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Former OpenAI CTO Mira Murati Reveals Her New AI Startup

digitex — Tue, 18 Feb 2025 23:06:12 +0000

Welcome back to The Prompt,
Mira Murati, former chief technology officer of OpenAI, announced her new venture called Thinking Machine Labs, where she plans to build accessible AI systems.© 2023 Bloomberg Finance LP

Today, former OpenAI CTO Mira Murati announced her new venture: Thinking Machine Labs, a public benefit corporation that aims to build accessible and broadly capable artificial intelligence systems. After leaving AI juggernaut OpenAI last September, Murati has brought together a team of engineers and researchers who have worked at buzzy startups like Character AI, Mistral and unsurprisingly, OpenAI. Additionally, Thinking Machine Labs said it will publish its technical blog posts, code and papers and collaborate with the broader community, indicating it plans to open source its work.

Now let’s get into the headlines.

BIG PLAYS
The cluttered world of AI reasoning models just got its newest addition. On Monday Elon Musk’s AI company, xAI launched a new AI model called Grok-3 that can process and answer complex questions across domains like science and math. In a livestream on X, Musk said the company’s mission is to “understand the universe…to figure out what’s going on, where are the aliens and what’s the meaning of life.”

The billionaire claims the model is built using 10 times more compute than Grok 2, likely from its “gigafactory of compute” in Memphis, and that it has been trained on public data from sources including social media platform X and legal documents. xAI also rolled out an AI-powered search engine called DeepSearch. OpenAI cofounder and former Tesla executive Andrej Karpathy, who tested the model, says Grok-3’s capabilities are largely on par with OpenAI’s best models but gets some questions wrong. Others have noted the model is lacking in its coding abilities compared to others. Grok-3 has yet not been independently evaluated and is only available to paying users.

ETHICS + LAW
Condé Nast, Vox, The Atlantic and a group of publishers have sued $5.5 billion-valued AI company Cohere for copyright and trademark violations. (Forbes is part of the group suing Cohere.) The lawsuit alleges that the Canadian AI startup scraped 4,000 copyrighted articles from the internet and used them to train its family of large language models called Command, which reproduced sections or entire works (at times word for word), allowing users to get information without visiting the publishers’ websites. It’s not the first time an AI company has faced publishers’ scrutiny. Last year, AI search engine Perplexity came under fire for republishing copyright works from multiple publications including Forbes. (In response, Forbes sent a cease and desist letter to Perplexity, accusing it of copyright infringement.)
AI DEALS OF THE WEEK
Humanoid robotics company Figure AI is in talks to raise $1.5 billion in venture capital at an eye-popping $39.5 billion valuation, Bloomberg reported. The news comes as the company is reportedly in talks with Meta to make robots for household chores.
AI legal company Luminance, which helps customers like AMD and National Grid generate, negotiate and analyze contracts, has raised $75 million in series C funding.
Chip startup Encharge AI has raised $100 million in a series B funding led by Tiger Global. CEO Naveen Verma started the company out of a lab in Princeton, where he worked on designing architecture for hardware that would help run large language models more compute and energy efficiently. Verma says the chips allow AI models to run locally on devices such as personal computers.
DEEP DIVE
Elon Musk’s surprise bid for the nonprofit controlling artificial intelligence behemoth OpenAI did exactly what he wanted it to. Announced as OpenAI CEO Sam Altman and other business and world leaders convened in Paris for a global AI summit, the unsolicited $97.4 billion offer for the nonprofit refocused the world’s attention on Musk and his efforts to block OpenAI’s transition to a for-profit company.
An irked Altman quickly dismissed Musk’s offer and sources close to OpenAI say it’s hard to imagine it going anywhere. But even if that’s the case, Musk has likely caused a headache for Altman, who is orchestrating the company’s transition to a for-profit venture. He’s attempted to forcefully raise the nonprofit price – which would make it harder for OpenAI to justify paying anything less.
Musk’s bid is the first hard number that values the nonprofit that controls OpenAI; that entity has to be bought out and become a minority shareholder for OpenAI to successfully transition to a for-profit company. Previously, The Information had reported the nonprofit was worth around $40 billion, citing a 25% stake and the company’s valuation at time. But with his $97.4 billion bid, Musk has backed Altman into a corner; now, as a board member, Altman faces pressure to sell the nonprofit for at least what Musk is asking. If he were to sell for anything less, it’d be a bad look, making it seem like he’s lowballing his own company to reduce share dilution.
“The important part here is that if [the board] doesn’t take it, which they almost certainly won’t, then they’ve made clear that they think the assets Musk is trying to buy are worth more than $97 billion,” a person familiar with the company told Forbes. “So if the for-profit tries to buy them later, the nonprofit will have to get more than that — otherwise the board is likely in breach of their fiduciary duties.”
Read the full story on Forbes.
MODEL BEHAVIOR
Generative AI is making it easier for fraudsters to carry out romance scams at scale, Wired reported. AI chatbots are being used to generate hundreds of deceptive scripts and generate fully fake profiles on dating apps. AI has already made a foray into the dating world. Last year, we wrote about a man who programmed ChatGPT to reply to his matches on Tinder and set up dates for him.

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Why Is This C.E.O. Bragging About Replacing Humans With A.I.?

