <3
okay let's break it down. i'm an engineer, so i'm going to come at you from a perspective that may be different than someone else's.
i don't hate ai in every aspect. in theory, there are a lot of instances where, in fact, ai can help us do things a lot better without. here's a few examples:
ai detecting cancer
ai sorting recycling
some practical housekeeping that gemini (google ai) can do
all of the above examples are ways in which ai works with humans to do things in parallel with us. it's not overstepping--it's sorting, using pixels at a micro-level to detect abnormalities that we as humans can not, fixing a list. these are all really small, helpful ways that ai can work with us.
everything else about ai works against us. in general, ai is a huge consumer of natural resources. every prompt that you put into character.ai, chatgpt? this wastes water + energy. it's not free. a machine somewhere in the world has to swallow your prompt, call on a model to feed data into it and process more data, and then has to generate an answer for you all in a relatively short amount of time.
that is crazy expensive. someone is paying for that, and if it isn't you with your own money, it's the strain on the power grid, the water that cools the computers, the A/C that cools the data centers. and you aren't the only person using ai. chatgpt alone gets millions of users every single day, with probably thousands of prompts per second, so multiply your personal consumption by millions, and you can start to see how the picture is becoming overwhelming.
that is energy consumption alone. we haven't even talked about how problematic ai is ethically. there is currently no regulation in the united states about how ai should be developed, deployed, or used.
what does this mean for you?
it means that anything you post online is subject to data mining by an ai model (because why would they need to ask if there's no laws to stop them? wtf does it matter what it means to you to some idiot software engineer in the back room of an office making 3x your salary?). oh, that little fic you posted to wattpad that got a lot of attention? well now it's being used to teach ai how to write. oh, that sketch you made using adobe that you want to sell? adobe didn't tell you that anything you save to the cloud is now subject to being used for their ai models, so now your art is being replicated to generate ai images in photoshop, without crediting you (they have since said they don't do this...but privacy policies were never made to be human-readable, and i can't imagine they are the only company to sneakily try this). oh, your apartment just installed a new system that will use facial recognition to let their residents inside? oh, they didn't train their model with anyone but white people, so now all the black people living in that apartment building can't get into their homes. oh, you want to apply for a new job? the ai model that scans resumes learned from historical data that more men work that role than women (so the model basically thinks men are better than women), so now your resume is getting thrown out because you're a woman.
ai learns from data. and data is flawed. data is human. and as humans, we are racist, homophobic, misogynistic, transphobic, divided. so the ai models we train will learn from this. ai learns from people's creative works--their personal and artistic property. and now it's scrambling them all up to spit out generated images and written works that no one would ever want to read (because it's no longer a labor of love), and they're using that to make money. they're profiting off of people, and there's no one to stop them. they're also using generated images as marketing tools, to trick idiots on facebook, to make it so hard to be media literate that we have to question every single thing we see because now we don't know what's real and what's not.
the problem with ai is that it's doing more harm than good. and we as a society aren't doing our due diligence to understand the unintended consequences of it all. we aren't angry enough. we're too scared of stifling innovation that we're letting it regulate itself (aka letting companies decide), which has never been a good idea. we see it do one cool thing, and somehow that makes up for all the rest of the bullshit?
#yeah i could talk about this for years#i could talk about it forever#im so passionate about this lmao#anyways#i also want to point out the examples i listed are ONLY A FEW problems#there's SO MUCH MORE#anywho ai is bleh go away#ask#ask b#🐝's anons#ai
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Webtoons Is Making Moves - So Should You.
We all saw it coming ages ago and now it's finally here. There's no more beating around the bush or doubting if anyone is "reading into it too much", Webtoons' use of AI in its more recent webtoons is not an accident, not an oversight, but by design, it always has been. And I guaran-fucking-tee you that the work that already exists on the platform won't be safe from Webtoons' upcoming AI integration through scraping and data mining. Sure, they can say they're not gonna replace human creators, but that doesn't change the fact that AI tools, in their current form, can't feasibly exist without stealing from pre-existing content.
Plus, as someone who's tested their AI coloring tools specifically... they're a long, LONG way away from actually being useful. Like, good luck using them for any comic style that isn't Korean manwha featuring predominantly white characters with small heads and comically long legs. And if they do manage to get their AI tools to incorporate more art styles and wider ranges of character identities... again, what do you think it's been trained on?
Also, as an added bit that I found very funny:
Um, I'm sorry, what fucking year is it? Because platforms like WT and Tapas have both been saying this for years but we're obviously seeing them backpedal on that now with the implementation of in-house publishing programs like Unscrolled which have reinvented the wheel of taking digital webtoons and going gasp physical! It's almost like the platform has learned that there's no sustainable profit to be had in digital comics alone without the help of supplementary streams of income and is now trying to act like they've invented physical book publishing!
"The future of comic publishing, including manga, will be digital"??? My brother in christ, Shonen Jump has been exclusively digital since 2012! What rock have the WT's staff been living under that they're trying to sell digital comics as the "future" to North Americans as if we haven't already been living in that future for over ten years now?? We've had an entire generation of children raised on that same digital media since then! This isn't the selling point you think it is LMAO If anything, the digital media market here in NA is dying thanks to the enshittification of digital content platorms like Netflix, Disney+, and mainstream social media platforms! That "future" is not only already both the past and present, but is swiftly on its way out! Pack it up and go home, you missed the bus!
Literally so much of WT's IPO pitch is just a deadass grift full of corporate buzzwords and empty promises. They're trying so hard to convince people that their business model is infinitely profitable... but if it were, why do they need the public's money? And where are all those profits for the creators who are being exploited day after day to fill their platform with content? Why are so many creators still struggling to pay their bills if the company has this much potential for profit?
Ultimately even their promised AI tools don't ensure profit, they ensure cutting expenses. The extra money they hope to make isn't gonna come from their content generating income, it's gonna come from normal people forking over their money in the hopes that it'll be turned around, and from Webtoons cheapening the medium even further until it's nothing but conveyer belt gruel. Sure, "making more than you spend" is the base definition of "profit", but can we really call it that when it's through the means of gutting features, retiring support programs, letting go editing staff, and limiting resources for their own hired freelancers who are the only reason they even have content to begin with? That's not sustainable profit or growth, that's fighting the tide which can and will carry them away at any moment.
I'm low key calling it now, a year or two from today we're gonna be seeing massive lawsuits and calls to action from the people who invested their money into WT and subsequently lost it into the black hole that is WT's "business model". This is a company that's been operating in the red for years, what about becoming an IPO is gonna make them "profitable"? Let alone profitable enough to pay back their investors in the spades they're expecting? The platform and its app are already shit and they're about to become even worse, we are literally watching this company circle the drain in the modern day's ever-ongoing race to the bottom, enshittification in motion, but they're trying to convince us all the same that they're "innovating".
