Rising AI costs have contributed to the steepest drop in Big Tech stocks since before ChatGPT launch, Adrian Cox writes in his article on finews.first. What happened?
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Alphabet’s capital expenditure doubled to $13.2 billion in the second quarter from the same period last year, which it says was «driven overwhelmingly» by infrastructure investments as the owner of Google goes full steam ahead on Artificial Intelligence (AI). Meanwhile, Tesla says the 39 percent jump in its operating expenses from a year earlier was «largely driven by AI projects» and that it has spent $0.6. billion on AI infrastructure in the second quarter.
Concern about a lack of much evidence that higher AI spending is translating into conspicuous returns helped trigger a near 6 percent average drop in the seven Big Tech stocks in the US, the day after Tesla and Alphabet reported earnings. That was their largest daily loss since September 2022, pre-history as far as generative AI is concerned before OpenAI’s ChatGPT went live in November of that year.
«Beyond the cloud, however, indications of returns are more qualitative than quantitative»
While tech firms are ramping up AI spending, revenue has so far been contained within the cloud business where companies train and run AI models. Indeed, Alphabet CEO Sundar Pichai says AI infrastructure and generative AI solutions «for cloud customers have already generated billions in revenues» so far this year.
Beyond the cloud, however, indications of returns are more qualitative than quantitative. Pichai added: «People who are looking for help with complex topics are engaging more and keep coming back for AI Overviews,» which give short AI-generated answers in addition to normal search results.
By relying on AI returns from cloud infrastructure, tech firms are counting on developers to continue to build and run ever more compute-hungry AI models. However, equity analysts think AI «could prove incremental to search revenue growth» for Alphabet as the company introduces ads to AI Overviews in the US.
«Whoever blinks for a second could risk falling light-years behind everyone else»
Tech firms are competing to lead the AI race because the high costs, scarce semiconductor resources, and speed of progress invest a zero-sum game. There is only likely to be space for a couple of champions. Whoever blinks for a second could risk falling light-years behind everyone else.
The fear of missing out is real. Pichai says «The risk of underinvesting is dramatically greater than the risk of overinvesting,» while also saying «We are relentlessly driving efficiencies in our AI models». Analysts have increased their full-year capex forecasts for Alphabet in their report here. Meanwhile, Tesla projects that AI training capacity will continue to increase throughout the year.
The sky is the limit for AI costs as companies push toward AI that they say will be not only more efficient but also generally smarter than humans. Anthropic CEO Dario Amodei has said that training an AI model could cost as much as $10 billion two years from now, compared with about $100 million currently.
Adrian Cox is a strategist at Deutsche Bank on the Thematic Research team currently focusing on the impact of Artificial Intelligence on jobs, the economy, and society.
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