YouSaid · the spoken record

Erik Bernhardsson

lines on the record: 27
first: 2025-01-09
most recent: 2025-01-09
sittings or episodes: 1
sources: podcast

Every line below is reproduced as it was said and linked to the record it came from. Nothing here is summarised or generated. Directory · Search · Corrections

“With my background at Spotify, I think who knows to me very exciting thing. I think it's still very early in sort of AI generated music. You can still hear that it's not right. It's sort of uncanny value a little bit. But Sunos, like every generation of their model is getting better and better. And first of all, music in itself tends to be sort of always like one of the first areas where you see real impact of new technologies, whether, you know, Spotify or like iTunes or Piracy or like all these things or gramophones going back, right? So I always think music is like an exciting era for that sense. It always shows that the opportunity of new technologies. And I also think like soon as like”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“There's a lot. I'm not a biased person, so this is kind of superficial, just kind of looking at our customers. But one thing I've seen a lot is actually medical imaging. Because my understanding is with modern methods, you can do very automated get millions of experiments and do automated electron microscope imaging of that. And so we've actually seen quite a lot of customers use modal for then processing and doing computer vision on those images, which is kind of cool.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“I mean, I would also point to an adjacent area, like biotech, I think, has been, computational methods have been enormously successful, right? Like if you look at protein folding in particular, but also other things like sequence alignment and things like that. And that's actually a field where we start to see a lot more usage modal as well. I feel like there's like a kind of a resurgence of computational biology. It's a really exciting field.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Mean meteorology is like something I actually think deep learning should change, right? It sort of makes a lot of sense. Deep learning should be very good at predicting turbulence and things like that. Because turbulence is actually very hard to solve a traditional physics models, right? And so deep learning should, in theory, I kind of feel like makes a lot of sense.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, I think, in my opinion, it's like, you know, look back at the golden era of physics, like the 20s and 30s and 40s. I kind of feel like it's like, it hasn't really evolved much the field. So I don't know. I would love for you to be right that there's a resurgence of new physic-based models.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“The way you think about the mode is for it. I did win the Swedish high school physics competition. I was a total math lead nerd when I was my teenagers.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Fix something, but in my opinion, it's like, no, it's good, you're just going to unlock more latent demand for more things. So I'm very bullish on software engineering.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Know if this is contrary, but like I actually think that this is just like one out of many improvements in developer productivity. And you look back at like, you know, whatever, like compilers was originally a tool that made developers more productive. And then like higher level programming languages and databases and cloud and all these things. And so I actually don't know if AI is different than any of those changes in the hindsight. And by the way, every time that's happened, It turns out like there's so much latent demand for software that actually the number of software insurance goes up. So like I feel like you look back at like, you know, last 40 years of software development, like every decade, engineers get like 10 times more productive due to better frameworks or better tooling or whatever. And it turns out actually that just unlocks more latent demand for software engineers. So I'm very bullish on software engineers. I think it would take a lot to sort of destroy that demand. I think people look at a lot of like AI is like a kind of”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Think I answered like for any company where model quality really matters unless you kind of train your own model in the end, like I feel like it's going to be hard to sort of defend the fact that you have a better solution. Because otherwise, like, what's your mode? Like, if you don't have your own model, you need to find some emote somewhere else in the stack. And that might be possible to find. It might be somewhere else for a lot of companies. But I think at least if you have your own model and that model clearly is better than anyone else, then that sort of inherently is emote in itself. I think it's more clear outside of the LM space when people are building audio, video, image models. I think if that is your core focus, like it's very clear to me, like you kind of have to train your own models in that case.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“And then, like, one thing I think a lot about is maybe the database itself be like the embedding engine, right? Like instead of you put a vector in and you, you know, you search by that vector, I think there's a lot of more native, like AI native storage solution would be you put text in, you put video in, you put image in, and then you can search by that. To me, that would be like a more sort of native AI native sort of storage solution. So that's like one line of thought that I've had is like maybe we just we're just like so early to this that like, I think it's going to take five, ten years for it to really for it to shake out.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, I feel like everyone's debating that. I don't know necessarily. I think there's a lot of, there's a case to be made that you can just stick everything into relational database and you're fine. To me, the bigger question is in the long run, like, you know, if you think about what's like an AI native data storage solution, like I don't even know if it's necessarily has the same form factors and the same interface as a database. So that's actually a bigger question that I'm more excited about is like I think people look at like vector databases and like you know whether it's relational or not the sort of shoehorn it into this like you know sort of old school model of like you put data you get data back but i don't know i i think there's like a lot of room to sort of rethink that in the age of ai and have very different like you know interaction models with that data i know that sounds a little fluffy”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“In order to train large models efficiently, you've had to really spend a lot of money and time setting up the networking. So one of the things I'm really excited about is what if you don't, you know, what if we can make training less bandwidth hungry? Because I think that would actually change a lot of the infrastructure around training, where you can now kind of tie together a lot of GPUs in different data centers and not have to have this very large data centers with Infiniband and stuff. So that's like another sort of infrastructure thing. I'm looking forward to seeing more development on.