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ChatGPT AI Emits Metric Tons of Carbon, Stanford Report Says - 0 views

gizmodo.com/ons-stanford-report-1850288635 carbon ai training report emissions
shared by Javier E on 08 Apr 23 - No Cached
  • A new report released today by the Stanford Institute for Human-Centered Artificial Intelligence estimates the amount of energy needed to train AI models like OpenAI’s GPT-3, which powers the world-famous ChatGPT, could power an average American’s home for hundreds of years. Of the three AI models reviewed in the research, OpenAI’s system was by far the most energy-hungry.
  • “If we’re just scaling without any regard to the environmental impacts, we can get ourselves into a situation where we are doing more harm than good with machine learning models,” Stanford researcher ​​Peter Henderson said last year. “We really want to mitigate that as much as possible and bring net social good.”
  • OpenAI’s model reportedly released 502 metric tons of carbon during its training. To put that in perspective, that’s 1.4 times more carbon than Gopher and a whopping 20.1 times more than BLOOM. GPT-3 also required the most power consumption of the lot at 1,287 MWh.
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  • If all of this sounds familiar, it’s because we basically saw this same environmental dynamic play out several years ago with tech’s last big obsession: Crypto and web3. In that case, Bitcoin emerged as the industry’s obvious environmental sore spot due to the vast amounts of energy needed to mine coins in its proof of work model. Some estimates suggest Bitocin alone requires more energy every year than Norway’s annual electricity consumption.
  • rs of criticism from environmental activists however led the crypto industry to make some changes. Ethereum, the second largest currency on the blockchain, officially switched last year to a proof of stake model which supporters claim could reduce its power usage by over 99%. Other smaller coins similarly were designed with energy efficiency in mind. In the grand scheme of things, large language models are still in their infancy and it’s far from certain how its environmental report card will play out.
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Pause or panic: battle to tame the AI monster - 0 views

www.thetimes.co.uk/...-tame-the-ai-monster-mjd97lhkh AI control threat report crisis
shared by Javier E on 21 Apr 23 - No Cached
  • What exactly are they afraid of? How do you draw a line from a chatbot to global destruction
  • This tribe feels we have made three crucial errors: giving the AI the capability to write code, connecting it to the internet and teaching it about human psychology. In those steps we have created a self-improving, potentially manipulative entity that can use the network to achieve its ends — which may not align with ours
  • This is a technology that learns from our every interaction with it. In an eerie glimpse of AI’s single-mindedness, OpenAI revealed in a paper that GPT-4 was willing to lie, telling a human online it was a blind person, to get a task done.
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  • For researchers concerned with more immediate AI risks, such as bias, disinformation and job displacement, the voices of doom are a distraction. Professor Brent Mittelstadt, director of research at the Oxford Internet Institute, said the warnings of “the existential risks community” are overblown. “The problem is you can’t disprove the future scenarios . . . in the same way you can’t disprove science fiction.” Emily Bender, a professor of linguistics at the University of Washington, believes the doomsters are propagating “unhinged AI hype, helping those building this stuff sell it”.
  • Those urging us to stop, pause and think again have a useful card up our sleeves: the people building these models do not fully understand them. AI like ChatGPT is made up of huge neural networks that can defy their creators by coming up with “emergent properties”.
  • Google’s PaLM model started translating Bengali despite not being trained to do so
  • Let’s not forget the excitement, because that is also part of Moloch, driving us forward. The lure of AI’s promises for humanity has been hinted at by DeepMind’s AlphaFold breakthrough, which predicted the 3D structures of nearly all the proteins known to humanity.
  • Noam Shazeer, a former Google engineer credited with setting large language models such as ChatGPT on their present path, was asked by The Sunday Times how the models worked. He replied: “I don’t think anybody really understands how they work, just like nobody really understands how the brain works. It’s pretty much alchemy.”
  • The industry is turning itself to understanding what has been created, but some predict it will take years, decades even.