digitex — Sun, 02 Feb 2025 08:19:03 +0000

Ask typical corporate executives about their goals in adopting artificial intelligence, and they will most likely make vague pronouncements about how the technology will help employees enjoy more satisfying careers, or create as many opportunities as it eliminates. A.I. will “help tackle the kind of tasks most people find repetitive, which frees up employees to take on higher-value work,” Arvind Krishna, the chief executive of IBM, wrote in 2023.And then there’s Sebastian Siemiatkowski, the chief executive of Klarna, a Swedish tech firm that helps consumers defer payment on purchases and that has filed paperwork to go public in the United States with an expected valuation north of $15 billion.Over the past year, Klarna and Mr. Siemiatkowski have repeatedly talked up the amount of work they have automated using generative A.I., which serves up text, images and videos that look like they were created by people. “I am of the opinion that A.I. can already do all of the jobs that we, as humans, do,” he told Bloomberg News, a view that goes far beyond what most experts claim.According to Klarna, the company has saved the equivalent of $10 million annually using A.I. for its marketing needs, partly by reducing its reliance on human artists to generate images for advertising. The company said that using A.I. tools had cut back on the time that its in-house lawyers spend generating standard contracts — to about 10 minutes from an hour — and that its communications staff uses the technology to classify press coverage as positive or negative. Klarna has said that the company’s chatbot does the work of 700 customer service agents and that the bot resolves cases an average of nine minutes faster than humans (under two minutes versus 11).Mr. Siemiatkowski and his team went so far as to rig up an A.I. version of him to announce the company’s third-quarter results last year — to show that even the C.E.O.’s job isn’t safe from automation.In interviews, Mr. Siemiatkowski has made clear he doesn’t believe the technology will simply free up workers to focus on more interesting tasks. “People say, ‘Oh, don’t worry, there’s going to be new jobs,’” he said on a podcast last summer, before citing the thousands of professional translators whom A.I. is rapidly making superfluous. “I don’t think it’s easy to say to a 55-year-old translator, ‘Don’t worry, you’re going to become a YouTube influencer.’”Mr. Krishna, the IBM chief executive, once turned heads when he said A.I. could prompt the company to slow or pause hiring for the roughly 10 percent of its jobs involving back-office roles like human resources.For his part, Mr. Siemiatkowski said that A.I. had allowed his company to largely stop hiring entirely as of September 2023, which he said reduced its overall head count to under 4,000 from about 5,000. He said he expected Klarna’s work force to eventually fall to about 2,000 as a result of its A.I. adoption. (Mr. Siemiatkowski and Klarna declined to comment for this article.)One might be tempted to conclude that Mr. Siemiatkowski is simply unfamiliar with the political sensitivity around questions of automation, or with the best practices for communicating about it to skeptical employees. (“Leaders can combat this initial resistance by highlighting how A.I. can help people focus on more meaningful work,” an IBM study said.)But Mr. Siemiatkowski is well aware of the backlash that his bluntness can provoke. “We did a tweet later on about the marketing things we are doing about A.I., where we have less need for photographers,” he said in the podcast interview. “That had a violent reaction online.”Instead, interviews with former employees and transcripts of internal company meetings suggest that Mr. Siemiatkowski’s pronouncements about A.I. are motivated by something altogether different from political naïveté or an impulse for real talk. And those motivations shed light on the A.I. future that many executives and investors are working to bring about.Leaning In to AutomationSo far, most large companies do not appear to be replacing workers en masse. A report on 50 large banks by Evident, a firm that analyzes A.I. adoption, found that they typically derive other benefits from the technology, like improving services or helping employees work faster.In a paper exploring one area that Klarna has highlighted, customer service, the Stanford economist Erik Brynjolfsson and two co-authors found that A.I. made many employees more productive when it came to relatively complicated tasks, like navigating customers’ tax issues.The bot did this by excelling at certain simpler tasks, like advising the human on the optimal order in which to request information from a customer. But it didn’t handle the interaction from start to finish. (In fairness, the experiment didn’t attempt full automation.) “I think people exaggerate how much they can automate everything in the near term,” said Dr. Brynjolfsson, though he acknowledged that more tasks could be automated as A.I. became more powerful over the next few years.When pressed, Mr. Siemiatkowski has conceded that the picture is somewhat more complicated than his company’s news releases have suggested. He explained on another podcast that Klarna had been relying on humans to perform customer service tasks that other companies had automated long before A.I., like instructing a customer where to go on the Klarna app to delay a payment. As a result, Klarna replaced more workers than other companies would have replaced.His claims about hiring may have been overblown, too. The website TechCrunch searched through Klarna’s job listings more than a year after the company supposedly stopped hiring and found more than 50 openings in a variety of jobs. A Klarna spokesman told the outlet that the company was “not actively recruiting to expand the work force but only backfilling some essential roles” like engineering, and that Mr. Siemiatkowski had been “simplifying for brevity in a broadcast interview.”But all of this raises the question: At a moment when A.I. is already alarming office workers, why would a chief executive not only speak candidly about his company’s progress in automating jobs, but even overstate the case?A Self-Mythologizing RiseThe son of Polish nationals who immigrated to Sweden in the early 1980s, not long before he was born, Mr. Siemiatkowski grew up feeling like something of an outsider in his parents’ adopted country. He has talked of being teased as a child. According to former employees, he once said that feeling like an outsider helped him empathize with Black Americans after the killing of George Floyd.Mr. Siemiatkowski founded Klarna, then known as Kreditor, in 2005 with two classmates after a telemarketing job alerted him to the problems that small companies had collecting payments from online customers. The idea was to guarantee the payment for merchants and collect from the customer later.It was an old retail practice known as “buy now, pay later,” except updated for the internet age.The company quickly turned a profit by charging merchants a fee for the payment service, and began expanding across Europe and taking business from banks. By 2010, Klarna had renamed itself Klarna, meaning “clear,” and had begun to attract the attention of Silicon Valley investors.Mr. Siemiatkowski gave the impression of someone who had for years been playing out the moment in his mind. When the famed Silicon Valley venture capital firm Sequoia dispatched a partner to Sweden to pitch the co-founders on an investment, telling them Sequoia thought they could transform banking the way Google had changed the internet, Mr. Siemiatkowski was quick to pipe up. “Just tell me one more thing,” he said, recalling the exchange to Forbes magazine years later. “If we’re going to be the Google of banks, would you really just send you? Wouldn’t the whole of Sequoia come here?”The Sequoia partner quickly connected the founders with Michael Moritz, one of the firm’s high-profile investors. Mr. Moritz apologized for not appearing in person and later joined Klarna’s board.Mr. Siemiatkowski, who with his strong jaw and blue eyes looks like a long-lost Hemsworth brother, seemed to style himself as the kind of tech mogul investors were eager to back. Former employees said the company’s hiring process for engineers resembled that of a Silicon Valley start-up — using a logic test to screen applicants, then requiring some to demonstrate their coding chops in real time. From Amazon, he borrowed the “two pizza” rule — keeping teams small enough that the group could be fed with two pizzas.In 2019, Klarna began to build a major presence in the United States. The company’s timing proved impeccable. When the pandemic hit, Americans cut back on dining out and travel and embarked on an online shopping splurge — precisely the consumption habits Klarna was built to enable.New investors piled in at ever-higher valuations — from $5.5 billion in 2019 to to $45.6 billion in 2021. Klarna accelerated hiring, roughly tripling in size to 7,000 employees within three years. It ran a Super Bowl ad starring Maya Rudolph to lodge itself in the American psyche.Then the bill came due. From Google to Amazon to Netflix, the share prices of companies that had raked in profits as people retreated to their living rooms were suddenly pummeled by investors who saw rising inflation and interest rates as a sign that the pandemic-era boom was ending.When Klarna tried to raise money again in 2022, reportedly seeking a valuation above $50 billion, investors had other ideas. A funding round announced in July would value it at a mere $6.7 billion.In the meantime, Klarna culled about 10 percent of its employees, under pressure from investors to cut costs, and endured suddenly skeptical media coverage. Mr. Siemiatkowski also now had to contend with another setback to his rise as a tech icon: a growing union presence inside the company.Though morale at Klarna had generally been high because of its collaborative culture and competitive pay, a relatively small group of workers had formed a union in 2020. The union roughly doubled in size, to over 1,000 employees, not long after the downsizing announcement in May 2022.During an all-hands meeting around the same time, a recording of which The New York Times obtained, Mr. Siemiatkowski spoke darkly of how unionized companies handle layoffs (“union representatives and senior management, behind locked doors, decide on the outcome of each individuals”).He seemed to worry that a union would turn Klarna into just another stodgy Swedish company — around 90 percent of the country’s workers are covered by collective-bargaining agreements — and hardly the muse of investors worldwide. “The more everything becomes thick and slow moving,” he said at another meeting, alluding to the effect of a union, “my investors will challenge me.”But as workers prepared to strike in the fall of 2023, the company backed down and signed a collective-bargaining agreement.Mr. Siemiatkowski was sarcastic and brooding as he announced the arrangement at a third all-hands meeting. He appeared to liken union leaders to the pigs in “Animal Farm,” whom George Orwell had intended as a stand-in for Stalinists, and he quipped that there were two people in the entire company of more than 4,000 who made less than what the collective-bargaining agreement would mandate. “They’re going to get a salary increase thanks to us signing the C.B.A.,” he said. “Isn’t that amazing?”A Favorite Guinea PigMr. Siemiatkowski often says he first realized A.I. would upend the workaday world shortly after playing around with OpenAI’s ChatGPT in late 2022, only a few months after Klarna endured layoffs and saw its valuation crater. “I’m on Twitter in November ’22, and somebody is tweeting, ‘You’ve got to try this,’” he said on a podcast. “I’m just like, ‘Jesus, I’m speaking to a computer.’”He quickly arranged a meeting with Sam Altman, the chief executive of OpenAI, and began pushing employees to experiment with the software.Whatever progress Klarna made on automation, Mr. Siemiatkowski sometimes seemed as invested in spinning out a story about A.I. as actually using the technology. In 2024, he and the company regularly put out news releases and conducted interviews, leading to headlines like “Klarna Marketing Chief Says A.I. Is Helping It Become ‘Brutally Efficient,’” in The Wall Street Journal.By the time Mr. Siemiatkowski made the rounds of prominent tech podcasts that summer, in a tour that included the popular show “Acquired” and podcasts hosted by Sequoia and the venture capitalist Logan Bartlett, he seemed to have distilled Klarna’s A.I. story to its sharpest narrative elements.“My understanding is that you told Sam and OpenAI that you wanted to be their guinea pig,” an interviewer said.“Their favorite guinea pig,” Mr. Siemiatkowski corrected.A former Klarna manager, who left in 2022, said the rhetorical emphasis on A.I. was no accident. According to the manager, there was a sense within the company that Klarna had lost its sheen in the media and among investors, and that Mr. Siemiatkowski was desperate to get it back.The former manager said the A.I. story provided a lifeline at a time when Klarna was hoping to offer shares on the public markets. It demonstrated that the company was still on the cutting edge, and that it was shrinking not because it had faltered but because it had figured out how to replace humans with machines.The effort appears to have worked. Klarna’s likely public offering is one of the more anticipated of this year and could fetch triple the valuation that followed its 2022 swoon. Though some of that progress reflects Klarna’s improved financial performance over the past year and a half and the upward march of the market overall, Mr. Siemiatkowski’s relentless focus on A.I. appears to have been important. “The benefits of A.I. are likely to be a key selling point for any Klarna I.P.O.,” The Financial Times wrote last year.It does not appear to have hurt that Mr. Siemiatkowski is willing to go much further in his A.I. pronouncements than fellow C.E.O.s, telling the paper, “Not only can we do more with less, but we can do much more with less.”Mr. Siemiatkowski’s statements are sometimes sweeping or grandiose because, former employees say, he sees himself as a righteous warrior in a fight with powerful forces. “I have always been anti-establishment,” he said at one all-hands meeting. “To me, what we’ve been doing here, going after the banks, is to be anti-establishment.”As with his challenge to Swedish banks and his standoff with the union, Mr. Siemiatkowski’s A.I. campaign appears to be another instance of self-interest merging with heroic self-conception.When the host of the “Big Technology Podcast” asked why he was so intent on talking up Klarna’s A.I. prowess, Mr. Siemiatkowski said it was partly for the good of humanity.“We have a moral responsibility to share that we are actually seeing real results and that that’s actually having implications on society today,” he said. “To encourage people, specifically politicians in society, to actually treating this as a serious change that’s coming.”Then he acknowledged that another part of the motivation was “self-promotion, for sure.” He added, “We’re regarded as a thought leader.”Saying What Investors Can’tMr. Siemiatkowski may have at times overstated what A.I. has accomplished at Klarna, but that doesn’t mean he’s wrong about the future.Dr. Brynjolfsson of Stanford notes that most office jobs are collections of tasks, and that while A.I. can take on some of them, it still struggles to combine most or all of them in the manner of a human.But even he believes that could change within a few years, while a growing number of tech experts argue that artificial general intelligence — a bot that can do anything the human brain does — is not far-off. Mr. Altman of OpenAI recently predicted that A.I. agents — bots than can perform relatively complicated tasks on their own— would soon “join the work force” and “materially change the output of companies.” Others have predicted that such agents will take over a wide variety of jobs.Many tech investors are already banking on this outcome, effectively counting on automation to save their huge bets on free-spending A.I companies. In an influential analysis last year, the venture capitalist David Cahn estimated that the combined A.I.-related revenue of companies like OpenAI and Microsoft was likely to be hundreds of billions a year less than the amount needed to pay back investors.But one way to make the numbers add up is if employers can save hundreds of billions of dollars using A.I. to replace workers in the relatively near future. In that case, the revenue of companies like OpenAI could grow rapidly and their investors could earn a profit. (They might still risk being undercut by Chinese competitors who can build similar technology at lower cost, though that would also make it cheaper for employers to automate work.)The catch is that very few investors and top executives are willing to discuss this in plain language. When it comes to the question of job loss, those with a large financial interest in A.I. tend to euphemize and equivocate.Even Mr. Altman, one of the foremost proponents of the idea that A.I. will soon be capable of advanced humanlike cognition, has increasingly avoided discussing the potential downside for workers. Two years ago, he conceded that A.I. would take over certain jobs and that the shift in power from labor to capital “goes way further in a world with A.I.” By last year, he had toned down this language, telling a podcaster that he, too, imagined A.I. taking over tasks rather than whole jobs and that it would allow people to do work at “a higher level of abstraction.” He did this even as — or perhaps because — he seemed to think the technology was becoming vastly more powerful.(OpenAI declined to comment. The New York Times has sued OpenAI and its partner, Microsoft, for copyright infringement. The two tech companies have denied the claims.)Mr. Siemiatkowski has brought clarity to this discussion. In his eagerness to court investors, and in his tendency to overstate the case and say the quiet part out loud, he has laid bare Silicon Valley’s ambition. In his own slightly muddled way, for his own slightly idiosyncratic reasons, he is helping to surface a conversation that has largely been whispered in the executive suites.Investors in his presence sometimes become so excited about the possibilities of displacing humans that they forget to deploy the usual euphemisms and aphorisms. During a podcast interview with Mr. Siemiatkowski, a partner at the prominent venture firm Kleiner Perkins gushed about Klarna’s “full-on automation at scale” and said, “That’s where it’s eyebrow-raising.”At times, even Mr. Siemiatkowski can be wrong-footed by such directness. When another podcaster asked which jobs were most likely to be automated, he seemed momentarily flustered, then reached for a joke he’d told Sam Altman.“I said to Sam, ‘What you should focus on, try to build A.I. that replaces C.E.O.s, bankers and lawyers,’” he recalled, identifying three unpopular jobs. “‘Nobody will make a big fuss about it.’”