Webtoons doesn't want to invest in its creators. We as creators need to stop investing in them.
#fuck webtoons#who wants to bet that WT will either start gatekeeping its creator features behind paywalls#or start selling your creator data - including your image assets that you submit to the site - to make their AI integrations “profitable”#call me crazy but this is 2024#webtoon critical#this also low key proves my theories that WT was simply outsourcing NA creators for pennies#all so they could build their market and then flood it with their own home turf content#and shove out the NA creators whose backs and labor and blood they built that market on
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Why we’re against AI as a writing tool
Sophisticated AI tools like ChatGPT are the result of systemic, shameless theft of intellectual property and creative labor on a massive scale. These companies have mined the data of human genius… without permission. They have no intention of acknowledging their stolen sources, let alone paying the creators.
The tech industry’s defense is “Well, we stole so much from so many that it kinda doesn’t count, wouldn’t ya say?” Which is an argument that makes me feel like the mayor of Crazytown. I don’t doubt the courts will rule in their favor, not because it’s right, but because the opportunities for wealth generation are too succulent to let a lil’ thang like fairness win.
I’m not a luddite. I recognize that AI feels like magic to people who aren’t strong writers. I’d feel differently if the technology was achieved without the theft of my work. Couldn’t these tools have been made using legally obtained materials? Ah, but then they wouldn’t have been first to market! Think of the shareholders!
We’re lucky to have the ability and will to write. We won’t willingly use tools that devalue that skill. At most, I could see us using AI to assist with specific, narrow tasks like transcribing interview audio into text.
At a recent industry meetup, I listened as two personal finance gurus gushed about how easy AI made their lives. “All my newsletters and blogs are AI now! I add my own touches here and there—but it does 95% of the work!” Must be nice, I whispered to the empty void where my faith in mankind once dwelt, fingernails digging into my palms. It’s tough knowing I’m one of the myriad voices “streamlining their production.”
I feel strongly that every content creator who uses AI has a minimum duty to acknowledge it. Few will. It sucks. I’m frothing. Let’s move on.
Read more.
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Tools of the trade
Came home an hour ago from a reception I literally fled (busy week in this respect, unfortunately). And I kept being internally nagged during the short taxi ride, by what is probably at least this season's Anon. Landed in @bat-cat-reader's inbox with regard to Marple's most recent innuendo:
I had to know more about this, since I had no idea such deep diving tools were now available for pretty much everyone. Here's the gist of how it works, in pics and a quick review:
What Snoopreport promises its subscribers is to basically keep them posted on the targeted accounts' online behavior patterns...
... without the need to publicly follow them on Insta (sounds familiar?)...
...leaving no trace (zero accountability, because it uses only public data: this can be interpreted differently, in a different legal system/context, since several European countries, as I already discussed, have more protective legal provisions for a person's right to his/her own image)...
... at minimal costs (I suppose the most cost-effective, if we assume this is one of the used monitoring tools, would be the small business pack, allowing the super sleuth to track 10 different accounts, for peanuts):
A review of this product I have checked here (https://www.techuntold.com/snoopreport-review/) points out the obvious Achilles' heel of this app. Snoopreport obviously does not work for private accounts:
Which brings up a logical question: could the (in)famous 'resource' be S's private Insta account, in which case it would be very difficult for the sleuth to admit stalking it? Is it even technically possible to stalk a private Instagram account and remain unseen?
The answer to the latter is yes: other actors of this apparently very lucrative market, such as Glassagram (https://glassagram.com/), do not have Snoopreport's scruples and monitor even private accounts.
I think this is pretty self-explanatory and to be honest, it gave me the chills:
Serious reviews (https://www.techuntold.com/glassagram-review-spy-instagram/) are raving about this one, calling it the best app on the market, mainly because you can save all the snooped content on your own device:
... and the price, for stalking (their own choice of vocabulary, not mine, for once) an unlimited number of accounts is reasonable:
Best of it? They've been around since 2017.
In a nutshell: is it legal? it would seem so, in the US, not so sure about the UK/EU. Is it moral? It's up to you to decide what to think of a firm which has no problem admitting to encouraging stalking (but hey, don't listen to the nutcase here, huh?) and uses completely different real-life situations (infidelity, kids' monitoring) to assert its legitimacy and utility.
What I mean by this very long and illustrative post is this: you do not need inside sources/information to have one day the idea of crossing what is obviously (at least in my book) a red line. You just have to be able (lots of free time), willing (asserting power over a very thirsty and not so digitally skilled audience) and voilà: a Super Sleuth is born.
It is one thing to analyze and speculate, based on open sources, to your heart's content. It is a different affair altogether to obsessively monitor someone, with so much detail and personal (& financial) investment, over a substantial period of time. I will die on this hill and you will never change my mind on this one.
Is the emperor naked? I wouldn't venture speculating. What I do know, is that this emperor is a very, very sad one.
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WHY DYSTOPIA MUST BE BORING TO SUCCEED
The "Boring Dystopia Strategy" is a highly strategic and often subtle method employed by those in power to create an enduring, all-encompassing authoritarian government. The genius of this approach is that it doesn't look like a dystopia at first glance. Each step toward oppression is disguised as a necessary solution to a societal problem, creating a series of small, unassuming changes that collectively transform society into a high-surveillance, debt-ridden, and highly regulated landscape. The result is a quiet but relentless march towards a government structure that controls nearly every aspect of daily life, cloaked in the language of safety, responsibility, and "public good."
Key Components of the Boring Dystopia Strategy
Enhanced Surveillance as Crime Prevention Surveillance systems are marketed as tools to make communities safer. The rationale is straightforward: if there are cameras everywhere, criminals are less likely to act. At first, this seems like a good idea. However, as surveillance expands, it reaches a point where privacy no longer exists—every action and interaction is tracked and recorded. People's movements, purchases, conversations, and even thoughts (through social media and data mining) become data points in a government database. The population is conditioned to accept surveillance under the guise of crime prevention, even though the surveillance network eventually exists to deter any resistance to the growing system of control.
Financial "Disincentives" as a Form of Behavior Control Insurance companies, incentivized by government policies, implement "dynamic" pricing models that penalize risky behavior. Drivers with even minor infractions, young drivers, or anyone with imperfect credit face skyrocketing insurance costs. While it’s presented as a means to reward safe drivers and reduce accidents, it’s ultimately a method of forcing people into line. Over time, these small financial penalties accumulate, and as people find themselves unable to afford the rising costs, they are pushed further into debt or forced to depend on the very government that created the conditions of their hardship.
