Chinese tech companies and Wall Street trading firms were among the most prominent participants at the hottest annual machine learning conference this week, when more than 10,000 of the world’s top artificial intelligence researchers gathered in New Orleans.
Their presence shows how intense the competition for AI talent has become, with many PhD students making the trip specifically in the hopes of landing a job at a place like Google or OpenAI, where they could potentially earn upwards of $500,000 a year.
Several attendees at the Conference on Neural Information Processing Systems, or NeurIPS, told Semafor they arrived in Louisiana knowing their skills were more in demand than ever, thanks to ChatGPT and the broader frenzy over generative AI tools. The chatbot and its competitors have proven that open-ended machine learning research can lead to lucrative breakthroughs, giving companies a compelling reason to pour more resources into it.
That’s one reason why Chinese tech companies were so visible at the event, despite growing tensions between Washington and Beijing over the development of advanced technology, especially artificial intelligence. Ant Group, an Alibaba subsidiary responsible for the payment platform Alipay, had a large booth advertising its latest tech, though the word “China” didn’t appear anywhere.
A recruiter from Tencent hung up flyers around the conference advertising jobs working on “fundamental AI techniques” that would be applied to video games. The ads were written in both English and Mandarin, and instructed interested applicants to reach out on WeChat. Newer Chinese companies were there too, including Zhipu, a startup working on large language models that has raised over $340 million this year.
Tech firms like Amazon and TikTok, which one California professor said both pay among the highest starting salaries to newly minted PhDs, competed for talent with another industry: finance. Trading shops like Citadel had big booths at NeurIPS too, where they pitched AI researchers on using their skills to conduct market research. Jane Street Capital boasted that new employees would be helping to “keep financial markets transparent and efficient.” (Not to mention making enormous profits.)
NeurIPS, which was founded in 1987, has long been an important venue for PhD students trying to navigate the cutthroat academic job market. But over the last decade or so, major tech companies have increasingly used the event to lure talent, to the point that some see going to Silicon Valley for a year or two as an alternative to taking a postdoctoral fellowship.
But a sizable number of researchers still hope they will eventually land tenured professorships. While the pay gap between industry and academia has ballooned, being at a university remains one of the only places where experiments can be carried out with near total freedom. One PhD student at a university in South Korea told Semafor he was especially wary of joining a firm like Google DeepMind right now, where he perceived the focus was shifting from theoretical research to developing revenue streams for machine learning technology.
Even if research is the ultimate goal, academia is not necessarily the easiest place to bring that dream to life. The California professor noted that training and running large language models takes huge amounts of expensive computing resources, which most universities can’t afford. He estimated that at least half of the attendees at NeurIPS are doing work that requires generous computing budgets.
Attending NeurIPS demonstrated the large gulf between how the AI industry is perceived and the way it really operates. While the narrative in Washington is that the U.S. and China are decoupling their technology ecosystems, the reality is that AI researchers from both countries are still engaging in plenty of mutually beneficial collaboration.
Much of that work happens when Chinese students come to the U.S. to obtain advanced degrees. Previously, most stayed in America after they graduated, but more top scientists are now returning to the People’s Republic, a trend that may benefit Chinese companies recruiting at events like NeurIPS.
Another example is the hype around tools like ChatGPT. None of the researchers I spoke to doubted that OpenAI’s creation had transformed the industry, but they noted that the space is much broader than chatbots. Perhaps just as many PhD graduates will go on to optimize stock trading programs or develop drugs (AstraZeneca also had a booth at NeurIPS).
But the biggest disconnect is how worried most researchers feel about potential catastrophic risks related to advanced AI. Over the last year, a number of tech luminaries have raised concerns that developing superintelligent systems could pose an existential threat to humanity, and their perspectives have gained a lot of mainstream attention. But that rhetoric didn’t appear to be very common at NeurIPS, though there were plenty of researchers presenting work about racial bias, cybersecurity vulnerabilities, and other types of more common harms.
The View From AI safety advocates
Some NeurIPS attendees used the conference to push back against the idea of developing AGI, or artificial general intelligence, arguing systems smarter than humans will pose a danger to society. At a social event on Wednesday night, several of them passed out purple t-shirts with the phrase “Just Don’t Build AGI” printed on them above the Nike logo, a play on the athletic wear brand’s “Just Do It” slogan. The event was co-hosted by the nonprofit Center for AI Safety.
- NeurIPS was known for decades as NIPS, but organizers finally changed the acronym in 2018 after repeated protests over its sexist connotations as well as the word’s use as a slur against people of Japanese descent. The backlash started reaching its peak a year earlier, when the conference was preceded by an unofficial event called TITS.