Jonathan Siddharth

“If you can solve coding, tool use, reasoning, and multimodality, you have the keys to superintelligence. Those are the building blocks. If you can solve those four, you can automate anything that a human does in front of a computer, and it'll give humans super…”

“Now, I think in the limit over the next decade, every human might run seven to eight companies as these, as the loop from idea to, I mean, as you can go from prompt to company in hopefully like a single step over the next decade.”

“For example, I have a project at Turing that I run. I have a few agents running around to help me run Turing. The way I improve that code base is to also have an agent suggest to me, how should I improve the code base and to do it? So it's in a self-improvemen…”

“So on one hand, the models are becoming agentic. And in theory, if the models have access to the right sources of data, You kind of don't need software in the middle. The models can do it end to end.”

“The bottoms up pincer is every human can now write software. My EA wrote software because I have a crazy schedule. Like I work a lot. I travel a lot. Like I'm always on. So it creates a lot of work. So my EA wrote Software to manage her EA team, and that softw…”

“I mean, I have a system at Turing that helps me run Turing, and this is a system that I built on top of one of the frontier models, and I didn't have to fine tune it. Like, all I had to do was intelligent management of context, memory, access to the right tool…”

“Pick a market with weak competition. Like ideally not competition that's other big tech companies or other AI labs. Like don't pick a market with Weak competition or analog competition. For example, Uber competed with taxi companies, analog competition, not a …”

“I feel like most of humanity's most challenging problems are Intelligence constrained in terms of us being able to throw more intelligence at it to solve the problem.”

“It's innings one, and I believe in slow takeoff. I'm sorry to pour cold water on all the AI doomers that might be listening to this, but we are not in a rapid takeoff scenario. I believe in slow, steady takeoff for AGI and eventually super intelligence.”

“The glimpse of the future that I see is that all knowledge work is going to be automated. If a human's job involves looking at a computer, analyzing what's on the screen, using different tools, using a keyboard and a mouse, it's going to be automated. It's onl…”

“In back office automation, it'll probably be very slow, and it'll, it'll probably be the upstarts that'll do things well. I think the change management will be too slow. But I'm optimistic about front office, especially in financial services, life sciences, ph…”

“I think one moat will be data-driven feedback loops.”

“I feel like the models have touched reality in consumer. We haven't yet touched reality in enterprise. And the only way we'll improve is by deployment.”

“And there's a very significant model capability overhang. By that, what I mean is the models are capable of X, but what we are getting out of the models is X minus Delta.”

“I think it'll, I think there'll be more software engineers because if you define a software engineer as somebody who's capable of building a software product to solve a real problem, that pool of builders is going to expand way beyond people who've graduated w…”

“We'll have some type of a device that is, that we'll carry that's always on and processing multimodal tokens.”

“I used to believe that to build a Enduring, valuable company. You hire a strong, ah, exec team and operate with a lot of leverage. Basically hire strong people, hire great people and get out of the way. I used to believe that. Now I believe you hire great peop…”

“Now, for these verifiable domains like coding and math, instead of doing reinforcement learning with human feedback, you can do reinforcement learning. Because you can automatically check when you got the correct answer or not in these verifiable domains. And …”

“I don't think rapid takeoff is how things will unfold. I think it's going to be steady, continuous progress. Every step of the way, we're going to keep moving forward and it's going to be great, and it's great for a few reasons.”

“I feel like the self-driving car industry did a lot of damage to AI in one particular way, which is it because with self-driving cars, 99% accuracy is not enough. That, that last one percent really matters. But with a lot of AI systems, if you're automating th…”

“To solve real world enterprise workflows, you need, ah, real world enterprise data, and that data doesn't exist on the internet.”