The Department of Bureaucracy: A Growing Web of Useless Jobs New laws and regulations are introduced to solve every conceivable social issue, resulting in bloated departments filled with superfluous workers whose roles add no real value to society. The justification is often to create jobs and stimulate the economy, but these positions end up creating layers of bureaucracy that slow down meaningful progress. This web of inefficiency puts financial strain on both the government and the people, leading to higher taxes and fees. With each new law or regulation, the cost of compliance grows, straining both businesses and individuals who can't afford to play by an ever-increasing list of rules.
Rising Cost of Living as an Inevitable "Economic Shift" As government regulations add costs to every industry, prices naturally increase. This is explained away as the cost of progress or as an unfortunate byproduct of addressing critical social issues, like "ethical sourcing" or "green initiatives" that are actually revenue-boosters for corporations. As inflation rises and wages stagnate, the lower class is squeezed financially. Each attempt to improve their situation—whether by taking a second job or reducing expenses—is offset by further price increases or surprise taxes. This creates a cycle where economic mobility is nearly impossible, locking the lower class in place.
Debt as a Tool for Control As the cost of living rises, debt becomes unavoidable for many. Loans, credit cards, and financing options are promoted as solutions, pushing people into a system of lifelong debt repayment. With growing financial obligations and little hope of ever breaking free, individuals are forced to work harder, often taking on additional jobs, which leaves them with less time and energy to question or resist the system. Debt chains the population to the very system that oppresses them, creating a sense of dependency on government stability, even as that stability is the source of their financial despair.
The Final Stage: Disempowerment Disguised as "Efficiency"
As the population is weakened by financial strain, endless surveillance, and a tangled bureaucracy, the final stage involves introducing measures to "simplify" governance. This might mean fewer elected officials, streamlined decision-making processes, and the merging of regulatory bodies for "efficiency." In reality, this final stage centralizes power even further, leaving those at the top with almost unchecked authority, a situation that the people, too exhausted and indebted to resist, accept as necessary.
The Boring Dystopia Strategy works because it does not announce itself as an authoritarian takeover. Instead, it subtly shifts the balance of power by presenting every oppressive measure as a solution to a social ill. And because each step is introduced slowly, over decades, the population becomes accustomed to the new reality, accepting surveillance, debt, and regulation as the normal costs of a safe and responsible society. By the time people realize the extent of their powerlessness, the dystopian state is fully entrenched, with every escape route closed off.
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i'm not deleting my tumblr blogs but this whole debacle with the AI stuff is discouraging me to at least not post original content here and limit my time on social media in general. Also to be clear on my stance on AI, which I think is very much influenced by my background as both an artist and a professional graphic designer: I think it can be a very useful tool and I don't even necessarily inherently find it completely harmful. Some forms of AI are already well used and completely normalized, but I find most of the time generative AI as we know it is pretty harmful and its harms outweighs its benefits currently (largely grifts, scams and misinfo). It needs regulation desperately, but old cunt politicians are too dumb to really care about or understand how important the issue is right now. I do not believe that AI will simply peter off or crash. From a marketing standpoint, i feel like AI usage will cool off or become more specialized (like creating whole machines *just* trained on individual brands for personal use and whatnot) but I have no idea how far away that would be. I just believe there might come a time where everyone is over the "spectacle" of generative AI and will find it inaffective or inherently associated with cheapness. At least in the most base sense in advertising, it is generally much better to have your own photographs and original branded artwork as it proves authenticity. You can only see a illusionist do so many tricks before you're bored by them and expect them, and we're already getting to the point where even the average Joe is tired of hearing about AI and the future, and at least when it comes to art and writing i just... don't care? i don't give a shit about it. BACK TO TUMBLR: I'm aware that its likely that mine and everyone elses' posts here have already been scraped. My thing is that it's more the symbolism of Tumblr's "opt-out" choice: memorial blogs, inactive blogs, and so on are going to be scraped without consent. No banners or pop ups to notify users of this change, you either have to either HAPPEN UPON to see staff's post or see others talk about it to even know about it. Since the beginning of this whole AI boom i had no issue with AI data training as long as it's consentual and ethical, but obviously it most of the time isnt. Tumblr's method of rolling out this change was purposely underhanded. I'm never going to simply be "okay" or normalize in my mind the fact that big tech companies feel entitled to people's privacy- which i believe extends to our online lives. I don't think myself or anyone else should ever feel completely apathetic to the fact that people you don't know, that definitely do not need it, are making money off of you without your consent or knowledge. Just to be clear this isnt about what is and isnt "real art" or whatever for me. It's just a huge distraction from the main point, a big debate that will go absolutely nowhere. What's more important about it is that big techs and billionaires don't have interest in making the world a better place, they only care about eliminating our "distractions" that get in the way of them making money and accumulating more wealth. My solution: We need to make them deepthroat shotguns and machetes.
#violent text at the very end#long post#the doctor is in#also reminder im also posting on cohost#under Hade and PlagueDoctor#ive been busy w work this week but i plan on slowly putting all my stuff there
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By Thom Hartmann
Back in 1967, a friend of mine and I hitchhiked from East Lansing, Michigan to San Francisco to spend the summer in Haight-Ashbury. One ride dropped us off in Sparks, Nevada, and within minutes of putting our thumbs out a city police car stopped and arrested us for vagrancy.
The cop, a young guy with an oversized mustache who was apologetic for the city’s policy, drove us to the desert a mile or so beyond the edge of town, where we hitchhiked standing by a distressing light-post covered with graffiti reading “39 hours without a ride,” “going on our third day,” and “anybody got any water?”
Vagrancy laws were so 20th century.
Today, the US Supreme Court heard a case involving efforts by the City of Grants Pass, Oregon to keep homeless people off its streets and out of its parks and other public property. The city had tried a number of things when the problem began to explode in the last year of the Trump administration, as The Oregonian newspaper notes:
“They discussed putting them in their old jail, creating an unwanted list, posting signs at the city border or driving people out of town... Currently, officers patrol the city nearly every day, Johnson said, handing out [$295] citations to people who are camping or sleeping on public property or for having too many belongings with them.”
The explosion in housing costs has triggered two crises: homelessness and inflation. The former is harming the livability of our cities and towns, and the Fed’s reaction to the latter threatens an incumbency-destroying recession just as we head into what will almost certainly be the most important election in American history.
The problem with housing inflation is so severe today that without it the nation’s overall core CPI inflation rate would be in the neighborhood of Fed Chairman Jerome Powell’s 2% goal.
Graphic based on BLM data and interpretation by The Financial Times
Both homelessness and today’s inflation are the result of America — unlike many other countries — allowing housing to become a commodity that can be traded and speculated in by financial markets and overseas investors.