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In the room where A.I. happened

digitex — Sat, 01 Feb 2025 20:16:48 +0000

Nine years ago, I managed to get into a space normally sealed off to the world: the Stanford Artificial Intelligence Laboratory. I wanted to understand this phenomenon that was supposed to change everything. I reported on a meeting among A.I. researchers and venture capitalists looking for the Next Big Thing. As it happened, the topic of their discussion was how to use A.I. to, and I quote, “replace all the writers.” I was there, a writer on the wall.“This was some major disruption,” I wrote shortly thereafter in the dispatch below, “a bunch of non-writers debating how to replace all the writers. I was taking careful notes, so that the replaced writers of the future would have some record of how the purge went down.”Well, here it is.The dispatch was not published at the time, because it didn’t fit my book then in progress. I recently revisited it and was struck by how, in retrospect, our present was being hatched there.So I’m publishing it now, a glimpse into the past where the future was being foretold. It’s a long read, so dive in — or save it for a moment when you have time. I hope you enjoy it.By Anand GiridharadasThe Gates Building at Stanford, home to the A.I. lab.While out in the Bay Area, I spent a few days at the Stanford Artificial Intelligence Laboratory. The lab occupied two floors of the Gates Computer Science Building. It was a dull gray hive of offices and conference rooms. If, for some strange reason, someone blindfolded you and deposited you in its midst, and you somehow failed to notice all the robots and equations, you might guess you were in a regional sales department of a midsized manufacturer of lower-school sports trophies.Nothing in the atmosphere suggested power. Nothing told you that this is the place that had spawned Google. And yet it was said by very intelligent people that the future they were concocting here could change the face of human civilization. Some thought that their work would bring heaven down to earth; others feared this was the closest we had come to hell.The heaven scenario saw a human existence made effortless, seamless, healthy to the possible point of immortality, efficient, leisurely, cornucopiac, creative. A.I. already guessed what you were seeking when you looked things up, and in the future it would know all your needs in every area of life. A.I. already decided when to tell new parents that a newborn might not be breathing, and in the future disease-curing nanobots and big-data-crunching supercomputers could end aging and even dying as we know them. A.I. already traded half of all stocks on the American exchanges, and in the future it might free all of us from the burden of work, and allow us to paint and write sonnets and dance. By giving human beings such mastery over their health and environment, A.I. could, it had been argued, make us the first species to avoid extinction itself.And yet Elon Musk — builder of electric cars and rocket ships, booster of all things technological — had called A.I. the world’s “biggest existential threat” and declared that “with artificial intelligence we’re summoning the demon.” This was the hell scenario. It was less precise, less sure, because it focused on what human beings might not foresee as they built the tools of their replacement. Reid Hoffman, of LinkedIn, compared A.I. to the development of an unknown species that could have major effects on the planet. There was also the humanist worry that an artificially intelligent future would essentially be a future without work for most people — except, of course, for the builders of A.I. and its algorithms. Pope Francis had warned that robotics and related advances could, left alone, “lead to the destruction of the human person — to be replaced by a soulless machine — or to the transformation of our planet into an empty garden for the enjoyment of a chosen few.” The most dire visions had A.I., on its own or in the hands of bad people, speeding up our extinction date.It was a lot of pressure to work on such things. Such was the fate of the researchers of the Stanford A.I. Lab who were drifting into the second-floor lounge this evening. This, sometimes, is how civilization gets remade: by often highly socially awkward people who do not see themselves as remaking it — by a squad of robot-like humans chosen to make robots more human-like.ShareWhat stayed with me most from several days spent at the lab was this meeting, lasting a little more than an hour. For in that meeting, I was able to see, as I hadn’t so clearly before, how Silicon Valley’s rhetoric of prediction works: how a strange cocktail of futurism and cynicism could be used to justify a world that will be devastating for vast numbers of people and great for its predictors. And how cultivating and believing in the idea of your own powerlessness had become an essential tool for seizing power.***Tonight was the biweekly meeting of the lab’s eClub, which described itself as “the first official coalition between the Stanford Artificial Intelligence Laboratory (SAIL) and a cluster of corporate partners to foster discussions between artificial intelligence researchers and venture capitalists interested in real world AI applications.” The techies got to meet the money men of Silicon Valley, who worked a few blocks and a world away on Sand Hill Road. The money men, who were also ThoughtLeaders, got a glimpse into cutting-edge technologies that just might become their next unicorn.The topic of today’s meeting was journalism and writing. They were trying to figure out whether and how to “replace all the writers,” as one of them put it.The perks of coalition-building with venture capitalists: a table to the side was covered with pizza from Pronto, a bottle of Pinot Noir, and some beers. The pizza vanished at the rate of several slices a minute. The Pinot Noir would remain unopened, but some beers were being sipped.About twenty students began to take their seats. Lots of jeans, lots of wrist activity trackers, lots of waifish legs crossed at the knee, lots of genius, lots of zealous and impatient male energy unleavened by social awareness or social grace. There was one woman in the room. Over the next ninety minutes, she would not speak.In one corner of the room sat a pair of venture capitalists. There was a man I will call Marty, a partner at a preeminent venture capital firm nearby, who possessed, especially in this room full of immigrants and immigrants’ children, the special force of the Old White Man who has seen it all, is faintly bored by everything, thinks his first ideas are his best ideas, and has a lot of money. Beside him was a man I will call Ashish, a partner at another top venture capital firm in the Bay, who offered a more realistic ideal for the people in this room. He was Indian, handsome enough not to be rich, but rich all the same, dressed in perfectly fitting dark clothes that were at once sporty and formal, broadcasting a vibe of “I was the youngest partner in the history of my firm.” Which he had been. When you searched his name in Google, the first additional query suggested (by A.I.) was “Ashish ______ net worth.” You could just picture Stanford students looking him up late at night, intimidated and amazed: He studied here, too! He flies microlight airplanes! He is on leave from the Stanford Medical School! Together, Marty and Ashish represented several billions of dollars longing to be invested in kids like these techies.I took a seat beside a student named Manoush. He was unkempt, earnest, slightly hostile. I asked what drew him to A.I. He spoke of wanting to free people from the drudgery of work. Let the machines, the algorithms, do the repetitive things. Free people to think big strategic thoughts.“The biggest factor that leads to increased quality of life is efficiency of workforce,” he said.Without intending to, I must have looked skeptical. Manoush told me to look up the citation myself.There was some tension over Manoush’s vision in A.I. circles. A handful of A.I.’s founding fathers, some of whom were present at the 1956 Dartmouth meeting that was the field’s constitutional convention, lamented that their original project — using computers to seek to understand and mimic human beings — had given way to the more prosaic and lucrative goal of raising productivity. An irascible old-timer like Pat Langley could mourn the days when the “intelligence” in “artificial intelligence” was defined as “the ability to carry out complex, multi-step reasoning, understand the meaning of natural language, design innovative artifacts, generate plans that achieve goals, and even reason about their own reasoning.” But the privatizing drive of the age of markets had reached A.I., too. Things now had to justify themselves in the marketplace. The “commercial successes of ‘niche’ A.I.” and an “obsession with quantitative metrics” had reoriented the field, Langley wrote. A.I. labs had “abandoned the field’s original goal. Rather than creating intelligent systems with the same breadth and flexibility as humans, most recent research has produced impressive but narrow idiot savants.”Manoush believed deeply in the idiot savants. Those bots could free up much human energy. But, I asked Manoush, what about all the people who would be beached, temporarily or even permanently?“We have people who are going to get shafted,” Manoush said. “But in the long term, we are going to have a higher quality of life for the whole.”Leave a commentThis was an important article of faith around the Bay these days. These men and women knew their inventions could be frightening. Their promise was that this was the storm before the calm, the shafting before the emancipation.Of course, there were those, even within the lab, who questioned this vision. Juan Carlos Niebles, a Colombian researcher, laughed off the pop-culture imagery of robots killing off and eating their human masters. But he worried about other threats that to him seemed realistic. He wondered: Would the A.I. agents nurtured by his lab create mass unemployment? Would people need to be paid a minimum income when complex machines are doing so many of the old jobs? How would we occupy people’s time and energy and imagination? Niebles didn’t worry about apocalypses. He worried, with more self-awareness than many winners of the age, that he was participating in the creation of a new world that would be rewarding and fulfilling only for people like him.But he hastened to add that he had no time to think about such matters. “Day to day, we think of: what are the barriers to achieving new things?” he said. The technical problems were so overwhelming that they crowded out reflection. The A.I. researcher’s self-conception was of an unblocker of the blockages standing between us and progress, he said. It was not their habit to muse about consequences.