  • Alex Heath, deputy editor of The Verge, who recently attended an AI conference in San Francisco. “It’s clear the people working on generative AI are uneasy about the worst-case scenario of it destroying us all. These fears are much more pronounced in private than they are in public.” One figure building an AI product “said over lunch with a straight face that he is savoring the time before he is killed by AI”.
  • Greg Brockman, co-founder of OpenAI, told the TED2023 conference this week: “We hear from people who are excited, we hear from people who are concerned. We hear from people who feel both those emotions at once. And, honestly, that’s how we feel.”
  • A CBS interviewer challenged Sundar Pichai, Google’s chief executive, this week: “You don’t fully understand how it works, and yet you’ve turned it loose on society?
  • In 2020 there wasn’t a single drug in clinical trials developed using an AI-first approach. Today there are 18
  • Consider this from Bill Gates last month: “I think in the next five to ten years, AI-driven software will finally deliver on the promise of revolutionising the way people teach and learn.”
  • If the industry is aware of the risks, is it doing enough to mitigate them? Microsoft recently cut its ethics team, and researchers building AI outnumber those focused on safety by 30-to-1,
  • The concentration of AI power, which worries so many, also presents an opportunity to more easily develop some global rules. But there is little agreement on direction. Europe is proposing a centrally defined, top-down approach. Britain wants an innovation-friendly environment where rules are defined by each industry regulator. The US commerce department is consulting on whether risky AI models should be certified. China is proposing strict controls on generative AI that could upend social order.
  • Part of the drive to act now is to ensure we learn the lessons of social media. Twenty years after creating it, we are trying to put it back in a legal straitjacket after learning that its algorithms understand us only too well. “Social media was the first contact between AI and humanity, and humanity lost,” Yuval Harari, the Sapiens author,
  • Others point to bioethics, especially international agreements on human cloning. Tegmark said last week: “You could make so much money on human cloning. Why aren’t we doing it? Because biologists thought hard about this and felt this is way too risky. They got together in the Seventies and decided, let’s not do this because it’s too unpredictable. We could lose control over what happens to our species. So they paused.” Even China signed up.
  • One voice urging calm is Yann LeCun, Meta’s chief AI scientist. He has labelled ChatGPT a “flashy demo” and “not a particularly interesting scientific advance”. He tweeted: “A GPT-4-powered robot couldn’t clear up the dinner table and fill up the dishwasher, which any ten-year-old can do. And it couldn’t drive a car, which any 18-year-old can learn to do in 20 hours of practice. We’re still missing something big for human-level AI.” If this is sour grapes and he’s wrong, Moloch already has us in its thrall.
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He Turned 55. Then He Started the World's Most Important Company. - WSJ - 0 views

www.wsj.com/...hips-entrepreneurship-506fcbc4 entrepreneur chip company Taiwan
shared by Javier E on 10 Apr 24 - No Cached
  • You probably use a device with a chip made by TSMC every day, but TSMC does not actually design or market those chips. That would have sounded completely absurd before the existence of TSMC. Back then, companies designed chips that they manufactured themselves. Chang’s radical idea for a great semiconductor company was one that would exclusively manufacture chips that its customers designed. By not designing or selling its own chips, TSMC never competed with its own clients. In exchange, they wouldn’t have to bother running their own fabrication plants, or fabs, the expensive and dizzyingly sophisticated facilities where circuits are carved on silicon wafers.
  • The innovative business model behind his chip foundry would transform the industry and make TSMC indispensable to the global economy. Now it’s the company that Americans rely on the most but know the least about
  • I wanted to know more about his decision to start a new company when he could have stopped working altogether. What I discovered was that his age was one of his assets. Only someone with his experience and expertise could have possibly executed his plan for TSMC. 
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  • “I could not have done it sooner,” he says. “I don’t think anybody could have done it sooner. Because I was the first one.” 
  • By the late 1960s, he was managing TI’s integrated-circuit division. Before long, he was running the entire semiconductor group. 