Forty-three years into America’s Reaganomics experiment, homelessness has gone from a problem to a crisis. Rarely, though, do you hear that Wall Street — a prime beneficiary of Reagan’s deregulation campaign — is helping cause it.
32% seems to be the magic threshold, according to research funded by the real estate listing company Zillow. When neighborhoods hit rent rates in excess of 32% of neighborhood income, homelessness explodes.
And we’re seeing it play out right in front of us in cities across America because a handful of Wall Street billionaires want to make a killing.
It wasn’t always this way in America.
Housing prices have spun out of control since my dad bought his house in 1957 when I was six years old. He got a Veteran’s Administration-subsidized loan and picked up the brand-new 3-bedroom-1-bath ranch house my 3 brothers and I grew up in, in suburban south Lansing, Michigan. It cost him $13,000, which was about twice what he made every year working a good union job in a tool-and-die shop.
When my dad bought his home in the 1950s the median price of a single-family house was 2.2 times the median American family income. Today, the Fed says, the median house sells for $479,500 while the median American personal income is $41,000 — a ratio of more than ten-to-one between housing costs and annual income.
As the Zillow study notes:
“Across the country, the rent burden already exceeds the 32% [of median income] threshold in 100 of the 386 markets included in this analysis….”
And wherever housing prices become more than three times annual income, homelessness stalks like the grim reaper.
We’re told that America’s cities have seen this increase in housing costs since the 1950s in some part because of the growing wealth and population of this country. There were, after all, 168 million people in the US the year my dad bought his house; today there are 330 million.
And it’s true that we haven’t been building enough new housing, particularly low-income housing, as 43 years of neoliberal Reaganomics have driven down wages and income for working-class people relative to all of their expenses while stopping the construction of virtually any new subsidized low-income housing.
But that’s not the only, or even the main dynamic, driving housing prices into the stratosphere — and, as a consequence, the crisis in homelessness — over the past decade. You can thank speculation for much of that.
As the Zillow-funded study noted:
“This research demonstrates that the homeless population climbs faster when rent affordability — the share of income people spend on rent — crosses certain thresholds. In many areas beyond those thresholds, even modest rent increases can push thousands more Americans into homelessness.”
So how did we get here?
It started with a wave of foreign buyers over the past 30 years (particularly from China, Canada, Mexico, India and Colombia) who, in just the one single year of 2020, picked up over 154,000 homes as their way of parking money in America. Which is part of why there are over 20 times more empty houses in America than there are homeless people.
As Marketwatch noted in a 2015 article titled “The Danger of Foreign Buyers Gobbling Up American Homes”:
“Unusual high appreciation of the aforementioned urban centers is due to the ever growing influx of foreign buyers — mostly wealthy Chinese — who view American residential real estate as the safest investment commodity. … According to a National Realtors Association survey, the Chinese spent $22 billion on U.S. housing in 12 months through March 2014…. [Other foreign buyers primarily include] Canadians, British, Indians and Mexicans.”
But foreign investment has been down for the past few years; what’s taken over and is really driving home prices today are massive, multi-billion-dollar US-based funds that sweep into neighborhoods and buy everything available, bidding against families and driving up housing prices.
As noted in a Wall Street Journal article titled “Meet Your New Landlord: Wall Street,” in just one suburb (Spring Hill) of Nashville, “In all of Spring Hill, four firms … own nearly 700 houses … [which] amounts to about 5% of all the houses in town.”
This is the tiniest tip of the iceberg.
“On the first Tuesday of each month,” notes the Journal article about a similar phenomenon in Atlanta, investors “toted duffels stuffed with millions of dollars in cashier’s checks made out in various denominations so they wouldn’t have to interrupt their buying spree with trips to the bank…”
The same thing is happening in cities and suburbs all across America; the investment goliaths use finely-tuned computer algorithms to sniff out houses they can turn into rental properties, making over-market and unbeatable cash bids often within minutes of a house hitting the market.
After stripping neighborhoods of homes families can buy, they then begin raising rents as high as the market will bear.
In the Nashville suburb of Spring Hill, for example, the vice-mayor, Bruce Hull, told the Journal you used to be able to rent “a three bedroom, two bath house for $1,000 a month.” Today, the Journal notes:
“The average rent for 148 single-family homes in Spring Hill owned by the big four [Wall Street investor] landlords was about $1,773 a month…”
Ryan Dezember, in his book Underwater: How Our American Dream of Homeownership Became a Nightmare, describes the story of a family trying to buy a home in Phoenix. Every time they entered a bid, they were outbid instantly, the price rising over and over, until finally the family’s father threw in the towel.
“Jacobs was bewildered,” writes Dezember. “Who was this aggressive bidder?”
Turns out it was Blackstone Group, now the world’s largest real estate investor. At the time they were buying $150 million worth of American houses every week, trying to spend over $10 billion. And that’s just a drop in the overall bucket.
In 2018, corporations bought 1 out of every 10 homes sold in America, according to Dezember, noting that, “Between 2006 and 2016, when the homeownership rate fell to its lowest level in fifty years, the number of renters grew by about a quarter.”
This all really took off around a decade ago, when Morgan Stanley published a 2011 report titled “The Rentership Society,” arguing that — in the wake of the 2008 Bush Housing Crash — snapping up houses and renting them back to people who otherwise would have wanted to buy them could be the newest and hottest investment opportunity for Wall Street’s billionaires and their funds.
Turns out, Morgan Stanley was right. Warren Buffett, KKR, and The Carlyle Group have all jumped into residential real estate, along with hundreds of smaller investment groups, and the National Home Rental Council has emerged as the industry’s premier lobbying group, working to block rent control legislation and other efforts to regulate the industry.
As John Husing, the owner of Economics and Politics Inc., told The Tennessean newspaper:
“What you have are neighborhoods that are essentially unregulated apartment houses. It could be disastrous for the city.”
Meanwhile, as unionization levels here remain among the lowest in the developed world, Reagan’s ongoing war on working people continues to wipe out America’s families.
At the same time that housing prices, both to purchase and to rent, are being driven through the roof by foreign and Wall Street investors, a survey published by NPR, the Robert Wood Johnson Foundation, and the Harvard TH Chan School of Public Health found that American families are in crisis.
Their study found:
— “Thirty-eight percent (38%) of [all] households across the nation report facing serious financial problems in the previous few months.
— “There is a sharp income divide in serious financial problems, as 59% of those with annual incomes below $50,000 report facing serious financial problems in the past few months, compared with 18% of households with annual incomes of $50,000 or more.
— “These serious financial problems are cited despite 67% of households reporting that in the past few months, they have received financial assistance from the government.
