AI Reality Check: Are LLMs a Dead End?

We've been told time and again that the massive large language models trained by companies like OpenAI and Anthropic are poised to utterly transform our world. We've been told that huge percentages of existing jobs are soon to be automated. We've been told that skills like writing and photography and filmmaking are all about to be outsourced. And we'd be told if we're not careful, the systems built on these models might someday soon become sentient and even threaten the existence of the human race.

But here's the thing. One of the AI pioneers who helped usher in this current age is not convinced His name is Jan Lacoon, and he's been long arguing that not only will LLM-based AI fail to deliver all these disruptions, but that it is, and I'm quoting him here, a technological dead end. People have started to listen. Earlier this month, a syndicate of investors, including Jeff Bezos and Mark Cuban, along with a bunch of different VC firms,

raised over a billion dollars to fund Lacun's new startup, Advanced Machine Intelligence Labs, which seeks to build an alternative path to true AI, one that avoids LLMs altogether. After all of the hype and stressed and hand-reagging around LLM-based tools like chat GPT and Cloud Code, is it possible that Jan Lacun was right that those specific types of tools won't change everything? And if so, what's going to come next. If you've been following AI news recently, you've probably been asking these questions and today we're going to seek some measured answers.

We already have this episode, so unlocking it is cheap and permanent: the full transcript (31 minutes, 5,781 words), segment and word-level timestamps, and .txt, .srt, .vtt and word-level JSON downloads, as many times as you like, forever.

No account needed, we create one from your checkout email. With credits it is 1 credit; packs start at 10 episodes for $5, and monthly plans are cheaper still.