Just as speculative frenzies repeatedly occur in financial markets, they also seem to form around predictions made in the wake of technology breakthroughs. What does that mean for the biggest technological breakthrough of recent years, generative AI? Pundits have one-upped each other with descriptions of how radically it will transform every aspect of human life. But will reality justify them?
An article in the Wall Street Journal pours water on the generative AI frenzy by pointing out a big problem; the algorithms may have learned about as much as they can for the foreseeable future.
“These models work by digesting huge volumes of text, and it’s undeniable that up to now, simply adding more has led to better capabilities. But a major barrier to continuing down this path is that companies have already trained their AIs on more or less the entire internet, and are running out of additional data to hoover up.”
Add to that the fact that AI has trouble creating its own new training data, and you have the conditions for a bubble that may not only embarrass a lot of pundits, but burst the balance sheets of companies currently investing so heavily in an AI-powered future.
None of this is to say that today’s AI won’t, in the long run, transform all sorts of jobs and industries. The problem is that the current level of investment—in startups and by big companies—seems to be predicated on the idea that AI is going to get so much better, so fast, and be adopted so quickly that its impact on our lives and the economy is hard to comprehend.