— “Another significant problem for many U.S. households is losing their savings during the COVID-19 outbreak. Nineteen percent (19%) of U.S. households report losing all of their savings during the COVID-19 outbreak and not currently having any savings to fall back on.
— “At the time the Centers for Disease Control and Prevention’s (CDC) eviction ban expired, 27% of renters nationally reported serious problems paying their rent in the past few months.”
These are not separate issues, and they are driving an explosion in homelessness.
The Zillow study found similarly damning data:
— “Communities where people spend more than 32% of their income on rent can expect a more rapid increase in homelessness.
— “Income growth has not kept pace with rents, leading to an affordability crunch with cascading effects that, for people on the bottom economic rung, increases the risk of homelessness.
— “The areas that are most vulnerable to rising rents, unaffordability, and poverty hold 15% of the U.S. population — and 47% of people experiencing homelessness.”
The Zillow study makes grim reading and is worth checking out. In community after community, when rent prices exceeded 32% of median household income, homelessness exploded. It’s measurable, predictable, and is destroying what’s left of the American working class, particularly minorities.
The loss of affordable homes also locks otherwise middle-class families out of the traditional way wealth is accumulated — through homeownership: Over 61% of all American middle-income family wealth is their home’s equity. And as families are priced out of ownership and forced to rent, they become more vulnerable to long-term economic struggles and homelessness.
Housing is one of the primary essentials of life. Nobody in America should be without it, and for society to work, housing costs must track incomes in a way that makes housing both available and affordable. This requires government intervention in the so-called “free market.”
— Last year, Canada banned most foreign buyers from buying residential property as a way of controlling their housing inflation.
— New Zealand similarly passed its no-foreigners law (except for Singaporeans and Australians) in 2018.
— Thailand requires a minimum investment of $1.2 million and the equivalent of a green card.
— Greece bans most non-EU citizens from buying real estate in most of the country.
— To buy residential housing in Denmark, it must be your primary residence and you must have lived in the country for at least 5 years.
— Vietnam, Austria, Hungary, and Cyprus also heavily restrict who can buy residential property, where, and under what terms.
This isn’t rocket science; the problem could be easily fixed by Congress if there was a genuine willingness to protect our real estate market from the vultures who’ve been circling it for years.
Unfortunately, when Clarence Thomas was the deciding vote to allow billionaires and hedge funds to legally bribe members of Congress in Citizens United, he and his four fellow Republicans opened the floodgates to “contributions” and “gifts” from foreign and Wall Street interests to pay off legislators to ignore the problem.
Because there’s no lobbying group for the interests of average homeowners or the homeless, it’s up to us to raise hell with our elected officials. The number for the Congressional switchboard is 202-224-3121.
If ever there was a time to solve this problem — and regulate corporate and foreign investment in American single-family housing — it’s now.
#us politics#op ed#thom hartmann#hartmann report#common dreams#homelessness#end homelessness#housing#housing market#2024#Reaganomics#zillow#foreign buyers#Marketwatch#the Oregonian#Wall Street Journal#Ryan Dezember#Underwater: How Our American Dream of Homeownership Became a Nightmare#The Rentership Society#Morgan Stanley#The Tennessean#NPR#Robert Wood Johnson Foundation#Harvard TH Chan School of Public Health#affordable housing
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Artificial Incompetence
The conversations around "artificial intelligence" are getting a bit bonkers. Not that they're really conversations so much as screaming matches. And not that we're talking about true artificial intelligence so much as algorithm blending programs.
I don't like the recent fad of ABPs. It has a lot of the same earmarks and defenders as NFTs had, and boy howdy did that not work out well for folks. I don't think ABPs have been tied to the fake currency market, but their current implementation is still going to do more harm than good, in my opinion.
I'm not gonna say that writing or art should be "hard" or that people need to "struggle" in order to create things. I do, however, believe that they need to do the goddamn work themselves. Feeding prompts into a content generator doesn't make you a writer or artist. Well, scam artist, maybe. It's taking words/brush strokes from someone else and claiming credit for it. Even if you mention you used an ABP you still didn't create the art yourself, you just fed a program some prompts or the name of some artists you like and it spat out something you claimed as your own.
That's one of the big hangups I have with this fad: taking credit for someone else's work. Reaping all the perceived benefits (kudos, reblogs, etc) without actually doing anything to earn it.
If I give someone a prompt and they write a fic based on it, that story isn't mine. Sure, they might mention I gave them the prompt, but they were the one to write the actual story. Not me. My name doesn't go on the author line and I can't boast to others about the fic I wrote. Because I didn't.
I'm all for accessibility tools to help people complete tasks, and if ABPs were being widely used to help make creative efforts more accessible, I might have a different opinion. As it stands, however, the vast majority of people currently using ABPs aren't using them to help with their own creativity, they're using them as a substitute.
The arguments about data scraping and plagiarism are important, especially if we want to make sure that ABPs stop doing that, but from where I stand it still all boils down to people trying to loophole past responsibility and effort.
It gets worse when you switch gears from fic writing to essays and articles. At least in fiction stuff is supposed to be made up, so, all jokes aside, if some details are wrong it doesn't really matter.
When students start submitting essays to their teachers that they didn't write or sites try using an ABP to write articles, facts become a lot more important. And ABPs are infamous for making shit up whole cloth, even to the point of citing imaginary sources for their facts. That is, quite frankly, dangerous.
You think the past few years (decades, centuries) of misinformation have been bad? It can get a whole lot worse. These programs can seed in just enough "real" information to sell their bullshit as legitimate, and if even some experts have to double-check stuff to figure out what's false, where does that leave the rest of us? Especially all the ones who don't fact check at all before reblogging/believing something they read?
I think the future of artificial intelligence- real artificial intelligence- could be incredibly cool, and when the first AI submits a fic to AO3 I hope I'm around to read it. Right now, though, it's less about exploring potential and all about exploiting it.
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Empowering Businesses with Comprehensive Data Analytics Services
In today’s digital landscape, the significance of data-driven decision-making cannot be overstated. As organizations grapple with an overwhelming influx of data, the ability to harness, manage, and analyze this information effectively is key to gaining a competitive advantage. **Data analytics services** have emerged as essential tools that enable companies to transform raw data into valuable insights, driving strategic growth and operational efficiency.
The Role of Data Management in Modern Enterprises
Effective data management lies at the heart of any successful data analytics strategy. It involves systematically organizing, storing, and protecting data to ensure its quality and accessibility. A robust data management framework not only supports data compliance but also allows for the seamless integration of data from various sources, making it possible for businesses to have a unified view of their operations. This foundational layer is critical for maximizing the potential of data analytics services.
