The End of Finetuning — with Jeremy Howard of Fast.ai

**Alessio** (0:11)
Hey, everyone, welcome to the Latent Space Podcast. This is Alessio, partner and CTO and resident at Decibel Partners, and I'm joined by Michael Swicks, founder of Small AI.

**Swyx** (0:21)
Hey, and today we have in the remote studio, Jeremy Howard, all the way from Australia. Good morning.

**Jeremy Howard** (0:26)
The remote studio, also known as my house. Good morning.

**Swyx** (0:31)
Nice to see you too. And I'm actually very used to seeing you in your mask as a message to people, but today we're mostly audio. Thank you for doing the very important public service of COVID awareness.

**Jeremy Howard** (0:41)
Once there was a pleasure, it was all very annoying and frustrating and tedious, but somebody had to do it.

**Swyx** (0:47)
Somebody had to do it, especially somebody with your profile, I think, it really drives home the message. So we tend to really introduce people for them and then ask people to fill in the blanks on the personal side. Something I did not know about you was that you graduated with a B in Philosophy from the University of Melbourne.
I assumed you had a PhD.

**Jeremy Howard** (1:03)
No, I mean, I barely got through my BA because I was working 80 to 100 hour weeks at McKinsey & Company from 19 years old onwards. I actually didn't attend any lectures in second and third year university.

**Swyx** (1:19)
Well, I guess you didn't need it. Oh, you're very sort of self-driven and self-motivated.

**Jeremy Howard** (1:23)
I just took two weeks off before each exam period when I was working at McKinsey. And then, I mean, I can't believe I got away with this in hindsight. I would go to all my professors and say, oh, I was meant to be in your class this semester and I didn't quite turn up. Were there any assignments I was meant to have done? Whatever. And I can't believe all of them, they basically always would say like, okay, well, if you can have this written by tomorrow, I'll accept it. So yeah, stressful way to get through university.

**Swyx** (1:51)
Well, it shows that, I guess, you min-maxed the opportunities. That definitely was a precursor.

**Jeremy Howard** (1:57)
I mean, finally, like in philosophy, the things I found interesting and focused on in the little bit of time I did spend on it was ethics and cognitive science. And it's kind of really amazing that they all come back around and those are actually genuinely useful things to know about which I never thought would happen.

**Swyx** (2:12)
Yeah, a lot of relevant conversations there. So you were a consultant for a while and then in the magical month of June, 1999, you founded both optimal decisions and FastMail, which I also briefly used. So thank you for that.

**Jeremy Howard** (2:24)
Oh, good for you. Yeah, because I had read the statistics, which is at like 90% or something, if small businesses fail. So I thought if I start two businesses, I have a higher chance.
In hindsight, I was thinking of it as some kind of stochastic thing. I didn't have control over it, but it's a bit odd, but anyway.

**Swyx** (2:40)
And then you were president and chief scientist at Kaggle, which obviously is the composition platform of machine learning. And then Analytic, where you were working on using deep learning to improve medical diagnostics and clinical decisions.

**Jeremy Howard** (2:54)
Yeah, I was actually the first company to use deep learning in medicine. So I kind of founded the field.

**Swyx** (2:58)
And even now, that's still like a pretty early phase. And I actually heard you on your new podcast with Tanishq, where you went very, very deep into the stuff, the kind of work that he's doing. Such a young prodigy at his age.

**Jeremy Howard** (3:11)
Maybe he's too old to be called a prodigy now. Ex-prodigy.

**Swyx** (3:15)
No, I think he still counts. And anyway, just to round out the bio, you have a lot more other credentials, obviously. But most recently, you started Fast.ai, which is still, I guess, your primary identity with Rachel Thomas.

**Jeremy Howard** (3:26)
Yep, who's my wife?

**Swyx** (3:27)
Doing a lot of public service there. With getting people involved in AI. And I can't imagine a better way to describe it than Fast.
Fast.ai is, you teach people from nothing to stable diffusion in seven weeks or something. And that's amazing.

**Jeremy Howard** (3:39)
Yeah, yeah. I mean, it's funny, when we started that, what was it, like 2016 or something, the idea that deep learning was something that you could make more accessible was generally considered stupid.
Everybody knew that deep learning was a thing that you got a math or a computer science PhD, or it was one of five labs that could give you the appropriate skills that you enjoyed. Yeah, basically from one of those labs, you might be able to write some papers. So yeah, the idea that normal people could use that technology to do good work was considered kind of ridiculous when we started it. And we weren't sure if it was possible either, but we kind of felt like we had to give it a go because the alternative was we were pretty sure that deep learning was on its way to becoming the most or one of the most important technologies in human history. And if the only people that could use it were a handful of computer science PhDs, that seemed like A, a big waste and B, kind of dangerous.