The Ledger, every show

“What in. Other industries we would call a bug or a hallucination. In the creative world, there are features. They're, so it's a goodness to come up with something that has not been done before, or it's a mix and match of existing things. So creative industries…”

“I think all of this will shift. In the next six, 12 months, this is all starting already, because in the same way that search changed the rules of engagement with public data, Gen AI is doing the same thing, and the companies that are behind that data are doin…”

“We've seen companies that with Seven employees have creating models that are comparable for some use cases to what OpenAI or Anthropic do.”

“These are strong words, but I think they're getting commoditized until the next big innovation comes and you allocate some more value to the model.”

“Probably the opening eyes and Anthropics are continuing their innovation, which those are effectively research companies.”

“I would bias towards incumbents that have the data. So I would say, think of all the data that a company like Google has. Or that's public data, or not semi-public, but a lot of user data, or think all the private enterprise data that a company like Snowflake …”

“I also think that commercial solutions will largely be hosted cloud services, in which case, in the same way that it is true with open source, I think it will be true about open weights.”

“I don't think that it's a mass firing happening next week. It's more incremental productivity boosts happening over the next six, 1224 months.”

“I would say don't ever compromise on talent. Don't ever say, yeah, this person doesn't have a background, but maybe Has the right intention. Just take a bet. No, I think that nothing substitutes talent.”

“So at this point, I would say the incentive should be working maybe, I don't know, A year, a couple of years from now, what you're saying becomes true.”

“If things did not change, the language models, or the models in general, would all converge towards, they're all training on the same data, and at some point it's what mix of data you use, but you'll trend towards the same answer.”

“I don't know if they're going to be able to keep all the existing revenue, but for sure they should be able to capture some amount of revenue. So I don't know exactly what would be the replacement ratios. But clearly their data is valuable. Right now it's not …”

“There are some very shallow wrappers on top of a GPT-IV. I don't place much value on them. I usually ask, hey, how long did it take you to build this? Oftentimes it's a week or two. I don't think there's a company there.”

“I do think that there are some very deep wrappers on top of GPT-IV that apply domain specific legal or other domain that I think you end up with a true way to bring GPT-IV to a given market or industry. I think those are value.”

“And now there's plenty of examples that have been run where a smaller model fine tune where a specific purpose or a specific data set produces results better than a generic model.”

“In the same way that you have a hardware abstraction layer or a cloud abstraction layer, you should have a model abstraction layer that knows how to translate a specific request that your application needs to do to a model with its intricacies or specific char…”

“I would say that for certain use cases, that's entirely true. Like if I have a UI to configure a cluster, like I don't need to know all the options. I just can specify what I want. There are many use cases where You may want a richer way to interact with data …”

“In some instances where you want a product to come out with a consistent view, as if it came from a single unified set of principles and individuals, sometimes you have to go and push for something like, Hey, this is what we're doing.”

“For the most part, no. There may be a few types of products that you might get by, but I like deep technical PMs.”

“Absolutely not. Well, there's amazing talent throughout the world. And even though the Valley has something special from the community and the ability to bounce ideas of one another, It's very clear right now. There's a lot of innovation happening elsewhere.”

“If you turn something that is a subset of the capability, but dramatically easier to use, That gets a following, and that was a very, very clear lesson learned, and I've seen it over and over, and by the way, the Snowflake story follows a big part of that jour…”

“I do think that there is the opportunity to change pretty much every single interaction between humans and computers into something that is friendlier and simpler. So yes, there's fog, and there's noise around it, but it will clear up, and at the end of the da…”

“I think it's comparable. I think it's on the scale of the internet. I think it's on the scale of mobile.”

“I think it completely correlates with data maturity. You may have heard some of us at Snowflake talk about There's no AI or gen AI strategy without a data strategy. It's not just a line. It's a truth that we strongly believe in.”

“And from that perspective, I would say financial services are at the forefront. Most of the financials have figured out for a long time how to organize data and leverage data for competitive advantages.”

“I think Gen AI has the opportunity to Turbo charge this type of translation where the language is natural language, and the answers come in natural language, but along the way, there's traditional database lookups, traditional retrieval, and has the opportunit…”

“What has happened for language models is coming for computer vision, for images. The democratization, democratization, how do you simplify it? Then there's the intersection of those true multimodal languages, which there are many of them out there, but how do …”

“Anyone that builds too tightly coupled to a given model is sort of giving up optionality for the future.”

“There are a lot of issues. Probably the most obvious one is around the Correctness and dependability of answers. If you ask folks, one of the key concerns is like, well, these models make up stuff. So that, that is the obvious one. But then there are second or…”

“What you're seeing many of us, Snowflake for sure on the list, is evolve their platforms where it's easy to bring LLMs to the data as opposed to send Large data volumes to where the LLMs are.”

“Because enterprises are worried about if they incorporate Gen AI into any of their products or services in a way that they truly depend on them, and at some point lawsuits start to fly, they're exposed, and because of those concerns, it has held back enterpris…”

“I would say that that is the world that we're headed towards, at least in the enterprise, like forget the creative side of things, but at least in the world where you need correct answers, you need to be able to attribute where things came from.”

“For example, LAMA II is very significant as a development in the industry. But they were very clear. Thou shall not use LAMA-II for training other models. Thou shall not use LAMA-II for, I think it's seven hundred million user use cases.”

“All of this is harder than people realize. The demos are awesome. The productization takes longer time.”

“When you're very successful with some positioning that comes and bites you later that you are too successful with that positioning.”

“So the core subsystem that does say clustering of data on disk I think you want to design that thing really, really well. Measure a hundred times and cut once because nobody wants their data to get corrupted or their results to be wrong if that thing is not bu…”

“It is something a little bit counterintuitive that you may put out a product faster to the market. If you just say, I don't know if we should be used this way or that way. So you just surface choices to users. And sometimes it takes longer for us to take the a…”

“I was super wrong. When Satya came into the enterprise business, this is before he was CEO, he came in in very short order and made a lot of really difficult decisions. How the org was structured how contractors were hired, how we thought about the cloud versu…”

“Every customer that I talk to these days, they're looking into doing something. They're all trying to figure out how to get started and how to get there”

“He's also such a clear thinker. He has that commonality with Satya that he becomes a clarifying force. Oftentimes if you're just picturing yourself telling Frank about a problem and a couple of options, Just in the formulation, it becomes very obvious that you…”