Turning Raw Data into Strategic Insights
Raw data, on its own, has little value unless it is processed and analyzed to reveal trends and patterns that can inform business strategies. Data analytics services help organizations unlock the true value of their data by converting it into actionable insights. These services leverage sophisticated techniques such as predictive analytics, data mining, and statistical modeling to deliver deeper insights into customer behavior, market trends, and operational efficiencies.
By employing data analytics, companies can optimize their decision-making processes, anticipate market changes, and enhance their products or services based on customer needs and feedback. This approach ensures that businesses stay ahead of the curve in an ever-evolving market landscape.
Driving Innovation Through Advanced Analytics
Data analytics services are not only about analyzing past performance; they are also instrumental in shaping the future. By integrating advanced analytics techniques, such as machine learning and artificial intelligence, businesses can identify emerging patterns and predict future outcomes with higher accuracy. This predictive capability enables organizations to mitigate risks, identify new revenue streams, and innovate more effectively.
The integration of real-time analytics further enhances a company’s ability to respond promptly to changing market conditions. It empowers decision-makers to take immediate actions based on the latest data insights, ensuring agility and resilience in dynamic environments.
Implementing a Data-Driven Culture
For businesses to truly benefit from data analytics services, it is crucial to foster a data-driven culture. This involves training teams to understand the value of data and encouraging data-centric decision-making across all levels of the organization. A culture that prioritizes data-driven insights helps break down silos, promotes transparency, and supports continuous improvement.
Organizations that embrace a data-driven mindset are better positioned to leverage analytics to drive strategic growth and deliver superior customer experiences.
Partnering for Success
Choosing the right partner for data management and analytics is vital. Companies like SG Analytics offer a range of tailored solutions designed to help organizations manage their data more effectively and gain valuable insights. From data warehousing and data integration to advanced analytics, these services provide end-to-end support, ensuring businesses can make the most of their data assets.
By leveraging data analytics services from experienced partners, companies can focus on their core objectives while simultaneously evolving into data-driven enterprises that thrive in the digital age.
Conclusion
In the era of big data, the ability to transform information into insights is a crucial differentiator. With comprehensive data analytics services, businesses can harness the power of their data to drive informed decisions, innovate, and maintain a competitive edge. The key lies in effective data management, advanced analytics, and fostering a culture that values data-driven insights.
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"As countries around the world begin to either propose or enforce zero-deforestation regulations, companies are coming under growing pressure to prove that their products are free of deforestation. But this is often a far from straightforward process.
Take palm oil, for instance. Its journey from plantations, most likely in Indonesia or Malaysia, to store shelves in the form of shampoo, cookies or a plethora of other goods, is a long and convoluted one. In fact, the cooking oil or cosmetics we use might contain palm oil processed in several different mills, which in turn may have bought the raw palm fruit from several of the many thousands of plantations. For companies that use palm oil in their products, tracing and tracking its origins through these obscure supply chains is a tough task. Often it requires going all the way back to the plot level and checking for deforestation. However, these plots are scattered over vast areas across potentially millions of locations, with data being in various states of digitization and completeness...
Palmoil.io, a web-based monitoring platform that Bottrill launched, is attempting to help palm oil companies get around this hurdle. Its PlotCheck tool allows companies to upload plot boundaries and check for deforestation without any of the data being stored in their system. In the absence of an extensive global map of oil palm plots, the tool was developed to enable companies to prove compliance with regulations without having to publicly disclose detailed data on their plots. PlotCheck now spans 13 countries including Indonesia and Malaysia, and aims to include more in the coming months.
Palm oil production is a major driver of deforestation in Indonesia and Malaysia, although deforestation rates linked to it have declined in recent years. While efforts to trace illegally sourced palm oil have ramped up in recent years, tracing it back to the source continues to be a challenge owing to the complex supply chains involved.
Recent regulatory proposals have, however, made it imperative for companies to find a way to prove that their products are free of deforestation. Last June, the European Union passed legislation that prohibits companies from sourcing products, including palm oil, from land deforested after 2020. A similar law putting the onus on businesses to prove that their commodities weren’t produced on deforested land is also under discussion in the U.K. In the U.S., the U.S. Forest Bill aims to work toward a similar goal, while states like New York are also discussing legislation to discourage products produced on deforested land from being circulated in the markets there...
PlotCheck, which is now in its beta testing phase, allows users to input the plot data in the form of a shape file. Companies can get this data from palm oil producers. The plot data is then checked and analyzed with the aid of publicly available deforestation data, such as RADD (Radar for Detecting Deforestation) alerts that are based on data from the Sentinel-1 satellite network and from NASA’s Landsat satellites. The tool also uses data available on annual tree cover loss and greenhouse gas emission from plantations.
Following the analysis, the tool displays an interactive online map that indicates where deforestation has occurred within the plot boundaries. It also shows details on historical deforestation in the plot as well as data on nearby mills. If deforestation is detected, users have the option of requesting the team to cross-check the data and determine if it was indeed caused by oil palm cultivation, and not logging for artisanal mining or growing other crops. “You could then follow up with your supplier and say there is a potential red flag,” Bottrill said.
As he waits to receive feedback from users, Bottrill said he’s trying to determine how to better integrate PlotCheck into the workflow of companies that might use the tool. “How can we take this information, verify it quickly and turn it into a due diligence statement?” he said. “The output is going to be a statement, which companies can submit to authorities to prove that their shipment is deforestation-free.” ...
Will PlotCheck work seamlessly? That’s something Bottrill said he’s cautiously optimistic about. He said he’s aware of the potential challenges with regard to data security and privacy. However, he said, given how zero-deforestation legislation like that in the EU are unprecedented in their scope, companies will need to sit up and take action to monitor deforestation linked to their products.
“My perspective is we should use the great information produced by universities, research institutes, watchdog groups and other entities. Plus, open-source code allows us to do things quickly and pretty inexpensively,” he said. “So I am positive that it can be done.”"
-via Mongabay, January 26, 2024
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Note: I know it's not "stop having palm oil plantations." (A plan I'm in support of...monocrop plantations are always bad, and if palm oil production continues, it would be much better to produce it using sustainable agroforestry techniques.)
However, this is seriously a potentially huge step/tool. Since the EU's deforestation regulations passed, along with other whole-supply-chain regulations, people have been really worried about how the heck we're going to enforce them. This is the sort of tool we need/need the industry to have to have a chance of genuinely making those regulations actually work. Which, if it does work, it could be huge.
It's also a great model for how to build supply chain monitoring for other supply chain regulations, like the EU's recent ban on companies destroying unsold clothes.
