Kanjun Qiu
Co-Founder and CEO, Imbue. On 3 shows, 3 appearances. The Shows tab opens the full record on each.
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Kanjun Qiu is the co-founder and CEO of Imbue, an AI research lab developing reasoning and code-generating agents. She previously served as the first Chief of Staff at Dropbox, co-founded the startup Sourceress, and co-authored the computing education book Sew Electric.
3shows
3appearances
43statements
5resolved
4supported
0contradicted
80%fully supported
4said about them ↓ Everything Kanjun Qiu said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Qiu: Pragmatic, smaller models will eventually address the majority of AI workflows
“And I suspect we're going to see something similar where a lot of use cases are going to be able to be addressed by something pretty pragmatic and relatively small.”
Qiu: Training a giant monolithic model does not magically solve agent reliability
“It's not like, oh, magical, you know, we train a giant model and stick everything into it and then magically it works. Like it does not work. It'll get better at random parts of the agent loop, but that's not what we want.”
Qiu: Imbue trains state-of-the-art AI models with only 13 or 14 people
“We're kind of like training state, state of the art models with like 14, 13 people.”
Qiu: Reasoning is the single biggest blocker for AI agents
“Reasoning is actually, we believe the biggest blocker to agents or systems that can do these larger goals.”
Qiu: Models lack reasoning because the internet lacks explicit reasoning data
“And models today, they're not optimized for reasoning. It turns out that there's not actually that much explicit reasoning data on the internet.”
Qiu: Synthetic code data can improve reasoning better than human code
“Code also is a big piece of improving reasoning. So yeah generated code is not That much worse than, like, regular human written code. You might even say it could be better in a lot of ways.”
Qiu: Pure reinforcement learning cannot deliver planning and reasoning
“The second thing we learned is that reinforcement learning is not a good vehicle. Like, pure reinforcement learning is not a good vehicle for planning and reasoning.”
Kanjun Qiu: Most autonomous AI agents do not work well today
“So to your question of, like, what agents work well and what doesn't work well, like, most of the agents don't work well, and we're slowly making them work better by improving the underlying model and improving these.”
Qiu: Imbue generates specific reasoning data rather than relying on web data
“So I think internally, yeah, we have a lot of thoughts on what reasoning is, and we generate a lot more specific data. We're not just like, oh, it'll figure out reasoning from this black box or like, it'll figure out reasoning from the data that, that exists.”
Kanjun Qiu: Chat is a skeuomorphic, primitive interface for AI agents
“Chat as an interface is skeuomorphic. So in the early days, when we made word processors on our computers, they had notepad lines because that's what we understood you know, these like objects to be chat. Like texting someone is something we understand. So tex…”
Kanjun Qiu: Standardizing agent protocols is premature because agents don't work yet
“Part of why I think it's early is because the issue with agents is it's not quite like the internet where you could like make a website and the website would appear. The issue with agents is that they don't work. And so it may be a bit early to figure out what…”
Qiu: RAG is inadequate for scientific AI reasoning and cumulative synthesis
“I don't think RAG is enough for that kind of thing. But RAG is certainly enough for, like, user preferences and things like that.”
Kanjun Qiu: AI emergent capabilities are artifacts of evaluation metric design
“If your metric is smooth you actually see slow performance improvement over time, and if your metric is relatively discrete or not smooth, that's where you see the emergence, and it's actually more about the evaluation metric Than about the emergence of the ca…”
Qiu: Self-supervised AI may learn representations akin to human cognition
“There's something really interesting here where maybe machines are learning the same kinds of representations or similar representations to what humans are learning. And maybe they can get to a point where they can actually do the types of things that humans a…”
Qiu: Software output will explode as programming democratizes to non-coders
“Software is just dramatically underwritten because it's so hard to write code today. So, you know, as we said in the future, like, computers will be able to be programmed by regular people. What that means is, like, we're gonna write way, way, way more softwar…”
Kanjun Qiu: Agent reliability's final 20% is as hard as self-driving cars
“Agents haven't been productized yet for, partly for this reason, is that, like, the abstractions are very leaky. You know, we can get, like, 80% of the way there, but, like, self-driving cars, like, the remaining 20% is actually really difficult.”
Qiu: RL algorithms do not work at all without a curriculum
“One is with no curriculum, RL algorithms don't work at all.”
Qiu: Code is the most explicit reasoning curriculum for AI models
“Code is the most explicit example of reasoning data on the internet. Yeah. And it's not only structured, it's actually very explicit, which is nice. You know, it says this variable means this and then it uses this variable and then the function does this. Like…”
Qiu: AI is currently in an un-reliable analog computer phase
“I think today, you know, we're kind of in the analog computer phase of AI, where You know, ah, these systems, they output things. Errors compound. They're not very reliable.”
Kanjun Qiu: Language models trained without code perform poorly at reasoning
“Some companies have tried training language models with no code because they're like, oh, the product we're building, we don't need code. You know, it's a therapist or it's a question answering thing and we don't need code. So we should take code out of our tr…”
Qiu: Psychological trauma can be conceptualized as computational overfitting
“Trauma is overfitting and actually a good way to overcome trauma. If we look at a lot of therapy It's like by giving more data to me and helping me access the overfit parts and then give them more data.”
Qiu: Autonomous AI agents represent a calculator-to-computer leap in technology
“The diff between this, where we are today, and that is kind of like the diff between the first calculator and where computers are today.”
Qiu: Chain of thought and tree of thought function as error correction
“Reasoning is one big piece of improving reliability, and second chunk of things is like all of this error correction, and I think like chain of thought, tree of thought, these are error correction techniques.”
The other half of the tape: Kanjun Qiu's own voice is left out of every number here. Other people bring the name up 4 times in 3 episodes across the shows. every mention, with the transcript →
Who brings them up most Alessio Fanelli 2
Every mention by year
tap a year for its mentions
Latent Space 4
One line per show, most statements first. The link opens Kanjun's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
| LATENT SPACELEDGER | Co-Founder and CEO, Imbue | 1 | 20 | 50% 1/2 | full record on Latent Space → |
 MADLEDGER | Co-Founder and CEO, Imbue | 1 | 12 | 100% 3/3 | full record on the MAD Podcast → |
 NO PRIORSLEDGER | Co-Founder and CEO, Imbue | 1 | 11 | — | full record on No Priors → |