fast.ai

also referred to as: fast ai

8 statements across 2 episodes · 4 bullish · 3 bearish · 1 people on the record · first statement Oct 20, 2023 by Jeremy Howard · said 40 times in 6 episodes since 2023 · across every show →

Mentions by year

brought up most by Jeremy Howard (15), Swix (Shawn) (4), Suhail Doshi (2), Shawn Wang (1), Robert McCloy (1)

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00131.5253202320242025episodesmentions per episode
2025 2 mentions in 2 episodes 1 per episode
2024 16 mentions in 3 episodes 5 per episode
2023 22 mentions in 1 episode

every mention, scene by scene, with the transcript →

Everything said about fast.ai, oldest first

Oct 20, 2023 negative
Opinion
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…”
Jeremy Howard Oct 20, 2023 ▶ 19:29 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 positive
Insight
Howard: Rapid LLM race created massive technical debt and optimization opportunities
“There's a whole lot of technical debt everywhere, you know, nobody's really figured this stuff out because everybody's been so busy building what we know works as quickly as possible. So, yeah, I think there's a huge amount of opportunity to, you know, I think…”
Jeremy Howard Oct 20, 2023 ▶ 1:14:48 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 neutral
Disclosure
Howard: Fast.ai was never more than two people and is now solo
“That's just one of, like, three things we do, is the course, you know, and it's only ever been at most two people, either me and Rachel, or me and Sylvain. Nowadays it's just me.”
Jeremy Howard Oct 20, 2023 ▶ 28:31 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 negative
Insight
Jeremy Howard: AI research artifacts should be software and courses, not papers
“To me the main artifact shouldn't be papers, because papers are things read by a small exclusive group of people, you know, to me the main artifacts should be, like, something teaching you people, here's how to use this insight, and here's software you can use…”
Jeremy Howard Oct 20, 2023 ▶ 32:00 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 positive
Assertion Partly supported
Jeremy Howard: Fast.ai won Stanford's DawnBench in 10 days using progressive resizing
“We only found out about this 10 days before the competition finished but, you know, we basically got together an emergency bunch of our students, and Rachel and I, and sat for the next 10 days, and just tried to crunch through, and Try to use all of our best i…”
Jeremy Howard Oct 20, 2023 ▶ 34:21 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 positive
Assertion Not checkable as stated
Howard: Tesla and OpenAI Scholars used Fast.ai courses for deep learning training
“Andre Capathy grabbed me when I saw him at NeurIpes a few years ago, and he's like, I have to tell you, thanks to the fast AI courses, when people come to Tesla, and they need to know more about deep learning, we always send them to your course. And the OpenAI…”
Jeremy Howard Oct 20, 2023 ▶ 28:15 The End of Finetuning — with Jeremy Howard of Fast.ai
Oct 20, 2023 positive
Insight
Howard: Transfer learning reduces deep learning compute and data needs
“There's this thing which nobody knows about, nobody talks about, called transfer learning, where you take somebody else's model where they already figured out, like, how to Detect edges, and gradients, and corners, and text, and whatever else, and then you can…”
Jeremy Howard Oct 20, 2023 ▶ 7:53 The End of Finetuning — with Jeremy Howard of Fast.ai
Aug 17, 2024 negative
Insight
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…”
Jeremy Howard Aug 17, 2024 ▶ 2:54 Answer.ai & AI Magic with Jeremy Howard
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