  • He transferred to the Massachusetts Institute of Technology, where he studied mechanical engineering, earned his master’s degree and would have stayed for his Ph.D. if he hadn’t failed the qualifying exam. Instead, he got his first job in semiconductors and moved to Texas Instruments in 1958
  • he came along as the integrated circuit was being invented, and his timing couldn’t have been any better, as Chang belonged to the first generation of semiconductor geeks. He developed a reputation as a tenacious manager who could wring every possible improvement out of production lines, which put his career on the fast track.
  • Chang grew up dreaming of being a writer—a novelist, maybe a journalist—and he planned to major in English literature at Harvard University. But after his freshman year, he decided that what he actually wanted was a good job
  • “They talk about life-work balance,” he says. “That’s a term I didn’t even know when I was their age. Work-life balance. When I was their age, if there was no work, there was no life.” 
  • These days, TSMC is investing $40 billion to build plants in Arizona, but the project has been stymied by delays, setbacks and labor shortages, and Chang told me that some of TSMC’s young employees in the U.S. have attitudes toward work that he struggles to understand. 
  • Chang says he wouldn’t have taken the risk of moving to Taiwan if he weren’t financially secure. In fact, he didn’t take that same risk the first time he could have.
  • “The closer the industry match,” they wrote, “the greater the success rate.” 
  • By then, Chang knew that he wasn’t long for Texas Instruments. But his stock options hadn’t vested, so he turned down the invitation to Taiwan. “I was not financially secure yet,” he says. “I was never after great wealth. I was only after financial security.” For this corporate executive in the middle of the 1980s, financial security equated to $200,000 a year. “After tax, of course,” he says. 
  • Chang’s situation had changed by the time Li called again three years later. He’d exercised a few million dollars of stock options and bought tax-exempt municipal bonds that paid enough for him to be financially secure by his living standards. Once he’d achieved that goal, he was ready to pursue another one. 
  • “There was no certainty at all that Taiwan would give me the chance to build a great semiconductor company, but the possibility existed, and it was the only possibility for me,” Chang says. “That’s why I went to Taiwan.” 
  • Not long ago, a team of economists investigated whether older entrepreneurs are more successful than younger ones. By scrutinizing Census Bureau records and freshly available Internal Revenue Service data, they were able to identify 2.7 million founders in the U.S. who started companies between 2007 and 2014. Then they looked at their ages.
  • The average age of those entrepreneurs at the founding of their companies was 41.9. For the fastest-growing companies, that number was 45. The economists also determined that 50-year-old founders were almost twice as likely to achieve major success as 30-year-old founders, while the founders with the lowest chance of success were the ones in their early 20s
  • “Successful entrepreneurs are middle-aged, not young,” they wrote in their 2020 paper.  
  • Silicon Valley’s venture capitalists throw money at talented young entrepreneurs in the hopes they will start the next trillion-dollar company. They have plentiful energy, insatiable ambition and the vision to peek around corners and see the future. What they don’t typically have are mortgages, family obligations and other adult responsibilities to distract them or diminish their appetite for risk. Chang himself says that younger people are more innovative when it comes to science and technical subjects. 
  • But in business, older is better. Entrepreneurs in their 40s and 50s may not have the exuberance to believe they will change the world, but they have the experience to know how they actually can. Some need years of specialized training before they can start a company. In biotechnology, for example, founders are more likely to be college professors than college dropouts. Others require the lessons and connections they accumulate over the course of their careers. 
  • one more finding from their study of U.S. companies that helps explain the success of a chip maker in Taiwan. It was that prior employment in the area of their startups—both the general sector and specific industry—predicted “a vastly higher probability” of success.
