The Ledger, every show

“I think we have AGI. I think we have artificial general intelligence. We really have it. We absolutely have it. It's like, Anyone who says we need to get to AGI, that's like, it's a, it's false premise to start with. We already have AGI.”

“Like I think keyboards are kind of basically going to disappear. Completely. We haven't actually nailed speech. I know it feels like we have, but we haven't, because you're still using your keyboard. So as long as you're using a keyboard, we haven't nailed spe…”

“I kind of think all the benchmarks are bullshit, and so all these, so all the LLM benchmarks, here's how it works.”

“This PLG thing is just overrated for the kind of business we have in the kind of market we are in.”

“In fact, I think open source has the potential to replace pretty much any software that's, Any proprietary software that exists on the planet today is, you know, in a really vulnerable state in the sense that it can be disrupted by an open source version, righ…”

“Any proprietary software company out there is ripe for disruption by an open source competitor.”

“I think if you have a really, really good sales leader on the enterprise software side, they should be able to get you to zero to five million revenue or so, regardless almost, of your product.”

“Yeah, look, I think the LLM is a commodity. People are not saying that, but it is a commodity. Like, and, you know, when I took econ classes, commodity was when it's interchangeable. Like, you can get gas from this gas station, or you can get gas from that gas…”

“The biggest problem is that you bake a model, and that's where it's learned everything it needs to learn, and then you freeze it, and then you launch it, and then maybe you give it some context, but that's it. It's frozen. So therein lies the problem that, you…”

“We have the AGI we need. Let us just focus on solving the actual problems inside the organizations, and I think we can already, that's enough to automate a lot of the tasks and get huge economic value out of it. We don't actually need superintelligence for tha…”

“But I do think most of the value will accrue to the apps. So it's kind of, and I think that's common sense. It's just, I just don't know which apps.”

“Hey, you can do whatever you want. You can sell. You're going to make a lot of money and you'll be super successful in life. But you know, if you're like me, you're going to look back the rest of your life thinking, you know, I missed that one shot. That was t…”

“But the problem was that you know, as it is often with open sources that you just everyone's just downloading the open source version. Actually your biggest enemy is your open source project.”

“They'll do well in their own archetype. When they have to step outside of their own archetype, they make a mistake. They hire people that are like their own archetype in other roles where that could be lethal.”

“There is one really good company that well, one really successful company that we never acquired. And I always vetoed it whenever it came up because I just think that the quality of their employee base is not great. And I didn't want it to dilute Databricks.”

“I don't think anyone's getting a hundred million dollar offers. You know, I mean, yes, there is like, One, you know, character that AI and so on, but I didn't think it's actually true.”

“PLG is something that we had tried very hard and it didn't work for us. Like, and actually one of our biggest failures was PLG at Databricks.”

“One of the things that's really interesting that's happened in the sort of brains of the CEOs and the boards is that they realize Maybe I can beat my competition. Maybe this is the kryptonite that will help me kill my enemy. I have the data with generative AI.…”

“And there you're better off if you have a good data set to train, you can train a smaller model. The latency will be faster to use it later, and it will be cheaper to use it later, and yes, you can have absolutely accuracy that beats the really large model, bu…”

“So we bought Mosaic. I did not unleash our sales force and go to market of 3000 people. To sell the thing that we bought because we just can't satisfy the demand. Like there's not enough GPUs.”

“So I think it's a little bit like right now like that. Who has the largest LLM? Obviously whoever can build the largest one that can train it the most obviously will own all of AI and all the future of humanity. But just like the internet, someone will show up…”

“If the original Llama was never released, What would the state of the world and our view of AI be right now? We would be way further behind, right? And A, it was a big model you know, by what existed in open source and it was open sourced. And both of those th…”

“MMLU is just a multi-choice question that's on the web. Ask a question. Here's, is the answer A, B, C, D, and then it says what the right answer is. And it's on the web. You can deliberately train on it and create an LLM that crushes it on that. Okay. Or you c…”

“Once you have reproduction and, you know, the building of new ones automatically once you crack the code on that loop, yes, then I think we're fucked, but we're very far away from that.”

