Jeremy Howard
23 statements across 3 episodes · 7 bullish · 10 bearish · 2 people on the record · first statement Oct 20, 2023 by Jeremy Howard · said 8 times in 7 episodes since 2024 · across every show →
On the record as a speaker too: Jeremy Howard's record, appearances and statements → this page counts the times other people say the name.
Mentions by year
brought up most by Shawn Wang (3), Alessio Fanelli (2), Kyle Corbitt (1)
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2025 5 mentions in 5 episodes 1 per episode
- Why RL Won — Kyle Corbitt, OpenPipe (acq. CoreWeave)
- Information Theory for Language Models: Jack Morris
- Why Every Agent needs Open Source Cloud Sandboxes
- Agent Engineering with Pydantic + Graphs — with Samuel Colvin, CEO of Pydantic Logfire
- 2024 Year in Review: The Big Scaling Debate, the Four Wars of AI, Top Themes and the Rise of Agents
- every mention in 2025, scene by scene →
2024 3 mentions in 2 episodes 2 per episode
Everything said about Jeremy Howard, oldest first
Oct 20, 2023 negative
Howard: AI research went backwards for years pursuing zero-shot learning
“And so I actually feel like we kind of went backwards for years and not to be honest, I mean, I'm a bit sad about this now, but I kind of got so disappointed and dissuaded by like, It felt like these bigger lab, much bigger labs, you know, like fast.ai had onl…”
Oct 20, 2023 negative
Howard: Focusing on massive compute infrastructure is a distraction in AI
“It might seem like a recent thing, but actually throughout my 30 years in data science, the attention's always been on, you know, the big iron results. So when I first started, everybody was talking about data warehouses, and it was all about Teradata, and it'…”
Oct 20, 2023 neutral
Oct 20, 2023
Oct 20, 2023 negative
Howard: NLP researchers unanimously insisted transfer learning would never work for language
“Like, the reason it took me so long to try it was because I asked all my friends in NLP if this could work, and everybody said, no, it definitely won't work. It wasn't like, oh, maybe. Everybody was like, it definitely won't work. NLP is much more complicated …”
Oct 20, 2023
Oct 20, 2023 negative
Aug 17, 2024 neutral
Aug 17, 2024 negative
Howard: Non-profit boards cannot control commercial entities with equity-compensated staff
“This didn't make sense to have like a so-called non-profit where then there are people working at a commercial company that's owned by or controlled nominally by the non-profit where the people in the company are being given the equivalent of stock options. Li…”
Aug 17, 2024 positive
Howard: Training stages form a continuum allowing deep modification of pre-trained models
“Sorry, it wasn't the end of fine-tuning, but more that we should treat it as a continuum, and we should have much higher expectations of how much you can do with an already trained model. You can really add a lot of behavior to it. You can change its behavior.…”
Aug 17, 2024 positive
Howard: Developers should distribute merged adapters rather than merged models
“To explain, it's not that you shouldn't merge models, it's that you shouldn't be distributing a merged model. You should distribute it a merged adapter. 99% of the time. And actually often, one of the best things happening in the model merging world is actuall…”
Aug 17, 2024 positive
Aug 17, 2024 neutral
Howard: Pre-training data mixes should be continuous per-batch functions, not discrete phases
“So the point at which they're doing proper continued pre-training is the point at which that becomes a continuum rather than a phase. So the only difference with what I was describing last time is to say, like, oh, they should, you know, There's a function or …”
Aug 17, 2024 positive
Howard: Public Benefit Corporation status allows founders to reject hostile buyouts
“If you're not a public benefit corporation, Then somebody can come along and offer to buy you with a stated description of, like, turning your company into the thing you most hate, right? And if they offer you more than the market value of your company and you…”
Aug 17, 2024 negative
Howard: Cursor and VS Code shoehorn AI into legacy software paradigms
“It's like a convenience over the top of this incredibly complicated system that full-time, sophisticated software engineers have designed over the past few decades in a totally different environment as a way to build software, you know. And so we're trying to,…”
Aug 17, 2024 positive
Howard: 80% of top unique creators have unconventional or non-mainstream backgrounds
“Like, 80% of the time, I find out the person has a really unusual background. So, like, often they'll have, like, either they, like, came from poverty and, like, didn't get an opportunity to go to good school, or they, like, you know, had dyslexia and, you kno…”
Aug 17, 2024 negative
Howard: Corporations are sociopathic by design due to fiduciary duty
“Companies are sociopathic, like, by design. And so the alignment problem, as it relates to companies, has not been solved. Like, companies become huge, they devour their founders, they devour their communities, and they do things where even the CEOs, you know,…”
Aug 17, 2024 neutral
Aug 17, 2024 bullish
Howard previews AI Magic, his upcoming dialogue engineering system
“So, I've created a new approach. It's not called prompt engineering. It's called dialogue engineering. And I'm creating a system for doing dialogue engineering. It's currently called AI Magic. I'm doing most of my work in this system, and it's making me much m…”
Aug 17, 2024 negative
Howard: Training AI models from random weights is almost never justified
“If you're training for random weights, you better have a really good reason, you know, because it seems so unlikely to me that nobody has ever trained on data that has any similarity whatsoever to the general class of data you're working with, and that's the o…”
Oct 2, 2025 negative
Howard: Correcting LLM errors in chat history degrades subsequent model answers
“The autoregressive nature of language models means that if they make a mistake, and you correct it, and then say, no, that was a mistake, please do it this way instead. The more often you do that, the worse the dialogue answers get. Because it's in the trainin…”
Oct 2, 2025 positive
Oct 2, 2025 negative
Jeremy Howard: AI coding should prioritize human learning over vibe coding
“We want to make sure at the end of building something, two things have happened. The first is you understand every line of code fully, why it's there, what it does, and that you've learned from the process. So at the end of this process, you're a better develo…”