Alex Ratner, CEO of Snorkel AI, references results from the BloombergGPT research paper during a presentation on adapting foundation models for enterprise tasks.
Insight
Alex Ratner: Traditional model-centric AI development is dying off
“Tweaking the model, finding a fancier algorithm, all this kind of traditional model-centric development that, frankly, we still mostly teach in data science one-on-one courses as what data science is, is effectively dying off.”
Insight
Alex Ratner: Enterprise data is AI's only durable moat
“Enterprise data knowledge is the durable moat in AI, I'd argue the only durable one”
Assertion Partly supported
Ratner: $200 of ChatGPT calls can clone closed models into open ones
“If you take a couple hundred bucks of API calls to, say, ChatGPT, and you graph that onto a model that is substantially smaller, say a seven billion parameter model like LLAMA, or now increasingly fully open for commercial use ones, like Red Pajama is one that…”
Prediction Held up
Ratner: Private data models will exceed closed models in specialized tasks
“Closed source models, like a GPT-IV, five, six, seven, whatever comes, are going to be very hard to match in terms of generalist capability for, say, consumer use cases that are reflected in the web data they're trained on and the flywheels that get powered by…”
Assertion Partly supported
Ratner: Distillation creates specialized models 100,000x smaller with higher accuracy
“It shows that you can take these massive kind of generalist foundation models, And not only can you tune them using that kind of programmatic labeling to be more accurate on a given task that you need to be really accurate on, but you can then distill down ver…”
Prediction Not checkable as stated
Ratner: Base models will open-source while production uses specialized models
“There are going to be these base models. They're probably going to be increasingly open source. And then the reality of what actually ships in production is going to be a whole kind of family tree of smaller specialized models that are tuned and adapted via da…”