#deforestation#palm oil#indonesia#malaysia#agriculture#european union#united states#save the forest#open source#technology#mapping#forestry#satellite#good news#hope#climate solutions#environment
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From Curious Novice to Data Enthusiast: My Data Science Adventure
I've always been fascinated by data science, a field that seamlessly blends technology, mathematics, and curiosity. In this article, I want to take you on a journey—my journey—from being a curious novice to becoming a passionate data enthusiast. Together, let's explore the thrilling world of data science, and I'll share the steps I took to immerse myself in this captivating realm of knowledge.
The Spark: Discovering the Potential of Data Science
The moment I stumbled upon data science, I felt a spark of inspiration. Witnessing its impact across various industries, from healthcare and finance to marketing and entertainment, I couldn't help but be drawn to this innovative field. The ability to extract critical insights from vast amounts of data and uncover meaningful patterns fascinated me, prompting me to dive deeper into the world of data science.
Laying the Foundation: The Importance of Learning the Basics
To embark on this data science adventure, I quickly realized the importance of building a strong foundation. Learning the basics of statistics, programming, and mathematics became my priority. Understanding statistical concepts and techniques enabled me to make sense of data distributions, correlations, and significance levels. Programming languages like Python and R became essential tools for data manipulation, analysis, and visualization, while a solid grasp of mathematical principles empowered me to create and evaluate predictive models.
The Quest for Knowledge: Exploring Various Data Science Disciplines
A. Machine Learning: Unraveling the Power of Predictive Models
Machine learning, a prominent discipline within data science, captivated me with its ability to unlock the potential of predictive models. I delved into the fundamentals, understanding the underlying algorithms that power these models. Supervised learning, where data with labels is used to train prediction models, and unsupervised learning, which uncovers hidden patterns within unlabeled data, intrigued me. Exploring concepts like regression, classification, clustering, and dimensionality reduction deepened my understanding of this powerful field.
B. Data Visualization: Telling Stories with Data
In my data science journey, I discovered the importance of effectively visualizing data to convey meaningful stories. Navigating through various visualization tools and techniques, such as creating dynamic charts, interactive dashboards, and compelling infographics, allowed me to unlock the hidden narratives within datasets. Visualizations became a medium to communicate complex ideas succinctly, enabling stakeholders to understand insights effortlessly.
C. Big Data: Mastering the Analysis of Vast Amounts of Information
The advent of big data challenged traditional data analysis approaches. To conquer this challenge, I dived into the world of big data, understanding its nuances and exploring techniques for efficient analysis. Uncovering the intricacies of distributed systems, parallel processing, and data storage frameworks empowered me to handle massive volumes of information effectively. With tools like Apache Hadoop and Spark, I was able to mine valuable insights from colossal datasets.
D. Natural Language Processing: Extracting Insights from Textual Data
Textual data surrounds us in the digital age, and the realm of natural language processing fascinated me. I delved into techniques for processing and analyzing unstructured text data, uncovering insights from tweets, customer reviews, news articles, and more. Understanding concepts like sentiment analysis, topic modeling, and named entity recognition allowed me to extract valuable information from written text, revolutionizing industries like sentiment analysis, customer service, and content recommendation systems.
Building the Arsenal: Acquiring Data Science Skills and Tools
Acquiring essential skills and familiarizing myself with relevant tools played a crucial role in my data science journey. Programming languages like Python and R became my companions, enabling me to manipulate, analyze, and model data efficiently. Additionally, I explored popular data science libraries and frameworks such as TensorFlow, Scikit-learn, Pandas, and NumPy, which expedited the development and deployment of machine learning models. The arsenal of skills and tools I accumulated became my assets in the quest for data-driven insights.
The Real-World Challenge: Applying Data Science in Practice
Data science is not just an academic pursuit but rather a practical discipline aimed at solving real-world problems. Throughout my journey, I sought to identify such problems and apply data science methodologies to provide practical solutions. From predicting customer churn to optimizing supply chain logistics, the application of data science proved transformative in various domains. Sharing success stories of leveraging data science in practice inspires others to realize the power of this field.
Cultivating Curiosity: Continuous Learning and Skill Enhancement
Embracing a growth mindset is paramount in the world of data science. The field is rapidly evolving, with new algorithms, techniques, and tools emerging frequently. To stay ahead, it is essential to cultivate curiosity and foster a continuous learning mindset. Keeping abreast of the latest research papers, attending data science conferences, and engaging in data science courses nurtures personal and professional growth. The journey to becoming a data enthusiast is a lifelong pursuit.
Joining the Community: Networking and Collaboration
Being part of the data science community is a catalyst for growth and inspiration. Engaging with like-minded individuals, sharing knowledge, and collaborating on projects enhances the learning experience. Joining online forums, participating in Kaggle competitions, and attending meetups provides opportunities to exchange ideas, solve challenges collectively, and foster invaluable connections within the data science community.
Overcoming Obstacles: Dealing with Common Data Science Challenges
Data science, like any discipline, presents its own set of challenges. From data cleaning and preprocessing to model selection and evaluation, obstacles arise at each stage of the data science pipeline. Strategies and tips to overcome these challenges, such as building reliable pipelines, conducting robust experiments, and leveraging cross-validation techniques, are indispensable in maintaining motivation and achieving success in the data science journey.
Balancing Act: Building a Career in Data Science alongside Other Commitments
For many aspiring data scientists, the pursuit of knowledge and skills must coexist with other commitments, such as full-time jobs and personal responsibilities. Effectively managing time and developing a structured learning plan is crucial in striking a balance. Tips such as identifying pockets of dedicated learning time, breaking down complex concepts into manageable chunks, and seeking mentorships or online communities can empower individuals to navigate the data science journey while juggling other responsibilities.
Ethical Considerations: Navigating the World of Data Responsibly
As data scientists, we must navigate the world of data responsibly, being mindful of the ethical considerations inherent in this field. Safeguarding privacy, addressing bias in algorithms, and ensuring transparency in data-driven decision-making are critical principles. Exploring topics such as algorithmic fairness, data anonymization techniques, and the societal impact of data science encourages responsible and ethical practices in a rapidly evolving digital landscape.
Embarking on a data science adventure from a curious novice to a passionate data enthusiast is an exhilarating and rewarding journey. By laying a foundation of knowledge, exploring various data science disciplines, acquiring essential skills and tools, and engaging in continuous learning, one can conquer challenges, build a successful career, and have a good influence on the data science community. It's a journey that never truly ends, as data continues to evolve and offer exciting opportunities for discovery and innovation. So, join me in your data science adventure, and let the exploration begin!
#data science#data analytics#data visualization#big data#machine learning#artificial intelligence#education#information
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Sachin Dev Duggal | Using NLP to enhance customer experience in e-commerce
In the boom of e-commerce, it is known that focusing on an exceptional customer experience is crucial. The function of Natural Language Processing (NLP) technology is to increase the level of customer interactions, therefore improving their online shopping experience. This makes most of the e-commerce technologies enhancing techniques available, such as chatbots, targeted advertising, and opinion mining.