***At present an Italian postdoc named Roberto called the meeting to order and introduced some questions to frame the conversation. How could A.I. help to personalize the news for each person’s interests? How could it mine oceans of data and discover stories hidden in the numbers and patterns? Could it copy the style of particular writers and produce fresh content in their voices?It should be noted that there were no journalists participating in this conversation. (I was a silent observer.) It is far less awkward to reimagine people’s lives in their absence.Some gatherings begin with problems in need of solution. Others begin with solutions seeking a problem. This was a meeting of the latter type. Journalism, of course, had plenty of problems. But no one in the room seemed to know much about those problems; and if they did, those problems weren’t their motivating spur. They were here because they were inventing technologies whose spread they believed was inevitable, and they wanted to see what those technologies could do for — or perhaps to — journalism.An important self-belief in the room seemed to be this: they were extrapolators of the Curves, the seers of forces. It was not their role to say what world they wanted. Their job was to get what they wanted by saying it would happen anyway.Manoush got things rolling with an idea about who should produce the news in the future. The Curve was driving more and more of the world’s Internet traffic and advertising dollars to the big Internet portals. In the quarter in which Manoush spoke, 85 percent of new money spent on online ads was captured by just two companies, Facebook and Google, according to the for-now-still-existing New York Times. (Both companies happened to be major recruiters at the lab.)“It seems pretty obvious to me that news should be moving toward distribution by people who can do advertising better than, like, New York Times and Washington Post, because they just don’t have enough data on you.”It was a modish idea in tech circles: that tech should “eat” the media, just like it should “eat” everything else. In the future that Manoush envisioned, the most powerful entities on earth would also serve as the checks on their own power. But he didn’t propose this idea out of any belief in the world it would imply. It just seemed obvious to him that news should move toward wherever the Curve of advertising revenue is going.A meek but protesting “Well…” shot out a few seats down from Manoush. It was Elek, who looked like a blend of Bjorn Borg and Jesus. “I’ll contest that to some extent,” he said faintly.By the way, just so you’re not alarmed, this was nothing untoward, because disagreements in the lab tended to be devoid of the E.Q. niceties of the business world: “I think that’s a really interesting point, and the only place I’d push back…”; “Just to build on that and take it in a slightly different direction…”; “I think that’s mostly true, but…” Here when you disagreed with a comment in progress, you leaned forward, and your neck stiffened, sometimes to the point of your chin mildly vibrating, and perhaps called up a fake smile that did not mask the contempt you felt, and then you launched.Some people went with the straightforward “No no no no no no no no no.”Others favored the more gentle but still direct “Yeah, I mean, but…”Or, on one occasion, just: “The reason I don’t like this idea…”“Well…” said Elek. “I’ll contest that to some extent.”Manoush turned toward Elek, both necks now stiff, both fake smiles in force: “O.K…”“There’s one of two cases,” Elek said. “Either there’s a lot of money in news, and The New York Times is being greedy and then, yes, Facebook should take a greater share of that. Or there’s not a lot of money in news, and The New York Times is scrambling. And if Facebook takes a bigger share of that, what’ll happen is not the world becomes a better place but all the writers get fired. And then there’s no news for anyone.”Elek, you will notice, reasoned differently from Manoush. Manoush saw a Curve and prophecized-advocated the future that it implied. Elek saw the Curve but didn’t think we were doomed to follow it. He thought we had choices. It would turn out that he wasn’t alone in this view in the room, though he was in a tiny minority. And that minority consisted entirely of Europeans. They, having some history under their belts, perhaps heard alarm bells when people spoke of a writer-free society.Yet, Elek and his fellow E.U. delegates aside, the ThoughtLeaders and their disciples tended to gravitate to Manoush’s view. If we lived in the best time of times, in an endlessly self-improving world, who needed the kind of critical press for which Elek seemed nostalgic?“I look forward to the time when the press covers all the hard work and toil and not the doom and gloom or shame of companies that hit bumps,” a V.C. partner named Josh Elman tweeted. When the darling startup Theranos was the subject of a Wall Street Journal investigation that questioned its basic veracity of its blood-testing business, young founders were incensed: “Sadden by witch hunt against @theranos. Yes, more transparency needed but innovation will have mis-steps. But why burn effort on a cross?” When Mark Zuckerberg pledged to give away ninety-nine percent of his Facebook shares, but to do so through a for-profit company with little oversight or accountability, many raised questions in the press. Sam Altman — Paul Graham’s cofounder at Y Combinator — tweeted: “It’s fine to wait to congratulate until they share more specifics on the recipients, but outright hostility in the mean time makes no sense.” Graham replied: “I think the reason you’re surprised is that not being a loser yourself you underestimate the power of envy.” Many ThoughtLeaders would hardly have minded Google and Facebook “eating” the news, as they liked to call it.***Yet tonight Elek had an unlikely ally. Marty, sitting in the corner, was becoming irritated by all the Facebook talk. He had driven over to hear some techie tell him the future of news lay in companies guys like him had already built.“If we get back to the context of these meetings,” Marty said, pleasantly but with great authority, “we’re trying to think of ways that you can create interesting new businesses.” He offered some kindling: “If Uber wants to replace all the drivers by robots, do we want to replace all the writers by A.I.? I’ll pause there. It strikes me that those are the kinds of things we should be talking about here.”Now we were talking. This was some major disruption: a bunch of non-writers debating how to replace all the writers. I was taking careful notes, so that the replaced writers of the future would have some record of how the purge went down.The other V.C., Ashish, gave Marty a bit of an assist, suggesting they discuss “an algorithmic approach towards content creation.” He praised the news site Buzzfeed, whose tautological purpose was to get the most eyeballs for the things most likely to attract the most eyeballs. The site was putting A.I. to work already, although for now it still involved humans in the process.“A lot of the listicles are often completely curated, or suggested, using this tool they have in-house that pulls together various links being shared across Twitter, Facebook, and so on,” Ashish said. The tool scans the Web for viral outbreaks. Perhaps it detects an upswing in posts about cupcakes. It analyzes them for patterns. “Basic classification techniques like string-matching can tell you that there’s some similarity between these several links that all have to do with how good the cupcakes look.” Then an editor can assign it, a writer can stick a headline on it and choose fourteen of the best examples, and now what was already beginning to trend on its own is unleashed to trend on Buzzfeed.“It turns out people really like that content,” Ashish said. “So maybe it means we’re staring at a future where you do have A.I. helping to create content; it just looks more like Buzzfeed than a New York op-ed.” Laughter filled the room. “And that’s what maybe we all actually secretly want to read.”Ashish had just shown off an important ThoughtLeader move: the faux-populism of claiming to give the people what they want, which just so happens to be rewarding for people like you.A European neck stiffened across the room. It was Roberto’s.Leave a comment“But how far can that go?” he said. “Because at the end of the day, someone needs to go out there and take a picture of that news. And someone needs to sit down and write the original thing that, with A.I., you’re gonna morph. But the original content was paid by someone.”Here, again, one of the European guys was entering the debate and offering some wide-eyed idealism. It was idealistic in this room because it elevated a vision that would require choosing, that was different from what the Curve might bring.Ashish quickly put Roberto in his place by reminding of the power of the Curve: “I would argue that as long as the Internet’s free, there’s going to be enough user-generated content that will allow folks to compile the most interesting things out there.” This was a common Valley refrain: in the future, the news would just be a greatest-hits collection of photos and videos and pieces of text posted by ordinary people.But if writers wanted to save themselves, Ashish said, there were ways. They could, for instance, join Patreon, a platform that allowed artists to crowdsource patronage — to find your own small-dollar Medicis. In other words, in the future the entrepreneurs were building, the way to survive was to become an entrepreneur. The rise of entrepreneurship was, after all, another Curve on which the Valley was gambling.Now another Euro guy, with two-tone brown and blond hair and more of that Euro-humanism, stiffened his neck and wanted in. He didn’t buy this patronage idea, which assumed that people would pay for higher-quality writing. “I mean, if no one cares about good op-eds and they only care about speaking about feelings, then no one’s gonna pay for it,” he said. Once again, a Euro was drawing a distinction between what the Curve would tend toward and what would be good.Ashish would have none of it. “What is the value of journalism?” he asked, laughing as he said it.Two-Tone Euro was still gloomy: “Once you tell people you gotta pay five dollars, or you could get a very shitty version that has a similar title and it’s made by Buzzfeed, they might not pay five dollars anymore.”Ashish didn’t want to be a downer. Besides patronage, there was another bright spot he knew of in journalism. A site called The Information had recently taken Silicon Valley by storm, and its subscriptions weren’t cheap. Here’s why The Information was good, according to Ashish. Because it helped people make money, instead of spouting some vague Euro ideals about democracy and citizenship.