That reflects not Mr Altman’s leadership but a broader trend in the technology industry, one that OpenAI itself precipitated. Since the launch of ChatGPT in November 2022, the market for AI labour has been transformed. Zeki Research, a market-intelligence firm, reckons that around 20,000 companies in the West are hiring AI experts. Rapid advances in machine learning and the potential for a “platform shift”—tech-speak for the creation of an all-new layer of technology—has changed the types of skills employers are demanding and the places where those who possess them are going. The result is a market where AI talent, previously hoarded at tech giants, is becoming more distributed.
Start with the skills. Technology giants such as Microsoft and Google may be laying off non-engineers but they are seeking out star researchers who can understand, and build, cutting-edge models. This group consists of perhaps several hundred people such as Mr Sutskever or Jeff Dean, who runs Google’s AI efforts. Companies covet such superstars because they can produce breakthroughs that, say, dramatically increase the efficiency of an AI system or make it less prone to confabulate. That makes them incredibly valuable; many command seven-figure pay packages.
Some are hired without interviews—or as entire teams. In March Microsoft recruited most of the staff of Inflection ai, a startup building cutting-edge models, including its co-founder, Mustafa Suleyman—a move that has reportedly attracted the attention of trustbusters at the Federal Trade Commission. (Mr Suleyman sits on the board of The Economist’s parent company.) Mark Zuckerberg, the boss of Meta (Facebook’s parent company), personally emailed some researchers at DeepMind, Google’s AI lab, in an effort to enlist them.
More intriguing is how generative AI has changed the talent market further down the ladder. According to data from Indeed, a job-listing website, one in 40 vacancies for software developers in America mentions skills related to “generative” AI, the sort that makes ChatGPT so humanlike. That is a more than 100-fold increase since the start of 2023. Amit Bhatia, co-founder of Datapeople.io, a research firm, says that before ChatGPT a medium-sized tech firm might employ a handful of AI engineers who built small models to do things such as analyse the sentiments of customers’ emails. Today generative models can do a much better job than small, in-house efforts.
The result is that some AI engineers are now given the task of working out which AI system to use and how to connect it to a company’s data. Mr Bhatia notes that the share of software-engineering job listings citing such “MLops” (short for machine-learning operations) has doubled since the start of 2022.
Different types of skills are also in demand. Kelsey Szot, a co-founder of Adept, another AI startup, points to individuals who quickly learn how to use AI tools and can stitch them together to build something new and impressive. Unlike the stuffy PhDs, they come up with ideas that are often not academically elegant. But, says Ms Szot, they will solve a problem on a tight deadline. In the ultra-competitive world of AI startups, that is invaluable.
As a result of all this demand, talent flows are shifting. For years engineers flocked to the big-tech quintet: Alphabet (Google’s corporate parent), Amazon, Apple, Meta and Microsoft. Live Data Technologies, a research firm, tracks job moves between companies. Of the AI workers in its database, the big five’s cumulative net additions (hires minus departures) averaged 168 a month between January 2019 and November 2022, when ChatGPT was released. Many of those who left one of the big five simply joined another.
Over the next nine months, however, the net flow of AI workers to the giants reversed to an average monthly outflow. The giants are now once again adding to their AI payrolls, for example poaching boffins from less-big tech companies with less impressive AI pedigrees, such as IBM and Oracle. But the net inflows have still not returned to their long-run average.
Where is the ai talent going instead? One popular destination is Nvidia, a chipmaker whose “graphics-processing units” are powering the AI boom and whose ambitions extend beyond hardware to software and applications. This month its market value surpassed $3trn, overtaking Apple and within striking distance of Microsoft, currently the world’s most valuable company. Others joined more mature startups, such as Databricks, a database and AI firm, and OpenAI.
But one in seven of the big-tech leavers went to startups in “stealth” mode, which have not unveiled products or announced plans. All eight authors of “Attention is all you need”, a paper published in 2017 that provided the algorithmic underpinnings of today’s generative AI, have left Google, where they were working at the time. Seven have founded their own firms (the other joined OpenAI).
One motivation for going to a smaller startup may be financial. For an AI wizard the potential rewards from owning a stake in a successful firm could easily outweigh the salary and stock options offered by a tech juggernaut. Researchers also increasingly want to work on meaningful problems. Since 2015 the number of them joining the health-care sector each year has increased 20-fold, according to Zeki (which may explain why Google is working on Med-PaLM 2, an AI doctor). Another motive is autonomy. “There is just too much brand risk in big companies to ever launch anything fun,” Noam Shazeer, one of the authors of the attention paper, told a venture-capital conference last September. He went on to co-found Character.ai, which allows users to create chatbots with different personalities.
The good news for big tech and small startups alike is that the supply of AI labour is growing. One source is academia. According to a report from Stanford University, in 2011 about 41% of AI PhDs took jobs in industry, roughly the same share as those taking jobs in academia. By 2022 that figure stood at 71% for industry, compared with 20% for academia. Universities are teaching more AI, too. The number of English-language, AI-related degree programmes has tripled since 2017. “All computer-science departments are becoming machine-learning departments,” says Naveen Rao of Databricks.
For American firms, which dominate the global AI industry, hiring from other countries is another way to alleviate the talent shortage. In October President Joe Biden signed an executive order to try to loosen immigration rules to let more AI experts study and work in America. Google and Microsoft have written to the Department of Labour to show their support for the plan. Other governments want the same thing. The EU is planning training schemes and subsidies. The Chinese government plans to attract talent to its shores by, among other things, establishing AI academies in Beijing and Shanghai. On every level, competition for AI workers is heating up.
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