The Ledger, every show

“So it's interesting that we might see kind of a bad time for SaaS in post-hyper-growth tech companies. So it's still a big market, but it's not that big, because if you're not a tech company, You don't have the capabilities to reduce desk cost. If you're a hig…”

“All generations of company might be the first billion dollar companies with engineering teams of 20 people. That would be so exciting as well. That would be so great. You know, you don't have the management hurdle. You're just 20 focused people with a lot of a…”

“But if it takes five years or 10 years, then that's probably where it's gonna happen.”

“Before that, there really was a strong belief in, in scale. I think it was just the belief that the transformer was a generic enough architecture that you could learn anything, and that this was just a question of scaling.”

“I had seen GPT-IV internally at the time. It was September, 20, 22. So it was pre-chat GPT, but GPT-IV was ready since, I mean, I'd been ready for a few months internally.”

“They kind of innovated in an interesting way, which was never quite publicized, but it's that they have that kind of chain of thoughts step whenever you use a Clouds model or Sonnet model with function calling. That chain of service step doesn't exist when you…”

“I think all of that can probably scale through product and not necessarily handholding and kind of custom work with our clients eventually.”

“It's already awesome that Mistral was able to raise that much, that Toolside is able to raise that much, but it's a trickle compared to what Open Air is raising, compared to what Anthropik is raising.”

“We're trying to apply transformers to code fuzzing. So code fuzzing, you have kind of an, sorry, an algorithm that goes really fast and tries to mutate the inputs of a library to find bugs. And we try to apply a transformer to that and do reinforcement learnin…”

“When we joined at People. There were very limited number of managers, very limited number of product manager. I think it was a forbidden word at the time. So no product manager that, that function was kind of covered by engineers and managers or engine manager…”

“Because the cost will go down. So that's fine. Even if you're losing money today, you'll be winning some, I mean, earning some money tomorrow.”

“Most of the compute was going to a product called Nest, which was basically GPT-free.”

“I think he was really focused on building the vision and communicating the vision within the company, which was extremely It's extremely useful. I was personally surprised that he spent so much time, you know, working on communicating that vision and getting t…”

“The highest penetration we have is 88% daily active users within the entire employee of the company. The kind of average penetration and activation we have in our current enterprise customers is something like more like 60 to 70% weekly active.”

“I think I saw the transition from research to research plus engineering being the ingredients into building the largest and best models. But even very early on OpenAI was very open on the fact that you could be one or the other Quite fluidly and changed betwee…”

“We knew them because we were the first European users.”