“What’s great is their subscriber base are the people they often write about,” he said. “It’s a lot of folks on Sand Hill Road. A lot of people who are in executive positions at tech companies. And they’re willing to pay for that content, because they’re a necessity almost. Business information. You’re not reading, sort of, news. It’s critical now to your business to know.”***As the conversation progressed, the future of journalism was revealing itself: unpaid user-generated content about cupcakes, auto-selected by bots for curation into listicles; journalist-entrepreneurs raising their own patronage; premium content on the society-magazine model of covering the great and good for consumption by the great and good — journalism of and for them.But now here came Roberto with his Euro-sentimentalism, delicately stated though it was.“Journalism — I’m trying to think — is more like the intersection between objective delivering the news and something that’s artistic in the way you write, inspires the person that’s reading, moving the person to a feeling, probably. It’s not so much to have a concrete goal of producing an outcome that would be monetizable.”Again, the Euro-defiance of the Curve. Listen to the words Roberto was condemning: concrete, goal, producing, outcome, monetizable. These were the words that made the Curve curve. What words did he offer instead? Artistic, inspires, moving, feeling. These were the kind of words you depended on when you sought, mostly in vain, to overrule the Curve.ShareBefore long, one of the Americans was helping to bring things back to the Curve. He had an idea for how to disrupt journalism. “Can we continue to distill the content collector, the reporter themselves?” he asked, a little inscrutably. “Instead of The New York Times employing a few hundred reporters, could this turn into a model where you’ve got individual freelancers or individual bloggers just out there taking pictures and writing about things, and A.I. aggregates this information for some kind of distribution?”Reporters at The Baltimore Afro-American, 1958But this only served to rev up Two-Tone’s Euro-sentimentalism once more. He didn’t want to live in a listicular world. And he believed there were many others like him — people who wanted to be elevated by the writing they read and the art they experienced, who, yes, might give in to clickbait in the moment, but who desired to rise above the immediacy and instinct. He wondered aloud: Could A.I. help to build “a new website that keeps you away from cat videos, away from Buzzfeed articles”?This was perhaps a bridge too far — an A.I. tool built to counteract the Curve? So extreme was this Euro-humanism that it now caused a Euro-schism. Roberto, though by the standards of the room a quite committed humanist, couldn’t take it.“Yeah, but sorry,” he said. “Facebook is not a conscience. The fact that you are hooked to Facebook — there’s a reason. And, yeah, it would be great to do something that keeps you away from partying or all these other things. But for some reason you end up going. It’s very hard to change the behavior of someone.”It is hard to change the behavior of someone: an important idea for the winners working in A.I. For those winners to win to the fullest, just with regard to media, algorithms would have to do more and writers, less; layoffs would have to happen; the quality of public discourse would have to drop; the press as an institution would have to rot; writers would have to become eternal fundraisers, dependent on the whims and opinions of their backers; the technology firms that recruited heavily in the Stanford lab would have to control ever more of the society’s information. The architects of A.I. knew that this could become an unpleasant future for many — as a subset of Euro-humanists in the room seemed to think it would.If you were intelligent, as these techies certainly were, you understood that things could grow tense as you built the future of your dreams — a future in which people with your specific skill set would gain an enormous amount of power, even as other people’s lives and many cherished institutions suffered. And so it was far more prudent, if you could pull it off, to present what was happening as inevitable — and, more important, to cast oneself as powerless over these changes.Here, in this laboratory, one saw the banality of disruption. Here you disrupted things because what you knew how to do was disrupt things. You optimized for variables because those happened to be variables that you knew how to optimize for. You could imagine away whole swaths of society, without asking the human questions, because the overwhelming technical questions crowded them out. You amassed what others would experience as great power, while insisting on your impotence. You mused about your tools being used to disrupt things, instead of asking what problems needed you. And you did all this by convincing yourself that your own role was minimal, that you were merely riding atop the Curve.***The handful of Euro-humanists — now excluding Roberto, perhaps — wanted the room to own up to the real choices that they and the world faced. They wanted their colleagues to own up to the “moral character” of their work, to borrow a phrase from Phillip Rogaway, a cryptographer. Rogaway once wrote an essay criticizing his own colleagues for denying the social implications of their work. “Cryptography rearranges power: it configures who can do what, from what,” he said. “This makes cryptography an inherently political tool, and it confers on the field an intrinsically moral dimension.”What he wrote of cryptography perhaps applied to A.I., too. A.I. types could cast their field as “fun, deep, and politically neutral.” Their shallow optimism about the Curve undercut the need for bigger-picture questioning: “a normative need vanishes if, in the garden of forking paths, all paths lead to good (or, for that matter, to bad).” Technologists, Rogaway wrote, prefer to deny that their inventions can either benefit or harm the weak, depending on choices we make together. Technologists were, you could say, a bit like ostriches.Roberto, having traveled to the Americanish side in the ongoing Euro-schism, was in full ostrich mode. “Facebook is not a conscience,” he had said. “It’s very hard to change the behavior of someone.” Then he brought up broccoli. It would be great if people wanted to buy pieces of broccoli at fast-food restaurants. But they don’t. So we have McDonald’s. The world is what it is. They were powerless to change it.This gave Two-Tone Euro the opening he needed. People do want broccoli nowadays! And if such change was coming to food, why not to other things?“Before McDonald’s, there used to be organic farmers,” Two-Tone said. “Then everyone wanted to step away from the old to McDonald’s, and now they’re going back. So in a similar fashion, people were like ‘O.K., let’s go for New York Times,’ now they’re going Buzzfeed, but they’re gonna come back.”Manoush, that champion of efficiency, had been following the back-and-forth and now tried to turn the conversation in a new direction.“There’s a problem here that we’re not tackling, which is: how do you identify an atom of content, right?” he said. “So right now we’re dealing with articles’ being one atom of content. So I wonder if you can break that up further and further, and maybe you can figure out how much of that content to give to each person.”(One might note, as an aside, that even this style of diction aided the Curve view. Manoush, like many in the Valley, began a great many of his sentences with a declamatory “so” and ended a significant fraction with a faux-interrogative “right?” To speak this way was to leave no space for doubt, for choices that might resist forces, for the thwarting of inevitability. This way of speaking reinforced a view of the world’s problems as purely technical — the view that there was, in every situation, a right answer. “So…right?” was the opposite of “From where I sit,” or “but maybe that’s just me.” It rejected the idea that people have different interests and needs and ideals. It rejected the very premise of politics. It dismissed the notion that there are competing values in tension in any situation, and that those values must be weighed and negotiated. It saw a world in which there was always a right answer, and technologists like Manoush had special access to those answers, and the rest of us should speak now or forever be quiet. So when I spoke, it made sense to cajole your agreement, right?)***So Manoush had been talking about how to identify an atom of content, right?A neck stiffened just to Manoush’s right. Mahesh, an Indian techie n a white T-shirt, seemed perplexed by this idea of breaking up news into bits and algorithmically distributing the packages. “I don’t know,” he said, seeming a little lost. “It’s like, what is the goal here? What are you trying to optimize on?”Now this was a great question — perhaps even the question with which the session should have begun. What problem were they actually trying to solve?But here was the problem with starting with problems. To start with the solution was easy: you looked at the tools you had invented and the Curves that were in progress and you imagined where the future would lead: If Uber wants to replace all the drivers by robots, do we want to replace all the writers by A.I.? To start with a problem was trickier, because not everyone agreed on what was problematic. Starting with a problem, your focus had to be on the society’s needs, not on your tools. Solving that kind of problem tended to involve democracy — collective action, contending values, the making of choices.What was most striking about the meeting was what hadn’t been discussed.No one had spoken of democracy and of the place of a press within it.No one had dwelled on what happens to art in an era of free everything.No one had reflected on the extraordinary market power of Amazon and the effect of that power on books and ideas.No one had asked whether the society could protect itself against the Facebook News Feed’s tinkerers slipping their own biases into the algorithm.No one asked these things, for to ask these things was to admit one’s own power and reveal to others their power, and to suggest that you and those others could decide what kind of future it would be, the forces and the Curves be damned.Here these bearers of great power over the future seemed in denial of that power. The world would be what it would be.Before the meeting ended, Two-Tone Euro got up, picked up what appeared to be a homemade hoverboard from the corner — a skateboard-sized platform with a cantaloupe-sized ball in its middle — and rolled away. Others mingled over the remaining pizza and drinks. Just outside, a man retrieving his bicycle from the rack was savoring what he had just imbibed upstairs. That room, he said, wonder filling his eyes, had collided some of the smartest minds in all of Stanford.ShareSome names and identifying details have been changed. All dialogue is quoted verbatim.Photos: Eric Sander/Getty; Andriy Onufriyenko/Getty; Kimberly White/Getty

