Well, that actually is a better segue to this next chart I was going to show you than I thought it would be, which is there's some suspicions going around that this whole thing has become a kind of circular money machine, that the hunt for growth, the hunt for justifying share prices and investment and valuations is leading to just money constantly passing hands to create the almost appearance of activity.
Reinforcement learning (RL) is the next frontier, Google is surging, and the party scene has gotten completely out of hand. Those were the through lines from this year's NeurIPS in San Diego. NeurIPS, or the "Conference on Neural Information Processing Systems," started in 1987 as a purely academic affair. It has since ballooned alongside the hype around AI into a massive industry event where labs come to recruit and investors come to find the next wave of AI startups.
The big worry centers on GPUs, the chips needed to train and run AI models. As new GPUs come out, older ones get less valuable, through obsolescence and wear and tear. Cloud companies must use depreciation to reduce the value of these assets over a period that reflects reality. The faster the depreciation, the bigger the hit to earnings. Investors have begun to worry that GPUs only have useful lives of one or two years,
Business Insider spoke to AI executives outside Big Tech, who said they worry the fees could hinder progress and limit the potential of startups. It could also help the US develop its own talent, one of them said. H-1B visas allow US employers to hire highly skilled foreign workers for specialized jobs. These visas have become a mainstay of the tech industry, with tech giants and startups alike hiring thousands of H-1B workers every year.
During the TechCrunch Sessions: AI, the panelists provided insights on navigating the competitive landscape, where established firms make it difficult for new entrants to gain traction.
