Jeremy Howard was recently[1] interviewed on the Machine Learning Street Talk podcast: YouTube link, interactive transcript, PDF transcript.

Jeremy co-invented LLMs in 2018, and taught the excellent fast.ai online course from which I learned much ML in ~2018, and he uses LLMs all the time, e.g. 90% of his new code is typed by an LLM (see below).

So I think his “bearish”[2] take on LLMs is an interesting datapoint, and I’m putting it out there for discussion.

Some relevant excerpts from the podcast, focusing on the bearish-on-LLM part, are copied below! (These are not 100% exact quotes, instead I cleaned them up for readability.)

So you know Piotr Woźniak, who's a guy I really respect, who kinda rediscovered spaced repetition learning, built the SuperMemo system, and is the modern day guru of memory: The entire reason he's based his life around remembering things is because he believes that creativity comes from having a lot of stuff remembered, which is to say, putting together stuff you've remembered in interesting ways is a great way to be creative.

LLMs are actually quite good at that.

But there's a kind of creativity they're not at all good at, which is, you [...]

The original text contained 2 footnotes which were omitted from this narration.

---

First published:
March 6th, 2026

Source:
https://www.lesswrong.com/posts/hvun2mP2yEr4kyKWk/podcast-jeremy-howard-is-bearish-on-llms

---

Narrated by TYPE III AUDIO.

“Podcast: Jeremy Howard is bearish on LLMs” by Steven Byrnes

LessWrong (30+ Karma)