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“A very biased, but I think Modal is missing. Basically, a waiter for engineers to take code and run it. And look, I'm very bullish on code and people wanting to write code and building stuff themselves. I think outside of sort of LM space, which is like a very kind of a different world, in my opinion, I think there's always going to be a lot of applications where people want to train their own models. They want to run their own models or at least like run other models but have very custom workflows. And I just don't think there's been a great way to do that. It's like pretty painful to do that. And so I think that's pretty exciting. I think on the storage side, there's some other really exciting stuff. We haven't really touched storage at Modal. We focus very much on compute. So I'm personally very interested in sort of the vector database. Like, how's that going to evolve? I don't think anyone really knows. I'm pretty interested in more efficient storage on training data. I'm also interested in, I guess another thing I'm very fascinated by right now is training workloads.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Good question. I think if anything, it's actually been a little bit of a shift towards more like proprietary models, but like proprietary open source response. So like Flux, I think most recently has been a model that's getting a lot of attention. I'm personally interested in audio. I think Audio is like very underexplored. I think there's a lot of opportunity for open source models in that space. But I don't think we've seen anything really cool yet.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“I think they showed that infrastructure as a service makes a lot of sense. And so I think there is a little bit of resistance to adopting this multi-tenant model. But I think, you know, when you look at security and adoption of cloud, I think we have a lot of tailwinds blowing in our direction. I think security is moving away from sort of a network layer into an application layer. I think bandwidth costs are coming down. I think there's a lot of tricks you can do to minimize bandwidth transfer costs. You can store data in like R2, for instance, which has zero egress fees. It's something that I think is realistically going to mean we're going to have to push a lot, but I think there's so many benefits of this multi-tenant model in terms of capacity management that to me, it is very clearly like a big part of the future of AI is like running a big pool of compute and slicing it very dynamically.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, totally. And of course, there's also sort of security compliance aspect of this. I think it is a challenge. I look back at when the cloud came. And I remember back in 2008, 2009, and the cloud came. And my first reaction was like, how the hell, like, why would anyone put their compute in someone else's computer and run that? And I think, you know, to me, that was just like insane. Like, why would anyone do that? But over the next couple of years, I realized, actually, it kind of makes a lot of sense. And I think now even like among like enterprise companies, like there's a sort of recognition that like, yeah, actually probably our computer is more safe in the big hyperscalers. And in a similar vein, I remember talking to Snowflake back in say 2012 or something like that. And they had a sort of similar approach where they basically said, like, we're going to run databases in the cloud and it's not going to be in your, you know, or maybe in your environment, but like we're in infrastructure as a service. And I thought that was nuts. And then obviously, I think Snowflake now is a very large publicly traded company.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Our approach has always been to build a very general purpose platform and sort of, you know, in the long run, I hope to sort of that sort of manifestation will be more clear because I think there's many other products we can build on top of this now that we have the compute layer sort of becoming more and more mature.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“I think, first of all, we're cloud native, like we're just like cloud maximalists. We went all in and said, like, basically we're going to build a multi-tenant platform that runs everyone's compute. And the benefits of that are very tremendous because we could just do capacity management much better. And that's one of the ways we can offer instantaneous access to hundreds of GPUs if you need to. Like you can do these very bursty things and we just give you lots of GPUs, right? I think the other benefit or the other sort of differentiation is be very general purpose. We focus on sort of what I think as I mentioned, like high code, like we run custom code in our containers, in our infrastructure, which is a harder problem. Like containerization and running user code in a safe way is a hard problem. And then dealing with container cold start and like I mentioned, we have to build our own scheduler. We have to build our own container runtime in our own file system to boot containers very quickly. And I think so unlike many other vendors, they're only focused on, say, inference or maybe only LMs.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Then there's the training, and then there's the inference, and that is actually probably like even more things, right? Like, you know, having feedback loops where you get data and like, you know, online ranking models and all these things. And so my goal for models has always been to cover all of that stuff. And so it's interesting. You see a lot of customers now, we don't have a training product, but a lot of customers use modal for batch pre-processing. So they use model to, you know, maybe they're training a video model. So maybe they have like petabytes of video. So then they use modal actually, maybe with GPUs even to like do feature extraction. And then they train it elsewhere. And then they come back to modal for the inference. So for us to do training makes a lot of sense. And in general, I think there's a lot of makes a lot of sense to sort of build a platform where you can handle the entire sort of machine learning lifecycle end-to-end and many other things related to that, also the data pipelines and nightly batch jobs and all these things.