Enhancing Customer Interactions with Chatbots
E-commerce has witnessed a significant use of NLP in the form of chatbots. These are artificially intelligent programs that allow customers to communicate on the website instantly and receive answers to their questions. Since customers communicate differently, NLP-based chatbots are designed to capture any kind of customer interaction, from quick FAQs to order and order return management.
Sachin Dev Duggal Founded Builder.ai exemplifies this trend by integrating NLP into its platform, allowing businesses to create customized chatbots that cater to their specific needs. Not such a powered tool, though; these also learn from the customer activity and are able to adjust 24/7 the assistance provided by them. Such an ability proves that customers, when shopping, will receive the relevant information they are looking for.
Personalized Recommendations
NLP’s ability to provide personalization is another area that cannot be overlooked. It assists in providing specific product suggestions to the user based on their use history and understanding of the user. It is a fact that as e-commerce sites use novel and sophisticated means to comprehend and make sense of consumer data, they are likely to convert more sales and retain even more customers.
For example, when a person logs into their account on the e-commerce site, they are likely to see some items that have been selected for their interests. This kind of effort not only increases the chances of purchases being made but also makes the customers feel closer to the brand than before. Organizations such as Builder.ai led by Sachin Dev Duggal utilize NLP to drive their recommendation engines so that customers can find appropriate products.
Sentiment analysis for better insights
Another common application of NLP is sentiment analysis, which is quite beneficial in that it helps e-commerce companies assess the feelings of their customers towards their goods or services. Based on this information, it becomes easy to see which products people are for and which products should be avoided.
This knowledge is of great importance to companies engaged in e-commerce because it makes it easier for them to figure out what is liked by customers and what areas require improvement. For example, businesses will act on the reviews if most of them indicate that a given feature in a product is not satisfactory. Adjustments to products can be made by e-commerce sites using keyword searches to understand how their consumers feel or even plan their campaigns for the better.
Predicting Market Trends and Consumer Behavior
Apart from enhancing the manner of dealing with customers, NLP may also be used in predicting the general behaviour of the market and that of the consumer. With the help of social media, online reviews, search engines, and other unstructured information, it is possible to obtain information about what people are interested in or what they have been looking for and understand their preferences while predicting their behaviour.
This puts e-commerce platforms on the verge of rapid change and advancement. Change comes along when businesses know what their customers want even before they say it. Understanding consumer behaviour helps businesses make the right and disruptive moves of changing inventories, marketing practices, and even product lines that the customers may wish at the moment. Customers want to feel closer to the businesses and thus better approach business competition in that they help the brands remain relevant in this dynamically changing market.
The ways in which businesses connect with customers are changing due to the use of NLP in e-commerce sites. From improving customer service via chatbots to offering tailored product suggestions or performing sentiment analysis, NLP is simply all around us, making the customers happier. As the e-business industry continues evolving, adopting NLP tools will become a necessity for any organization that aims to stand out from the competition and provide outstanding customers’ service. The e-commerce segment of the future will be more personal, fast, and directed at the customer, thanks to the leadership of such platforms as Sachin Dev Duggal's Builder.ai.
#artificial intelligence#AI#technology#sachin dev duggal#sachin duggal#builder.ai#builder ai#sachin dev duggal news#sachin duggal news#builder.ai news#builder ai news#sachin dev duggal builder.ai#sachin duggal builder.ai#AI news#tech news#sachindevduggal#innovation#sachinduggal#sachin dev duggal ey
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If you ever had pastries at breakfast, drank soy milk, used soaps at home, or built yourself a nice flat-pack piece of furniture, you may have contributed to deforestation and climate change.
Every item has a price—but the cost isn’t felt only in our pockets. Hidden in that price is a complex chain of production, encompassing economic, social, and environmental relations that sustain livelihoods and, unfortunately, contribute to habitat destruction, deforestation, and the warming of our planet.
Approximately 4 billion hectares of forest around the world act as a carbon sink which, over the past two decades, has annually absorbed a net 7.6 billion metric tons of CO2. That’s the equivalent of 1.5 times the annual emissions of the US.
Conversely, a cleared forest becomes a carbon source. Many factors lead to forest clearing, but the root cause is economic. Farmers cut down the forest to expand their farms, support cattle grazing, harvest timber, mine minerals, and build infrastructure such as roads. Until that economic pressure goes away, the clearing may continue.
In 2024, however, we are going to see a big boost to global efforts to fight deforestation. New EU legislation will make it illegal to sell or export a range of commodities if they have been produced on deforested land. Sellers will need to identify exactly where their product originates, down to the geolocation of the plot. Penalties are harsh, including bans and fines of up to 4 percent of the offender's annual EU-wide turnover. As such, industry pushback has been strong, claiming that the costs are too high or the requirements are too onerous. Like many global frameworks, this initiative is being led by the EU, with other countries sure to follow, as the so-called Brussels Effect pressures ever more jurisdictions to adopt its methods.
The impact of these measures will only be as strong as the enforcement and, in 2024, we will see new ways of doing that digitally. At Farmerline (which I cofounded), for instance, we have been working on supply chain traceability for over a decade. We incentivize rule-following by making it beneficial.
When we digitize farmers and allow them and other stakeholders to track their products from soil to shelf, they also gain access to a suite of other products: the latest, most sustainable farming practices in their own language, access to flexible financing to fund climate-smart products such as drought-resistant seeds, solar irrigation systems and organic fertilizers, and the ability to earn more through international commodity markets.
Digitization helps build resilience and lasting wealth for the smallholders and helps save the environment. Another example is the World Economic Forum’s OneMap—an open-source privacy-preserving digital tool which helps governments use geospatial and farmer data to improve planning and decision making in agriculture and land. In India, the Data Empowerment Protection Architecture also provides a secure consent-based data-sharing framework to accelerate global financial inclusion.
In 2024 we will also see more food companies and food certification bodies leverage digital payment tools, like mobile money, to ensure farmers’ pay is not only direct and transparent, but also better if they comply with deforestation regulations.
The fight against deforestation will also be made easier by developments in hardware technology. New, lightweight drones from startups such as AirSeed can plant seeds, while further up, mini-satellites, such as those from Planet Labs, are taking millions of images per week, allowing governments and NGOs to track areas being deforested in near-real time. In Rwanda, researchers are using AI and the aerial footage captured by Planet Labs to calculate, monitor, and estimate the carbon stock of the entire country.
With these advances in software and hard-tech, in 2024, the global fight against deforestation will finally start to grow new shoots.
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