We’ve always had output schemas for LLMs, and we’ve had small language classifiers for decades, so what’s new? Is it just some sweet spot in between in terms of quality vs speed?
Jev uses a different training architecture called RLCF (Reinforcement Learning from Calibrated Decisions) vs the traditional RLHF that most TF models use.
So at the end of the day the groundbreaking work wasn't the model itself inherently but the way it was trained and then the way the harness interacts with it.
So this demo here is showing the harness side of things afaict but then TypeSafe's Jev takes it a step further via a specific training regimine.
brap · · focus · HN ↗
We’ve always had output schemas for LLMs, and we’ve had small language classifiers for decades, so what’s new? Is it just some sweet spot in between in terms of quality vs speed?
OneDeuxTriSeiGo · · focus · HN ↗
So at the end of the day the groundbreaking work wasn't the model itself inherently but the way it was trained and then the way the harness interacts with it.
So this demo here is showing the harness side of things afaict but then TypeSafe's Jev takes it a step further via a specific training regimine.
dominotw · · focus · HN ↗
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