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    HomeExplained newsletterIs there an AI bubble — and is it about to pop?

    Is there an AI bubble — and is it about to pop?

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    Traders work on the floor of the New York Stock Exchange

    Wall Street stocks deepened their losses on Monday and had their worst day in 13 years in Tokyo as fears of a U.S. recession and overvaluation of AI and technology companies spread panic across the trading floor. | Charlie Tribelau/AFP via Getty Images

    What is the future value?

    Usually to answer this question, you have to ask philosophers or economists. But if you’re a tech CEO, you is a real number: About $1 trillion.

    How much is the tech industry as a whole prepared to spend on building artificial intelligence in the coming years? Even in Silicon Valley, where several companies have market capitalizations that begin with “T,” a trillion dollars is a lot of money. And nowhere will you find a more passionate campaigner for AI than in the C-suite of companies like Google and Microsoft, eventually, to recoup all that money. The alternative would be an economic recession the likes of which we haven’t experienced in years.

    Which may be in the process of happening.

    On Monday, the stock market continued its days of heavy losses, with the S&P down 3 percent by the end of the day. The blood-letting was led by the same technology companies that drove the market to record highs in recent months, with AI chip maker Nvidia falling nearly 7 percent and Amazon down 4 percent.

    There are a number of reasons why the market is at least temporarily underperforming, including the possibility that the Federal Reserve will be too slow to cut interest rates in the face of a weak U.S. economy. Recent data on US hiring and manufacturing activity have been weaker than expectedThis helped fuel off the sale.

    But there is real concern that despite the hundreds of billions spent so far building the AI ​​industry, and the hundreds of billions projected to be spent in the coming years, AI companies are not yet producing much. On the way to economic value. And they may not for the foreseeable future.

    The noise you’re hearing could be an AI investment bubble.

    Big AI dreams

    Nobody spends trillions of dollars on something unless they really believe in it — and Silicon Valley really, really believes in the transformative economic potential of AI. Way back in 2018, when ChatGPT was just a twinkle in OpenAI’s Sam Altman’s eye, Google CEO Sundar Pichai famously told Kara Swisher that “AI is one of the most important things humanity is working on. It’s deeper than electricity or fire, I don’t know.”

    Fire, I think we can all agree, is pretty important. You can even think of it as humanity’s first breakthrough product. But to tech leaders like Pichai, the prospect of effective, simple artificial intelligence is as revolutionary as the day one of our Paleolithic ancestors rubbed two sticks together. And once OpenAI releases ChatGPT in November 2022, exposing the world to the real magic that is large language models (LLMs), companies race to catch that fire.

    So investors like OpenAI (currently valuable $80 billion or more) and anthropogenic (approx at $18.4 billion). Only in the US, AI startups Raised $23 billion in capital in 2023, and more than 200 such companies around the world are unicorns – meaning they are worth $1 billion or more.

    All of this is a measure of the technology’s confidence that the AI ​​market will eventually prove titanically huge. one forecast Consultancy PwC estimates that AI could add about $16 trillion — there’s that word again — to the global economy by 2030, mainly from vastly increased labor productivity.

    Add that to the tech giants Lots of cash on handand is actively run First post to cross when it comes to AI against each other. If you believe that the AI ​​industry will be worth trillions — and that the bulk of that value will go to early leaders — then like Pichai said In a recent earnings call, “the risk of underinvestment is dramatically greater than the risk of overinvestment.”

    But the bill is mounting, because generative AI isn’t cheap — both to build and to run.

    When the bill comes due

    There is also Sam Altman himself said that OpenAI is “the most capital intensive startup in history.” Because as the models get bigger and bigger, they cost more to train. And that’s not just the cost of building the models – running them is also very expensive. An analysis last year estimated that it costs OpenAI $700,000 per day To run chatgpt, mainly all that computation-intensive server time. And the more ChatGPT and other LLMs are used, the more those costs will increase.

    While Silicon Valley didn’t invent the saying that “you have to spend money to make money,” it certainly lives by it. But the revenue these companies bring in through their premium model subscriptions is only a fraction of what they cost. Information Recently reported OpenAI could lose $5 billion this year, which is close to 10 times what it will lose in 2022.

    This is not a good trajectory, and neither is ChatGPT’s user base. Tech analyst Benedict Evans recently wrote that many people and companies try AI services like ChatGPT rarely stick to this. (Notably, ChatGPT usage seems to drop off meaningfully during the school holidays, in case you’re wondering who the power users are.)

    While what LLMs can do is impressive, especially compared to what seemed possible a decade ago, the promise of artificial general intelligence could replace entire classes of workers. still be true. As it stands now, the industry as a whole seems to be suffering from a classic Silicon Valley problem: this Lack of product-market fit. Chatbots aren’t a real product yet, and it’s not yet clear how big the market for them is. So do experts from Wall Street banks Like Goldman Sachs Technology to VCs Like Sequoia Capital Yellow warning flags have been thrown around the AI ​​industry — and why investors seem to be starting to pay attention to them.

    None of this is to say that AI itself doesn’t yet have revolutionary potential, or that the industry won’t eventually fulfill those dreams. The dot com crash of the early 2000s was due to the overinvestment and overvaluation of the era’s startups, but Evans notes that what remained set the stage for today’s mega-companies like Google and Meta. The same may one day be true for AI companies. But these AI companies may not exist without financial improvements.

    This story was originally published by Today, explainedVox’s flagship daily newsletter. Sign up for future editions here.

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