Eduard (Edward) Dulharu

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420 appearances 1 recordings 1 series first heard Aug 2026 last heard 7 Aug

Eduard (Edward) Dulharu’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Aug 2026 with 1.

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Heavy Networking · HN837: Agentic AI to Reduce MTTR · 7 Aug 2026 podcast

So which is fine for they say for the

for the academical level of understanding, but for the practical uh uh for the prac practicality of the result which is the uh final model, I want to

to to to pass actually all the tests.

So and then I test the model against the mo the fine tuned model should be better than the base model, obviously, because otherwise what is the point?

And then I test it against the frontier model.

I use GPD for me.

Exactly.

So the frontier models are excellent in generic knowledge, uh RFCs, documentation, yeah, everything, but not on specific, let's say, corner cases which are part of the data set.

And that's why when people test uh these frontier models against some very tricky uh use cases or coronal cases, and of course the model will hustle and say, yeah, it's not working.

But the reality is that it was never trained to uh behave correctly for that uh uh uh uh coronal cases.

So uh so this is the first level uh supervised fine tuning and then uh second level

Level is direct uh it's called DPO, uh, which uh I generate multiple answers for the same question and uh

I I generate two answers for the same question and I say to the model that I want I prefer this uh answer instead of uh a second.

So every question has uh two answers and the model is trained to prefer based off my um uh input, based on my data, to prefer uh one uh versus the other.

So in this way I add um behavioral

Preference uh for the model.

And this second level of training uh aligns the model with my preferen my preferences.

Yes, I think it should be.

It should be a everyday technology.

And um the prerequisites to get to this point I just um

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