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Expanding Generative AI with Databricks Deal

digitex — Sat, 01 Feb 2025 02:18:02 +0000

We recently published a list of Coatue’s 35 Most Important AI Stocks. In this article, we are going to take a look at where Amazon.com, Inc. (NASDAQ:AMZN) stands against Coatue’s other most important AI stocks. Artificial intelligence (AI) has fueled a major rally in the technology sector, driving up key market indices. Over the past year, the S&P 500, heavily influenced by tech giants, has risen by nearly 22%, while the tech-heavy NASDAQ Composite has surged over 26%. Initially, market analysts had predicted an increase in interest around growth options for 2024 due to easing inflation and potential rate cuts. However, AI has taken this expected interest and amplified it into an economy-wide wave of optimism. While tech stocks have been the primary beneficiaries, AI’s influence is expanding across industries such as manufacturing, supply chain, transportation, entertainment, and retail. Investment in AI is growing rapidly across various sectors. A recent Goldman Sachs report estimates that global businesses will invest nearly $1 trillion in AI infrastructure over the next few years. Venture capital (VC) investments in AI startups are also on the rise. In the first half of 2024 alone, VC firms made approximately 200 AI-related deals, injecting nearly $22 billion into the sector. The average AI startup funding round now exceeds $100 million, with company valuations averaging over $1 billion. In contrast, non-AI startups typically receive around $20 million in funding and have valuations near $200 million, indicating AI’s outsized appeal to investors. Companies that were early adopters of AI have experienced significant gains, particularly those specializing in graphics processing units (GPUs), AI chips, and generative AI technologies. The median returns of AI-linked firms in the S&P 500 stand at 20%, compared to just 2% for non-AI stocks. AI companies are also responsible for 90% of the total returns on the NASDAQ Composite Index. These gains are expected to drive earnings growth and contribute to broader economic expansion. According to Joseph Briggs, a senior global economist at Goldman Sachs, AI is projected to automate 25% of all work tasks in the next decade, increasing US productivity by 9% and boosting GDP growth by more than 6%. Read more about these developments by accessing 10 Best AI Data Center Stocks and 10 Buzzing AI Stocks According to Goldman Sachs. Philippe Laffont of Coatue Management argues that AI could be the start of a new “super cycle” in the tech industry. Previous cycles included the rise of personal computers in the 1980s, networking in the 1990s, wired internet in the 2000s, and mobile internet in the 2010s, leading to the cloud era. However, software and internet experts Kash Rangan and Eric Sheridan highlight a key difference: this time, companies are linking AI investments directly to revenue generation, providing a financial safety net that was absent in past cycles. Story Continues Since the launch of ChatGPT by OpenAI in early 2023, the industry’s focus has shifted from software to AI hardware and infrastructure. AI infrastructure companies have collectively added nearly $6 trillion to their market capitalization since Q1 2023. Before large-scale AI automation becomes commonplace—MIT economist Daron Acemoglu estimates this will take more than a decade—AI infrastructure is expanding into areas such as utilities, energy, internet, and industrials. Interestingly, companies in these sectors that support AI development have posted returns rivaling those of traditional AI firms. The growing demand for AI-driven data centers is also driving investments in the energy and utilities sectors. Goldman Sachs analysts Carly Davenport and Alberto Gandolf expect AI adoption to drive a surge in electricity demand not seen in decades. However, whether AI’s growth will align with energy infrastructure investments remains uncertain due to regulatory constraints and supply chain limitations in the utilities sector. Even if necessary investments materialize, their full benefits may take years to reach AI companies. Read more about these developments by accessing 30 Most Important AI Stocks According to BlackRock and Beyond the Tech Giants: 35 Non-Tech AI Opportunities. Some investors remain cautious, fearing an AI bubble similar to the dot-com crash of the early 2000s. However, current data suggests that AI valuations are far more grounded than those of the dot-com era. At the height of the dot-com bubble, software firms traded at price-to-earnings (P/E) ratios of 132x, compared to a five-year average of 37x in 1999. In contrast, in 2023, even the biggest AI stocks had P/E ratios around 39x, with a five-year average of 40x. These figures suggest that AI valuations are not overinflated, reinforcing investor confidence in AI’s long-term potential. AI companies are increasingly targeting multi-trillion-dollar valuations, comparable to today’s largest software and internet firms. Over the past decade, tech giants have scaled their businesses to unprecedented levels, combining billions of users, hundreds of billions in revenue, and tens of billions in net income. Today, a handful of firms account for 80% of the valuation of the Fortune 500. These companies dominate industries such as smartphones, e-commerce, cloud computing, and software-as-a-service (SaaS), all of which AI is poised to disrupt. As a result, these firms are aggressively incorporating AI into their business strategies to maintain market leadership. Some investors worry that AI firms could overshadow software companies, impacting long-term valuations. The price-to-sales (P/S) ratio for software stocks, which peaked in 2021, is now at an all-time low. Slower earnings growth has also contributed to negative sentiment in the sector. Coatue’s research shows that over the next twelve months, only 1% of SaaS companies expect 30% earnings growth, down from 30% during the SaaS boom. However, as human-machine interaction shifts towards natural language processing and generative AI, software companies that successfully integrate AI into their platforms are likely to thrive. As inflation cools, rate hikes ease, and prospects for a soft economic landing improve, AI’s macroeconomic outlook remains strong. AI is now the primary driver of future earnings growth in the S&P 500. According to Coatue’s projections, AI-linked stocks are expected to grow at a compound annual rate of nearly 20% over the next three years, outperforming non-AI stocks by approximately 14%. Additionally, 40% of future tech sector earnings are expected to be fueled by AI advancements. All available data points to a bright future for AI investments, with its influence extending far beyond traditional tech firms. As companies continue integrating AI into their operations, productivity and economic growth are set to accelerate, making AI one of the most transformative forces in modern history. For this article, we selected AI stocks by combing through a note on the AI industry by Coatue Management. These stocks are also popular among other hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here). Amazon.com, Inc. (AMZN): Expanding Generative AI with Databricks Deal A customer entering an internet retail store, illustrating the convenience of online shopping. Number of Hedge Fund Holders: 286 Amazon.com, Inc. (NASDAQ:AMZN) operates as a technology conglomerate with core interests in the ecommerce business. In the report for the third quarter of 2024, operating cash flow increased 57% to $112.7 billion for the trailing twelve months, compared with $71.7 billion for the trailing twelve months ended September of the prior year. Free cash flow also increased to $47.7 billion for the trailing twelve months, compared with $21.4 billion for the trailing twelve months ended September of the prior year. This demonstrates the company’s strong cash generation, with significant improvements in both operating cash flow and free cash flow over the past year. In addition, the company’s strategic collaboration with Databricks aims to accelerate the development of custom models built with Databricks Mosaic AI on AWS and for Databricks to leverage AWS Trainium chips as the preferred AI chip. This would help customers improve price performance when building generative AI applications, solidifying the company’s position in the competitive market. Overall, AMZN ranks 1st on our list of Coatue’s most important AI stocks. While we acknowledge the potential of AMZN as an investment, our conviction lies in the belief that some stocks hold greater promise for delivering higher returns, and doing so within a shorter time frame. If you are looking for a stock that is more promising than AMZN but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock. READ NEXT: 20 Best AI Stocks To Buy Now and Complete List of 59 AI Companies Under $2 Billion in Market Cap Disclosure: None. This article is originally published at Insider Monkey.