  • Chang was such a workaholic that he made sales calls on his honeymoon and had no patience for those who didn’t share his drive
  • Morris Chang had 30 years of experience in his industry when he decided to uproot his life and move to another continent. He knew more about semiconductors than just about anyone on earth—and certainly more than anyone in Taiwan. As soon as he started his job at the Industrial Technology Research Institute, Chang was summoned to K.T. Li’s office and given a second job. “He felt I should start a semiconductor company in Taiwan,”
  • “I decided right away that this could not be the kind of great company that I wanted to build at either Texas Instruments or General Instrument,”
  • TI handled every part of chip production, but what worked in Texas would not translate to Taiwan. The only way that he could build a great company in his new home was to make a new sort of company altogether, one with a business model that would exploit the country’s strengths and mitigate its many weaknesses.
  • Chang determined that Taiwan had precisely one strength in the chip supply chain. The research firm that he was now running had been experimenting with semiconductors for the previous 10 years. When he studied that decade of data, Chang was pleasantly surprised by Taiwan’s yields, the percentage of working chips on silicon wafers. They were almost twice as high in Taiwan as they were in the U.S., he said. 
  • “People were ingrained in thinking the secret sauce of a successful semiconductor company was in the wafer fab,” Campbell told me. “The transition to the fabless semiconductor model was actually pretty obvious when you thought about it. But it was so against the prevailing wisdom that many people didn’t think about it.” 
  • Taiwan’s government took a 48% stake, with the rest of the funding coming from the Dutch electronics giant Philips and Taiwan’s private sector, but Chang was the driving force behind the company. The insight to build TSMC around such an unconventional business model was born from his experience, contacts and expertise. He understood his industry deeply enough to disrupt it. 
  • “TSMC was a business-model innovation,” Chang says. “For innovations of that kind, I think people of a more advanced age are perhaps even more capable than people of a younger age.”
  • the personal philosophy that he’d developed over the course of his long career. “To be a partner to our customers,” he says. That founding principle from 1987 is the bedrock of the foundry business to this day, as TSMC says the key to its success has always been enabling the success of its customers.  
  • TSMC manufactures chips in iPhones, iPads and Mac computers for Apple, which manufactures a quarter of TSMC’s net revenue. Nvidia is often called a chip maker, which is curious, because it doesn’t make chips. TSMC does. 
  • Churning out identical copies of a single chip for an iPhone requires one TSMC fab to produce more than a quintillion transistors—that is, one million trillions—every few months. In a year, the entire semiconductor industry produces “more transistors than the combined quantity of all goods produced by all other companies, in all other industries, in all human history,” Miller writes. 
  • I asked how he thought about success when he moved to Taiwan. “The highest degree of success in 1985, according to me, was to build a great company. A lower degree of success was at least to do something that I liked to do and I wanted to do,” he says. “I happened to achieve the highest degree of success that I had in mind.” 
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'Social Order Could Collapse' in AI Era, Two Top Japan Companies Say - WSJ - 0 views

www.wsj.com/...p-japan-companies-say-1a71cc1d AI Japan risks caution
shared by Javier E on 09 Apr 24 - No Cached
  • Japan’s largest telecommunications company and the country’s biggest newspaper called for speedy legislation to restrain generative artificial intelligence, saying democracy and social order could collapse if AI is left unchecked.
  • the manifesto points to rising concern among American allies about the AI programs U.S.-based companies have been at the forefront of developing.
  • The Japanese companies’ manifesto, while pointing to the potential benefits of generative AI in improving productivity, took a generally skeptical view of the technology
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  • Without giving specifics, it said AI tools have already begun to damage human dignity because the tools are sometimes designed to seize users’ attention without regard to morals or accuracy.
  • Unless AI is restrained, “in the worst-case scenario, democracy and social order could collapse, resulting in wars,” the manifesto said.
  • It said Japan should take measures immediately in response, including laws to protect elections and national security from abuse of generative AI.
  • The Biden administration is also stepping up oversight, invoking emergency federal powers last October to compel major AI companies to notify the government when developing systems that pose a serious risk to national security. The U.S., U.K. and Japan have each set up government-led AI safety institutes to help develop AI guidelines.