“I disagree with that. I think from then on, it's you owe them. You're the one that made the mistake of hiring them to be as generous as possible within reason.”

“So the business models were not robust in the sense that really, it was really selling services masqueraded as software.”

“What they were doing is they were taking those algorithms from the seventies that do not work, but they were applying orders of magnitude, more data to it. So a lot of data on modern hardware, and they were getting superhuman results.”

“You don't get to pick your channel. You can, you don't get to say, oh, I want my ASP to be 50 K or 60. That's not your choice. You have a product. You have a market. If it has fit, you have to find the right channel to connect those two.”

“So our secret sauce is look at an enterprise problem, figure out what that is, understand it deeply by being really customer obsessed, bring the problem back, have the innovators, the PhDs that know how to solve these problems. Solve the problem. Iterate quick…”

“We're going to host open source software in the cloud, but the difference is we'll create open source software. That way we get competitive advantage with respect to anyone else who would want to do the same thing, right? Otherwise anyone can pick up any open …”

“So slowly what's happening is that the open source realm An ecosystem is emerging where you can do all of your analytics in this lake house paradigm, and you don't, eventually it will be the case that you will not need all these other, you know, proprietary ol…”

“It's certainly going to coexist, and it already coexists with Databricks in probably 70% of the accounts we're in.”

“So you actually, or chart wise should separate those out because otherwise what happens when you're successful is that the former gets all of the resources because the big enterprises have infinite demand for your for the things that you're doing.”

“Oftentimes, the valuation doesn't actually matter that much. People try to get another 10 or 20% higher valuation than what they have on the table right now, but you're only raising 10% of that valuation or something like that, so actually it's only gonna make…”

“The recommendation, actually, that we got was hire first the head of marketing, because, you know, the conventional wisdom in Silicon Valley is you need a marketing person to create the story and write the marketing material, otherwise the salesperson that you…”

“Rolling up your sleeves and doing it yourself is actually an anti-pattern at our face, because that means you're solving it in an ad hoc way.”

“High growth companies actually mostly outgrow most people's careers. The company's changing so fast that you can't in your career keep up with it. You need to change too fast to keep up with it.”

“Pretty much everything that humans are doing in these offices today, that's very repetitive, and it's not extremely creative, can be automated. So I think the impact of data science and AI is going to be massive, definitely in the trillions of dollars, in term…”

“I think automating, like, customer service and support is a little bit overhyped.”

“So like in, in these BD deals there always has to be a give and get that actually is kind of commensurate. And this is why most of these deals fall apart and they don't work. There has to be something that you as a small player can give that they don't have. U…”

“The way to think about it is your market cap divided by number of employees. That's how much money you can give away in terms of dilution.”

“It's when you're asking other people, what do you think? Or when you're starting to have the thoughts of like, is this the right person or is it not the right person? You're done.”

“And we could not do a deal that was bigger than 20 30 K. It was just impossible.”

“We thought there was one example of a good one, which was Red Hat, but there weren't many other examples that were doing well, and now we've seen Red Hat, you know, also, you know, did not survive as an independent company.”

“And I think this is a secular trend. So in a couple of years, I think it's going to be an absolute requirement. Like I don't want to, if your software only works on this cloud, I'm not sure I'm just going to be in this cloud.”

“They don't want to talk openly about it, but most of those vaccine teams behind the scenes built basically what we call the lake house. We stole all your data, store all your data and do AI on it. And it was really used for these sort of vaccine development bo…”

“The people in Amplab that were doing machine learning, the math folks, they had to use this thing called Hadoop, which was just terrible.”

“On the channel side, the mistake with it is we really early on, we're really big believers in this product led growth. We said, you know, we're going to build this beautiful simplified product that we now have. We put it online and it's going to be cloud based…”