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AI Revenue Soars with Data Center Growth

digitex — Fri, 31 Jan 2025 13:54:25 +0000

We recently published a list of Coatue’s 35 Most Important AI Stocks. In this article, we are going to take a look at where NVIDIA Corporation (NASDAQ:NVDA) stands against Coatue’s other most important AI stocks. Artificial intelligence (AI) has fueled a major rally in the technology sector, driving up key market indices. Over the past year, the S&P 500, heavily influenced by tech giants, has risen by nearly 22%, while the tech-heavy NASDAQ Composite has surged over 26%. Initially, market analysts had predicted an increase in interest around growth options for 2024 due to easing inflation and potential rate cuts. However, AI has taken this expected interest and amplified it into an economy-wide wave of optimism. While tech stocks have been the primary beneficiaries, AI’s influence is expanding across industries such as manufacturing, supply chain, transportation, entertainment, and retail. Investment in AI is growing rapidly across various sectors. A recent Goldman Sachs report estimates that global businesses will invest nearly $1 trillion in AI infrastructure over the next few years. Venture capital (VC) investments in AI startups are also on the rise. In the first half of 2024 alone, VC firms made approximately 200 AI-related deals, injecting nearly $22 billion into the sector. The average AI startup funding round now exceeds $100 million, with company valuations averaging over $1 billion. In contrast, non-AI startups typically receive around $20 million in funding and have valuations near $200 million, indicating AI’s outsized appeal to investors. Companies that were early adopters of AI have experienced significant gains, particularly those specializing in graphics processing units (GPUs), AI chips, and generative AI technologies. The median returns of AI-linked firms in the S&P 500 stand at 20%, compared to just 2% for non-AI stocks. AI companies are also responsible for 90% of the total returns on the NASDAQ Composite Index. These gains are expected to drive earnings growth and contribute to broader economic expansion. According to Joseph Briggs, a senior global economist at Goldman Sachs, AI is projected to automate 25% of all work tasks in the next decade, increasing US productivity by 9% and boosting GDP growth by more than 6%. Read more about these developments by accessing 10 Best AI Data Center Stocks and 10 Buzzing AI Stocks According to Goldman Sachs. Philippe Laffont of Coatue Management argues that AI could be the start of a new “super cycle” in the tech industry. Previous cycles included the rise of personal computers in the 1980s, networking in the 1990s, wired internet in the 2000s, and mobile internet in the 2010s, leading to the cloud era. However, software and internet experts Kash Rangan and Eric Sheridan highlight a key difference: this time, companies are linking AI investments directly to revenue generation, providing a financial safety net that was absent in past cycles. Story Continues Since the launch of ChatGPT by OpenAI in early 2023, the industry’s focus has shifted from software to AI hardware and infrastructure. AI infrastructure companies have collectively added nearly $6 trillion to their market capitalization since Q1 2023. Before large-scale AI automation becomes commonplace—MIT economist Daron Acemoglu estimates this will take more than a decade—AI infrastructure is expanding into areas such as utilities, energy, internet, and industrials. Interestingly, companies in these sectors that support AI development have posted returns rivaling those of traditional AI firms. The growing demand for AI-driven data centers is also driving investments in the energy and utilities sectors. Goldman Sachs analysts Carly Davenport and Alberto Gandolf expect AI adoption to drive a surge in electricity demand not seen in decades. However, whether AI’s growth will align with energy infrastructure investments remains uncertain due to regulatory constraints and supply chain limitations in the utilities sector. Even if necessary investments materialize, their full benefits may take years to reach AI companies. Read more about these developments by accessing 30 Most Important AI Stocks According to BlackRock and Beyond the Tech Giants: 35 Non-Tech AI Opportunities. Some investors remain cautious, fearing an AI bubble similar to the dot-com crash of the early 2000s. However, current data suggests that AI valuations are far more grounded than those of the dot-com era. At the height of the dot-com bubble, software firms traded at price-to-earnings (P/E) ratios of 132x, compared to a five-year average of 37x in 1999. In contrast, in 2023, even the biggest AI stocks had P/E ratios around 39x, with a five-year average of 40x. These figures suggest that AI valuations are not overinflated, reinforcing investor confidence in AI’s long-term potential. AI companies are increasingly targeting multi-trillion-dollar valuations, comparable to today’s largest software and internet firms. Over the past decade, tech giants have scaled their businesses to unprecedented levels, combining billions of users, hundreds of billions in revenue, and tens of billions in net income. Today, a handful of firms account for 80% of the valuation of the Fortune 500. These companies dominate industries such as smartphones, e-commerce, cloud computing, and software-as-a-service (SaaS), all of which AI is poised to disrupt. As a result, these firms are aggressively incorporating AI into their business strategies to maintain market leadership. Some investors worry that AI firms could overshadow software companies, impacting long-term valuations. The price-to-sales (P/S) ratio for software stocks, which peaked in 2021, is now at an all-time low. Slower earnings growth has also contributed to negative sentiment in the sector. Coatue’s research shows that over the next twelve months, only 1% of SaaS companies expect 30% earnings growth, down from 30% during the SaaS boom. However, as human-machine interaction shifts towards natural language processing and generative AI, software companies that successfully integrate AI into their platforms are likely to thrive. As inflation cools, rate hikes ease, and prospects for a soft economic landing improve, AI’s macroeconomic outlook remains strong. AI is now the primary driver of future earnings growth in the S&P 500. According to Coatue’s projections, AI-linked stocks are expected to grow at a compound annual rate of nearly 20% over the next three years, outperforming non-AI stocks by approximately 14%. Additionally, 40% of future tech sector earnings are expected to be fueled by AI advancements. All available data points to a bright future for AI investments, with its influence extending far beyond traditional tech firms. As companies continue integrating AI into their operations, productivity and economic growth are set to accelerate, making AI one of the most transformative forces in modern history. For this article, we selected AI stocks by combing through a note on the AI industry by Coatue Management. These stocks are also popular among other hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here). NVIDIA Corporation (NVDA): AI Revenue Soars with Data Center Growth Number of Hedge Fund Holders: 193 NVIDIA Corporation (NASDAQ:NVDA) provides graphics, computing and networking solutions. In the report for the fourth quarter of 2024, GAAP earnings per diluted share was $4.93, showing an increase of 33% from the previous quarter and up 765% from a year ago. Non-GAAP earnings per diluted share was $5.16, showing an increase of 28% from the previous quarter and up 486% from a year ago. These metrics indicate strong financial performance driven by higher revenues and improved margins, positioning the company for continued success. Also, record quarterly data center revenue was $18.4 billion, showing an increase of 27% from the third quarter, indicating heightened demand for data center products or services, possibly driven by trends like cloud computing expansion. NVIDIA Corporation (NASDAQ:NVDA) has also launched AI foundation Models for RTX AI PCs. These models offered as NVIDIA NIM microservices, are accelerated by new GeForce RTX 50 Series GPUs, which feature up to 3,352 trillion operations per second of AI performance and 32GB of VRAM. Overall, NVDA ranks 4th on our list of Coatue’s most important AI stocks. While we acknowledge the potential of NVDA as an investment, our conviction lies in the belief that some stocks hold greater promise for delivering higher returns, and doing so within a shorter time frame. If you are looking for a stock that is more promising than NVDA but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock. READ NEXT: 20 Best AI Stocks To Buy Now and Complete List of 59 AI Companies Under $2 Billion in Market Cap Disclosure: None. This article is originally published at Insider Monkey.

