Anthropic’s cofounder said the key to advancing AI isn’t rocket science — it’s asking the obvious stuff nobody wants to say out loud.
“It’s really asking very naive, dumb questions that get you very far,” said Jared Kaplan at a Y Combinator event last month.
The chief science officer at Anthropic said in the video published by Y Combinator on Tuesday that AI is an “incredibly new field” and “a lot of the most basic questions haven’t been answered.”
For instance, Kaplan recalled how in the 2010s, everyone in tech kept saying that “big data” was the future. He asked: How big does the data need to be? How much does it actually help?
That line of thinking eventually led him and his team to study whether AI performance could be predicted based on the size of the model and the amount of compute used — a breakthrough that became known as scaling laws.
“We got really lucky. We found that there’s actually something very, very, very precise and surprising underlying AI training,” he said. “This was something that came about because I was just sort of asking the dumbest possible question.”
Kaplan added that as a physicist, that was exactly what he was trained to do. “You sort of look at the big picture and you ask really dumb things.”
Simple questions can make big trends “as precise as possible,” and that can “give you a lot of tools,” Kaplan said.
“It allows you to ask: What does it really mean to move the needle?” he added.
Kaplan and Anthropic did not respond to a request for comment from Business Insider.
Anthropic’s AI breakthroughs
Anthropic has emerged as a powerhouse in AI‑assisted coding, especially after the release of its Claude Sonnet 3.5 model in June 2024.
“Anthropic changed everything,” Sourcegraph’s Quinn Slack said in a BI report published last week.
“We immediately said, ‘This model is better than anything else out there in terms of its ability to write code at length’ — high-quality code that a human would be proud to write,” he added.
“And as a startup, if you’re not moving at that speed, you’re gonna die.”
Anthropic cofounder Ben Mann said in a recent episode of the “No Priors Podcast” that figuring out how to make AI code better and faster has been largely driven by trial and error and measurable feedback.
“Sometimes you just won’t know and you have to try stuff — and with code that’s easy because we can just do it in a loop,” Mann said.
Elad Gil, a top AI investor and No Priors host, concurred, saying the clear signals from deploying code and seeing if it works make this process fruitful.
“With coding, you actually have like a direct output that you can measure: You can run the code, you can test the code,” he said. “There’s sort of a baked-in utility function you can optimize against.”
BI’s Alistair Barr wrote in an exclusive report last week about how the startup might have achieved its AI coding breakthrough, crediting approaches like Reinforcement Learning from Human Feedback, or RLHF, and Constitutional AI.
Anthropic may soon be worth $100 billion, as the startup pulls in billions of dollars from companies paying for access to its models, Barr wrote.
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