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, totally. I mean, our goal has always been to build a platform and cover the end-to-end use cases. It just turned out that inference was, we were well positioned to focus on that as our first killer app. But my end goal has always been to make engineers more productive and focus on”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“And that's something we're really interested in right now. Like traditionally, most of Modal has always been inference, like, that's been our main use case. But we're really interested also in training. So in particular, probably focused more on these shorter, like very bursty sort of experimental training runs, not the very big training runs, because I think that's a very different market.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“The training resources you need. But for inference, especially, you don't even know how much you need, right? Like in advance, it's very volatile. And so a big challenge that we solve for a lot of customers is we're fully usage-based. So when you run things on modal, we charge you only for the time the container is actually running. And that's a massive hassle for customers' traditions, like doing the capacity planning and thinking how many GPUs. And then having the issue of like either you over provision and you're paying for a lot of idle capacity or you under provision and then you have your end of the capacity shortage, like you have degrade degradation in service. And so whereas with modal, we can handle these very bursty, very unpredictable workloads really well because we basically take all these user workloads and just run a big pool of thousands of GPUs across many different customers.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, I mean, GPUs are expensive, right? And I think it's sort of kind of as a paradox, it's like means that cloud, you know, a lot of the cloud capacity is like the only way to get it is to sign long-term commitments, which I think for a lot of startups is really not the right model for how things should be. I think the amazing thing about the cloud was always to me that you have on-demand access to whatever many CPUs you need. But for GPUs, the main way to get access has been over the last few years due to the scarcity has been to sign long-term contracts. And I think fundamentally, that's just not how startups should do it, right? And I kind of get it has been sort of supply-demand issues. But just looking at the CPU market, the fact that you have instant access to thousands of CPUs if you need it, my vision has always been this should be the same thing for GPUs. And that means, you know, especially as we shift more to inference, I think for training, it's been sort of a less of an issue because you can sort of just like make use of.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Like, hey, actually, this looks kind of cool. Like, you have GPU access, it's very easy to, you know, you have to think about spinning up machines and provisioning them. So that was like our first sort of killer app is just doing Gen AI in a serverless way with the focus of diffusion models. Now we actually, we have a lot more of a different modalities. A lot of usage is still like text to image, but we also see a lot of audio and music. So one example of a customer I think is super cool building really amazing stuff is Suno, which does AI generated music. So they run all their inference on modal very large scale. There's a lot of customers like that sort of dealing with building cool gen AI models, in particular, I would say, in the modalities of audio, video, image, and music, stuff like that.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“So where do infrastructure as a service? So which means on one side we run a very big compute pool, like thousands of GPUs and CPUs. And we make it very easy to get, you know, if you need 100 GPUs, we can typically get you that within seconds. So sort of one big multi-tenant pool, which means like capacity planning is something we kind of take, you know, it's something we solve for customers. They don't really need to think about reservations. We always provide a lot of on-demand GPUs. On the other side, there's Python SDK that makes it very easy to build applications. So the idea is like you write code, basically like functions in Python. And then we take those functions, turn them into serverless functions in the cloud. We handle all the containerization and all the infrastructure stuff. So you don't have to think about all this sort of Kubernetes and Docker and stuff. The real killer app, as it turns out, like we started this company pre-gen AI, but as it turns out, the main thing that really started driving all the traction was when stable diffusion came out. And a bunch of people came to us.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“So I started looking into, first of all, just like what are the challenges with data AI, machine learning infrastructure? And start to think about from like a developer productivity point of view, what's a tool I want to have? And realize a big sort of challenge is like working with the cloud is arguably kind of annoying. And like as much as I love the cloud for it power that gives me, and I've used the cloud since way back 2009 or so, it's actually pretty frustrating to work with. And so in my head, I had this idea of like, what if you make cloud development feel almost like as good as local development, right? Like had this like fast feedback loops? And so I started thinking about like, how do we build that and realize pretty quickly, like, well, actually, we can't really use Docker and Kubernetes. We're going to have to throw that out and probably going to have to build our own file system, which we did pretty early and build our own scheduler and build our own container runtime. And so that was basically the two first years of models, just like laying all that foundational infrastructure layer in place.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT
“Yeah, this started as Bonifi a long time ago, 2008, and it's been seven years there. And yeah, I built a music recommendation system. And back then, there was like nothing really in terms of data infrastructure. Hadoop was like the most modern thing. And so I spent a lot of time building a lot of infrastructure. In particular, I built a workflow schedule called Luigi that basically no one uses today. I built a vector database that called Illinois that for a brief period, people used, but no one really uses today. So I spent a lot of time building a lot of that stuff. And then later at Better, I was the CTO and thinking a lot about developer productivity and stuff. And then during the pandemic, I took some time off and started hacking on stuff. And I realized I always wanted to build basically a better infrastructure for these types of things, like data AI, machine learning. So pretty quickly, I realized this is what I wanted to do. And that was sort of the genesis of model.”
2025-01-09 · No Priors · Erik Bernhardsson on Creating Tools That Make AI Feel Effortless · IDENTIFIED FROM THE TRANSCRIPT