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Leading the AI PC Revolution with Breakthrough Technologies

digitex — Fri, 31 Jan 2025 12:48:30 +0000

We recently published a list of Coatue’s 35 Most Important AI Stocks. In this article, we are going to take a look at where Intel Corporation (NASDAQ:INTC) stands against Coatue’s other most important AI stocks. Artificial intelligence (AI) has fueled a major rally in the technology sector, driving up key market indices. Over the past year, the S&P 500, heavily influenced by tech giants, has risen by nearly 22%, while the tech-heavy NASDAQ Composite has surged over 26%. Initially, market analysts had predicted an increase in interest around growth options for 2024 due to easing inflation and potential rate cuts. However, AI has taken this expected interest and amplified it into an economy-wide wave of optimism. While tech stocks have been the primary beneficiaries, AI’s influence is expanding across industries such as manufacturing, supply chain, transportation, entertainment, and retail. Investment in AI is growing rapidly across various sectors. A recent Goldman Sachs report estimates that global businesses will invest nearly $1 trillion in AI infrastructure over the next few years. Venture capital (VC) investments in AI startups are also on the rise. In the first half of 2024 alone, VC firms made approximately 200 AI-related deals, injecting nearly $22 billion into the sector. The average AI startup funding round now exceeds $100 million, with company valuations averaging over $1 billion. In contrast, non-AI startups typically receive around $20 million in funding and have valuations near $200 million, indicating AI’s outsized appeal to investors. Companies that were early adopters of AI have experienced significant gains, particularly those specializing in graphics processing units (GPUs), AI chips, and generative AI technologies. The median returns of AI-linked firms in the S&P 500 stand at 20%, compared to just 2% for non-AI stocks. AI companies are also responsible for 90% of the total returns on the NASDAQ Composite Index. These gains are expected to drive earnings growth and contribute to broader economic expansion. According to Joseph Briggs, a senior global economist at Goldman Sachs, AI is projected to automate 25% of all work tasks in the next decade, increasing US productivity by 9% and boosting GDP growth by more than 6%. Read more about these developments by accessing 10 Best AI Data Center Stocks and 10 Buzzing AI Stocks According to Goldman Sachs. Philippe Laffont of Coatue Management argues that AI could be the start of a new “super cycle” in the tech industry. Previous cycles included the rise of personal computers in the 1980s, networking in the 1990s, wired internet in the 2000s, and mobile internet in the 2010s, leading to the cloud era. However, software and internet experts Kash Rangan and Eric Sheridan highlight a key difference: this time, companies are linking AI investments directly to revenue generation, providing a financial safety net that was absent in past cycles. Story Continues Since the launch of ChatGPT by OpenAI in early 2023, the industry’s focus has shifted from software to AI hardware and infrastructure. AI infrastructure companies have collectively added nearly $6 trillion to their market capitalization since Q1 2023. Before large-scale AI automation becomes commonplace—MIT economist Daron Acemoglu estimates this will take more than a decade—AI infrastructure is expanding into areas such as utilities, energy, internet, and industrials. Interestingly, companies in these sectors that support AI development have posted returns rivaling those of traditional AI firms. The growing demand for AI-driven data centers is also driving investments in the energy and utilities sectors. Goldman Sachs analysts Carly Davenport and Alberto Gandolf expect AI adoption to drive a surge in electricity demand not seen in decades. However, whether AI’s growth will align with energy infrastructure investments remains uncertain due to regulatory constraints and supply chain limitations in the utilities sector. Even if necessary investments materialize, their full benefits may take years to reach AI companies. Read more about these developments by accessing 30 Most Important AI Stocks According to BlackRock and Beyond the Tech Giants: 35 Non-Tech AI Opportunities. Some investors remain cautious, fearing an AI bubble similar to the dot-com crash of the early 2000s. However, current data suggests that AI valuations are far more grounded than those of the dot-com era. At the height of the dot-com bubble, software firms traded at price-to-earnings (P/E) ratios of 132x, compared to a five-year average of 37x in 1999. In contrast, in 2023, even the biggest AI stocks had P/E ratios around 39x, with a five-year average of 40x. These figures suggest that AI valuations are not overinflated, reinforcing investor confidence in AI’s long-term potential. AI companies are increasingly targeting multi-trillion-dollar valuations, comparable to today’s largest software and internet firms. Over the past decade, tech giants have scaled their businesses to unprecedented levels, combining billions of users, hundreds of billions in revenue, and tens of billions in net income. Today, a handful of firms account for 80% of the valuation of the Fortune 500. These companies dominate industries such as smartphones, e-commerce, cloud computing, and software-as-a-service (SaaS), all of which AI is poised to disrupt. As a result, these firms are aggressively incorporating AI into their business strategies to maintain market leadership. Some investors worry that AI firms could overshadow software companies, impacting long-term valuations. The price-to-sales (P/S) ratio for software stocks, which peaked in 2021, is now at an all-time low. Slower earnings growth has also contributed to negative sentiment in the sector. Coatue’s research shows that over the next twelve months, only 1% of SaaS companies expect 30% earnings growth, down from 30% during the SaaS boom. However, as human-machine interaction shifts towards natural language processing and generative AI, software companies that successfully integrate AI into their platforms are likely to thrive. As inflation cools, rate hikes ease, and prospects for a soft economic landing improve, AI’s macroeconomic outlook remains strong. AI is now the primary driver of future earnings growth in the S&P 500. According to Coatue’s projections, AI-linked stocks are expected to grow at a compound annual rate of nearly 20% over the next three years, outperforming non-AI stocks by approximately 14%. Additionally, 40% of future tech sector earnings are expected to be fueled by AI advancements. All available data points to a bright future for AI investments, with its influence extending far beyond traditional tech firms. As companies continue integrating AI into their operations, productivity and economic growth are set to accelerate, making AI one of the most transformative forces in modern history. For this article, we selected AI stocks by combing through a note on the AI industry by Coatue Management. These stocks are also popular among other hedge funds. Why are we interested in the stocks that hedge funds pile into? The reason is simple: our research has shown that we can outperform the market by imitating the top stock picks of the best hedge funds. Our quarterly newsletter’s strategy selects 14 small-cap and large-cap stocks every quarter and has returned 275% since May 2014, beating its benchmark by 150 percentage points (see more details here). Intel (INTC): Leading the AI PC Revolution with Breakthrough Technologies A technician soldering components for a semiconductor board. Number of Hedge Fund Holders: 68 Intel Corporation (NASDAQ:INTC) markets key technologies for smart devices. There are several reasons why this company is a worthwhile investment. As per the report for the third quarter of 2024, total revenue was $13.3 billion, which shows that the company is generating substantial sales, a healthy indicator of ongoing market activity and business operations. Also, Intel Corporation (NASDAQ:INTC) continues to lead the AI PC category and will ship more than 100 million AI PCs by the end of 2025. Intel and Amazon Web Services (AWS) are also finalizing a multi-year, multi-billion-dollar commitment to expand the companies’ existing partnership to include a new custom Xeon 6 chip for AWS on Intel 3 and a new AI fabric chip for AWS on Intel 18A. Overall, INTC ranks 19th on our list of Coatue’s most important AI stocks. While we acknowledge the potential of INTC as an investment, our conviction lies in the belief that some stocks hold greater promise for delivering higher returns, and doing so within a shorter time frame. If you are looking for a stock that is more promising than INTC but that trades at less than 5 times its earnings, check out our report about the cheapest AI stock. READ NEXT: 20 Best AI Stocks To Buy Now and Complete List of 59 AI Companies Under $2 Billion in Market Cap Disclosure: None. This article is originally published at Insider Monkey.

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