Databricks

“It's one thing to do like a single monolithic push to create a, Training data set like that, or an evaluation corpus, but I think it's another to have a repeatable process, and a lot of that, I think, realistically is pretty unsexy, like, people management wor…”

“It's kind of impossible if you're doing training to not go all the way through the entire stack, regardless of what happens. Like somehow I'm still chatting with cloud providers about power contracts, even though the whole point of dealing with the cloud provi…”

“Like the most successful scientists I see are the ones who are okay operating in a world where everything's going to be broken. And yet we can still cobble things together and make something interesting happen.”

“And so actually the networking part of DPRX was the single hardest thing. I think of the entire process, just get MOE training, working at scale across a big cluster.”

“Think we're running on like six or seven different clouds right now.”

“We've had some surprisingly good luck with this. We just released a paper on it. The details matter a lot and it really matters what you're trying to do with the model. But it's been quite effective for us depending on the setting. And certainly when we're thi…”

“Releasing models open source is not our day-to-day bread and butter. It's kind of a fun reward that we get to do sometimes when we have something really cool to share and a little bit of time and spare GPUs in our hands. But for the most part, everything is go…”

“Is that we finally released our text image model which has been a year in the making through a collaboration directly with Shutterstock.”

“So a lot of models have had Shutterstock data incorporated into them, but this is the only model I know of so far where it was, you know, exclusively and specifically trained just on the vanilla Shutterstock data. There was nothing else mixed in. You know, we …”

“The DBRX small model that we still haven't released yet was called Abra. DBRX was called Kadabra and, you know, there's a third Pokemon in that evolution and that's all I'll say for now.”

“I don't think I have a single customer that's asking to, you know, have AI solve abstract reasoning problems.”

“Like it's, you know, text to SQL is still, or like having a model be able to make SQL calls in the backend is actually like one of the single most useful things for my customers. It sounds really boring. Models are really good at it and it moves the needle day…”

“So the venture funding, there's 50 professors and PhDs, the top names like Jeff Dean and the top faculty at Berkeley and Stanford and my co-founders of Databricks and Perplexity who've invested in the fund.”

“It has been probably the best investment the American popular public has ever made. Thousands X return on their investments. I mentioned Google earlier, Databricks, all these researchers came from NSF funding”

“Another way to think about it is like, imagine, you know we, our thing wasn't open. We had some kind of agent hosting thing, but it's not open. And then there is an open one. If you're, which one's gonna win in the long run? So like here, because there is this…”

“A lot of coding agents today have very basic things like you can tell me which tool patterns I'll allow or disallow or whatever. It's like yes or no, but that puts you in a very tough spot. So just as an example, like, should my agent be able to read, you know…”

“They use that to build a model. Like a machine learning model, not an L, a machine learning model. Machine learning model basically can very, very quickly tell us how any algorithm and how any implementation will perform for any specific type of queries with v…”

“So we, on the analytics side, I think we launched Maybe 50 or sixteen million virtual machines a day across all three clouds, so which are one of the biggest compute orchestrators out there. Stuff for sure for CPU compute.”

“It turned out that, you know, it's easier to go from that bod thing that's really good at the scale and ingesting and super low cost and create versions in it that have the speed and features of the, you know, super easy to use, like smaller data for business …”

“And as a matter of fact, once you transcode the data compresses better. So from those services writing to, for example, S three or other data lake, like object stores, you can actually write them faster because now they are now smaller. So there's no. Overhead…”

“One of the challenges I think we probably see, and maybe many newer generation companies are seeing is, so tech companies are very, very different from non-tech companies or traditional enterprises. And if you optimize everything just for tech companies, you m…”

“One, so, I mean, one of the reasons to open source something is if you think it's a layer that will actually, there'll be some network effect. It'll benefit from many people collaborating on it.”

“HTAP wants to build a single engine for both. We think you can get 99% of what you need by unifying the storage and just have a single storage layer.”

“We have a really great dev info team. They built something called Isaac that's basically like a wrapper on cloud code and codex and let's you use them either on the web and like, Sandboxes or just on your dev machine or on your laptop or whatever.”

“I think we had like five or six different agentic frameworks built by every different team. They do all do more or less the same thing.”

“It's unlimited, but we do you know, we use our own product to like analyze the traces and stuff, and we have a team that's, you know, looking to optimize and to see if anyone's doing something weird.”

“I think the industry has a sense of, hey, maybe if you overfit to like one or two customers, it's going to be really bad for you. But I think the downside overfitting is much smaller than the upside itself. And if you sort of try to be too ambitious and boil t…”

“What people eventually run into, It's kind of a question of a unification and consolidation is, hey, do you really need to chop all of this into different pieces and work with so many different vendors and platforms in order to get like a very simple visualiza…”

“We had a lot of engineers building, you know, their own Vibe coding setup. But then the other thing they all said is like, Hey, I built something that's amazing for me. But like no one else on the team can use it because I don't have a server to collaborate. A…”

“Our team built this document sort of vision model that takes a page and gives you back a nice JSON with all the components. And it's very competitive. It's like probably like a hundred X cheaper than those frontier models and still better.”

“Actually, every single database engine out there, especially on the analytics side, are kind of a decade old. Pretty much everything that had reasonable traction are about a decade old.”

“Even though we did launch open source model DBRX, and, you know, we went up to, like, sort of above the LAMA-R III scale, we decided that we really want to focus on, there'll be so many people releasing models, and instead of doing the general model where, lik…”