Noam Shazeer: How We Spent $2M to Train a Single AI Model and Grew Character.ai to 20M Users | E1055
Noam Shazeer (guest), Harry Stebbings (host)
In this episode of The Twenty Minute VC, featuring Noam Shazeer and Harry Stebbings, Noam Shazeer: How We Spent $2M to Train a Single AI Model and Grew Character.ai to 20M Users | E1055 explores noam Shazeer on Scaling Character.ai, Cheap Training, and Billion Use-Cases Noam Shazeer, co‑founder and CEO of Character.ai, discusses how his 20 years at Google shaped his philosophy of building full‑stack, consumer-first AI products that can serve billions of people. He explains why Character.ai is pursuing a broad, horizontal use case—“a billion users inventing a billion use cases”—rather than narrow verticals, and how emotional support, entertainment, and companionship emerged organically as core user behaviors. Technically, he outlines how modern neural language models work, why compute budget (not just data or model size) is the primary constraint, and how Character trained a flagship model for roughly $2M in compute. He also shares views on AI’s future, hallucinations as a feature for some applications, privacy, open vs. closed ecosystems, and his personal philosophy on responsibility, religion, and choosing usefulness over short-term fun.
Noam Shazeer on Scaling Character.ai, Cheap Training, and Billion Use-Cases
Noam Shazeer, co‑founder and CEO of Character.ai, discusses how his 20 years at Google shaped his philosophy of building full‑stack, consumer-first AI products that can serve billions of people. He explains why Character.ai is pursuing a broad, horizontal use case—“a billion users inventing a billion use cases”—rather than narrow verticals, and how emotional support, entertainment, and companionship emerged organically as core user behaviors. Technically, he outlines how modern neural language models work, why compute budget (not just data or model size) is the primary constraint, and how Character trained a flagship model for roughly $2M in compute. He also shares views on AI’s future, hallucinations as a feature for some applications, privacy, open vs. closed ecosystems, and his personal philosophy on responsibility, religion, and choosing usefulness over short-term fun.
Key Takeaways
Launch general-purpose AI directly to consumers and let use cases emerge.
Shazeer argues that when technology is versatile and simple to use, the best strategy is to ship to as many people as possible and observe what they do with it, rather than pre-picking narrow verticals.
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Versatility and usability can coexist in AI products if you design around language.
By framing the core problem as next-word prediction on massive text corpora, Character. ...
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Compute budget is the main bottleneck in building smarter models, more than raw data.
Shazeer emphasizes that the critical variable is how much computation you can afford to spend (model size × training duration), noting Character’s current flagship model cost about $2M in compute and could be substantially improved with more and better hardware.
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User-generated interaction data is valuable but must be handled with strict privacy safeguards.
Character. ...
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Hallucinations can be a feature for some applications, not always a bug.
Because Character. ...
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Startups can move faster than big tech, especially on brand‑risky, new consumer AI experiences.
Shazeer believes Character. ...
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Focus on what is truly your responsibility, and optimize for usefulness over fun.
Drawing from his personal life and faith, Shazeer says he evaluates roles like CEO not by enjoyment but by impact—choosing positions where he can most effectively push AI technology forward.
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Notable Quotes
“I like this sort of motto of a billion users inventing a billion use cases.”
— Noam Shazeer
“We consider [hallucinations] a feature… the use cases that emerge first will be ones for which hallucination is a feature.”
— Noam Shazeer
“You have this sequence of words… guess what the next word is. That problem is called language modeling.”
— Noam Shazeer
“This technology is just gonna get way, way smarter. We’re at a sort of Wright Brothers first airplane kind of moment.”
— Noam Shazeer
“It wasn’t a matter of, ‘Am I going to be having more fun being a startup CEO?’ It’s more like, ‘I want to push this technology forward. What’s the best thing I can do?’”
— Noam Shazeer
Questions Answered in This Episode
How can platforms like Character.ai better distinguish and signal when users should not rely on AI for factual or clinical advice, given the intentional tolerance for hallucinations?
Noam Shazeer, co‑founder and CEO of Character. ...
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What governance, technical safeguards, or auditing systems would be needed to safely use companion-style AI in sensitive areas like mental health support or youth interactions?
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As compute becomes cheaper and more widely available, how will that shift the balance of power between frontier labs, startups, open-source communities, and individual researchers?
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In a world of increasingly capable conversational agents, what concrete product mechanisms could actively strengthen, rather than substitute for, human-to-human relationships?
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If the most important AI applications haven’t been invented yet, how should founders and investors decide what to build now without overfitting to today’s obvious use cases?
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Transcript Preview
What we hear a lot more from users is, "I'm talking to a video game character who's now my new therapist, and this makes me feel better." (laughs) We- we had no idea that was going to go on.
Welcome to 20VC, the show that interviews the best founders and investors in the world. And today, we're joined by one of the foremost experts in AI and NLP, natural language processing, Noam Shazeer. Noam is the co-founder and CEO at Character.AI, a full stack AI computing platform that gives people access to their own flexible superintelligence. Before we dive into the show today, it would make such a difference, if you like 20VC, if you would click the Subscribe link beneath this video. (electronic music) Noam, I'm so excited for this. I heard so many great things from many different people. Eric Schmidt, Sarah Wang, Prajit. So thank you so much for joining me today.
Thank you. Yeah, great to be on, Harry.
Now, I would love to start with some context because few people spend 20 years at Google in the height of Google's scaling and trajectory. First, I wanna go back to the beginning. I heard there's a story to your joining. What happened, spelling corrector? Can you give me the story?
Um, yeah, that was, uh, yeah, that was, like, the first project that I, uh, that I worked on at Google. Yeah, I guess at the time, we, you know, Google had a spelling corrector that was, uh, you know, it, it was some third-party software, it was, uh, you know, based on maybe what you'd find in a word processor at the time. So there was, like, some human compiled dictionary of maybe about 50,000 words. And any word that wasn't in the dictionary that was in the query, it would say, you know, "Did you mean such and such?" And this worked great for spelling correction but it was, like, absolutely terrible for web search because people searched for such a wide diversity of things on web search, like most of them are just not in the dictionary. So, like, you'd search for turbot, like TurboTax, and it would say, "Did you mean turbot axe?" Like, and people just learned to ignore the thing. So, first project, like, we were just looking at, like, why are people, like, not happy using Google and, like, spelling correction was, like, the, you know, number one, uh, number one issue. So I was like, okay, let me, let me help out with this. And, you know, there was someone working on this, Paul Buchheit, who, uh, you know, who, who's, uh, you know, gone on to, uh, do a lot of, uh, a lot of illustrious things in his, uh, career. He's also one of our investors here at, uh, uh, Character. But, uh, he was going on, uh, on vacation for a couple weeks, uh, you know, o- over the winter holiday.
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