Ashvin Nair

speaker

533 appearances 1 recordings 1 series first heard Dec 2025 last heard 30 Dec

Ashvin Nair’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 Dec 2025 with 1.

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Latent Space: The AI Engineer Podcast · [State of RL/Reasoning] IMO/IOI Gold, OpenAI o3/GPT-5, and Cursor Composer — Ashvin Nair, Cursor · 30 Dec 2025 podcast

Uh actually haven't seen exactly like like

Yeah.

What I'd like to do is kinda like I haven't I just haven't read the like GDP Val traces close closely.

Um it's not clear to me that, you know, like what like what does the job of an accountant entail and like what kind of context needs to be in the product, yeah so that you can actually do it.

EDFs.

I see, I see.

Yeah.

So yeah, I think like roughly operating in this kind of thing is what I envision.

Yeah, I think that's like roughly the right shape of the thing.

And I guess how I imagine this being um you know, operationalized is that you'd want to like co-design the product and the model so that like the product for whatever it is, like I mean, coding is kind of maybe the easiest first step because most of the context that you care about is just your code base and like being able to run stuff in the terminal and that kind of stuff.

And still like we're not that close really to automating it necessarily.

But you know, for for like all the other jobs, the context is like insane, right?

It's like all the conversations you've had with your coworkers, like your Slack messages, you know, like for my um so at OpenAI, I was working on kind of like hyperparameter scaling research and I actually wrote not that much

Uh no, more like um understanding how different like um science of deep learning in like 2020 where it's like oh you had to like initialize the layers in a particular way to get good scaling love.

Kind of the analog for that for RL.

Um the thing is like I didn't write a ton of code.

The LM, you know, like writing code is not the uh bottleneck, but it's more like you know, over the course of a year, I like run sweeps, look at like the interaction between different hyperparameters and kind of build up that knowledge for like a year of like just different graphs.

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