Imbue co-founder Kanjun Qiu describes the technical realizations regarding multimodal self-supervised learning that inspired founding Imbue.
Prediction Not checkable as stated
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.”
Insight
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.”
Assertion Not checkable as stated
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.”
Prediction Not checkable as stated
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…”
Insight
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.”
Insight
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.”