AI Is Improving Faster Than Most Humans Realize
Artificial intelligence advances in a manner that's hard for the human mind to grasp. For a long time nothing happens, and then all of a sudden something does. The current revolution of Large Language Models (LLMs) such as ChatGPT resulted from the advent of “transformer neural networks” in about 2017.
What will the next half-decade bring? Can we rely on our current impressions of these tools to judge their quality, or will they surprise us with their development? As someone who has spent many hours playing around with these models, I think many people are in for a shock. LLMs will have significant implications for our business decisions, our portfolios, our regulatory structures and the simple question of how much we as individuals should invest in learning how to use them.
To be clear, I am not an AI sensationalist. I don't think it will lead to mass unemployment, much less the “Skynet goes live” scenario and the resulting destruction of the world. I do think it will prove to be an enduring competitive and learning advantage for the people and institutions able to make use of it.
I have a story for you, about chess and a neural net project called AlphaZero at DeepMind. AlphaZero was set up in late 2017. Almost immediately, it began training by playing hundreds of millions of games of chess against itself. After about four hours, it was the best chess-playing entity that ever had been created. The lesson of this story: Under the right conditions, AI can improve very, very quickly.
LLMs cannot match that pace, as they are dealing with more open and more complex systems, and they also require ongoing corporate investment. Still, the recent advances have been impressive.
I was not wowed by GPT-2, an LLM from 2019. I was
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