Steve Gibson

speaker
17,616 appearances 14 recordings 1 series first heard May 2026 last heard 2 Sep

Steve Gibson’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 14 in all, peaking in Jul 2026 with 5.

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sentiment of generations and matches or improves response quality in summarization and single-turn dialogue while being substantially simpler to implement and train.
So
Okay, that's just their abstract.
And the paper goes on at length, like with crazy formulae.
Uh, I wanted to share that because I didn't want to leave everyone with the belief that the original RLHF, the reinforcement reinforcement learning from human feedback approach, which began this transformation from autocomplete to actually QA, um, that that that's what the industry.
Still using it as I said, it was the Genesis.
Stanford's DPO, their direct preference optimization dramatically improved it.
Um, and DPO's success, as I said, spawned a number of successors, which I cited earlier.
Okay, so.
What is all this about?
It's about how we take a massive neural network, which has been trained on and contains raw knowledge, which can initially only be used to predict the next most likely token and impress upon that network actual behavior.
That's what's changing here.
We're giving this knowledge base.
A set of behavior
That the first example of behavior was turning the network into something that could actually respond to queries.
That gave us the first interactive AI.
But as I noted, those first steps were somewhat shaky.
So over the time, researchers learned that by using
the technologies I just described, they could improve the model's instruction following behavior so that it would answer the question that was asked as well as respect the requested format and length and language.
the model's style and tone could also be modified and tuned to improve its response formatting, structure, hedging, politeness, and its own verbosity.
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