  • NTT and Yomiuri said their manifesto was motivated by concern over public discourse. The two companies are among Japan’s most influential in policy. The government still owns about one-third of NTT, formerly the state-controlled phone monopoly.
  • Yomiuri Shimbun, which has a morning circulation of about six million copies according to industry figures, is Japan’s most widely-read newspaper. Under the late Prime Minister Shinzo Abe and his successors, the newspaper’s conservative editorial line has been influential in pushing the ruling Liberal Democratic Party to expand military spending and deepen the nation’s alliance with the U.S.
  • The Yomiuri’s news pages and editorials frequently highlight concerns about artificial intelligence. An editorial in December, noting the rush of new AI products coming from U.S. tech companies, said “AI models could teach people how to make weapons or spread discriminatory ideas.” It cited risks from sophisticated fake videos purporting to show politicians speaking.
  • NTT is active in AI research, and its units offer generative AI products to business customers. In March, it started offering these customers a large-language model it calls “tsuzumi” which is akin to OpenAI’s ChatGPT but is designed to use less computing power and work better in Japanese-language contexts.
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Opinion | The Mystery of White Rural Rage - The New York Times - 0 views

www.nytimes.com/...white-rural-voters.html white rural voters economics economy US crisis culture
shared by Javier E on 27 Feb 24 - No Cached
  • Business types and some economists may talk glowingly about the virtues of “creative destruction,” but the process can be devastating, economically and socially, for those who find themselves on the destruction side of the equation. This is especially true when technological change undermines not just individual workers but also whole communities.
  • It’s a big part of what has happened to rural America.
  • This process and its effects are laid out in devastating, terrifying and baffling detail in “White Rural Rage: The Threat to American Democracy,” a new book by Tom Schaller and Paul Waldman
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  • “devastating” because the hardship of rural Americans is real, “terrifying” because the political backlash to this hardship poses a clear and present danger to our democracy, and “baffling” because at some level I still don’t get the politics.
  • Technology is the main driver of rural decline, Schaller and Waldman argue. Indeed, American farms produce more than five times as much as they did 75 years ago, but the agricultural work force declined by about two-thirds over the same period, thanks to machinery, improved seeds, fertilizers and pesticides
  • Coal production has been falling recently, but thanks partly to technologies like mountaintop removal, coal mining as a way of life largely disappeared long ago, with the number of miners falling 80 percent even as production roughly doubled.
  • The decline of small-town manufacturing is a more complicated story, and imports play a role, but it’s also mainly about technological change that favors metropolitan areas with large numbers of highly educated workers.
  • Technology, then, has made America as a whole richer, but it has reduced economic opportunities in rural areas. So why don’t rural workers go where the jobs are? Some have
  • But some cities have become unaffordable, in part because of restrictive zoning — one thing blue states get wrong — while many workers are also reluctant to leave their families and communities.
  • So shouldn’t we aid these communities? We do. Federal programs — Social Security, Medicare, Medicaid and more — are available to all Americans, but are disproportionately financed from taxes paid by affluent urban areas. As a result there are huge de facto transfers of money from rich, urban states like New Jersey to poor, relatively rural states like West Virginia.
  • While these transfers somewhat mitigate the hardship facing rural America, they don’t restore the sense of dignity that has been lost along with rural jobs.
  • And maybe that loss of dignity explains both white rural rage and why that rage is so misdirected — why it’s pretty clear that this November a majority of rural white Americans will again vote against Joe Biden, who as president has been trying to bring jobs to their communities, and for Donald Trump, a huckster from Queens who offers little other than validation for their resentment.
  • This feeling of a loss of dignity may be worsened because some rural Americans have long seen themselves as more industrious, more patriotic and maybe even morally superior to the denizens of big cities — an attitude still expressed in cultural artifacts like Jason Al
  • In the crudest sense, rural and small-town America is supposed to be filled with hard-working people who adhere to traditional values, not like those degenerate urbanites on welfare, but the economic and social reality doesn’t match this self-image.
  • Prime working-age men outside metropolitan areas are substantially less likely than their metropolitan counterparts to be employed — not because they’re lazy, but because the jobs just aren’t there.
  • Quite a few rural states also have high rates of homicide, suicide and births to single mothers — again, not because rural Americans are bad people, but because social disorder is, as the sociologist William Julius Wilson argued long ago about urban problems, what happens when work disappears.
  • Draw attention to some of these realities and you’ll be accused of being a snooty urban elitist
  • The result — which at some level I still find hard to understand — is that many white rural voters support politicians who tell them lies they want to hear. It helps explain why the MAGA narrative casts relatively safe cities like New York as crime-ridden hellscapes while rural America is the victim not of technology but of illegal immigrants, wokeness and the deep state.
  • while white rural rage is arguably the single greatest threat facing American democracy, I have no good ideas about how to fight it.
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Climate change just became solvable because of math - 0 views

the.ink/...case-for-climate-unilateralism climate change economic cost research
shared by Javier E on 04 Jun 24 - No Cached
  • For years, economists’ best estimates of the cost of climate inaction were giant but not quite big enough to stimulate immediate and adequate action. The cost of inaction was, in a sense, high enough to be terrifying but too low to be galvanizing
  • now a groundbreaking new study has raised the estimated cost of inaction by so much that it makes acting seem like a bargain, and even makes it makes sense for wealthy countries to act alone, regardless of what their peers are doing. It’s a rare academic paper that could change everything.
  • Until the new paper, the most commonly used economic models were predicting climate impacts on the world economy on the order of about $200 in losses per ton of carbon emitted, or around 2 percent of world GDP (the monetary value of everything people produce) per degree of warming
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  • But while those are huge numbers by any measure (world GDP is around $100 trillion), they aren’t big enough to motivate most leaders to justify mitigation, which will also cost a whole lot of money.
  • To put it in terms the authors use, the recently enacted Inflation Reduction Act will cost Americans roughly $80 per ton of carbon emissions avoided, and while each ton not pumped into the atmosphere would save the world $200 as a whole, it would only save Americans about $40 of that $200, making it feel to some altruistic but not self-evident in purely economic terms.
  • In their new paper, economists Adrien Bilal of Harvard and Diego Känzig of Northwestern take a fresh look at the data
  • They show that the social cost of carbon is likely far bigger — six times bigger — than previously estimated: losses of more than $1,000 per ton, or around 12 percent of world GDP per degree of warming.
  • — roughly equivalent to the economic drag on big economies if they were permanently at war.
  • Suddenly, that $80 Americans are spending on reducing one ton of carbon emissions is netting them $200 or so in U.S. economic activity.
  • Bilal and Känzig argue that it’s very much worth it for countries of means to spend the money now to avoid much greater costs down the line
  • the potential losses are so vast it makes sense for these countries to go ahead and act on their own to avoid climate change losses, even if other nations do nothing.
  • What’s different about your methodology and how did it lead you to the numbers you've come up with?
  • Adrien Bilal: So virtually all of the previous work that's been done on the subject has relied on comparisons of different countries that heat up or cool down at different points in time. The U.K. gets a little hotter in one year, and then Germany stays cool. And then you look at how GDP in the U.K. evolves following that change in temperature.
  • that generally gives you numbers in the vicinity of $150 per ton of carbon emitted and a 2 percent decline in GDP per degree Celsius in warming
  • we think that is quite different from what climate change is actually doing to the world. It's not only that the U.K. is going to heat up a little more than Germany, but the whole world is heating up because of climate change. And, in particular, oceans are also heating up. And when the whole planet warms, that has potentially really different implications for the climate system, increased frequency of extreme weather events that then have big local impacts. 
  • that's actually what geoscientists have been telling us for a long time, but it simply hadn't percolated into economics. And so we took that perspective very seriously and thought, "Well, what happens when we basically compare years where the world is very hot to years where the world is cooler?" And that gives you a much larger effect of climate change on the economy.
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