Micah-Hill Smith

speaker

601 appearances 1 recordings 1 series first heard Jan 2026 last heard 8 Jan

Micah-Hill Smith’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 Jan 2026 with 1.

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Latent Space: The AI Engineer Podcast · Artificial Analysis: Independent LLM Evals as a Service — with George Cameron and Micah-Hill Smith · 8 Jan 2026 podcast

Some of the people with the strongest opinions about what we're doing well and what we're not doing well and what they are want to see next from us.

Because when you're building any kind

Of AI application now, chances are you're using a whole bunch of different models.

You're maybe switching reasonably frequently for different models and different parts of your application to optimize what you're able to do with them at an accuracy level and to get better speed and cost characteristics.

So for many of them, no, they're um like not commercial customers of ours, like we don't

charge for all that data on the website, but they are absolutely some of our power users.

Okay.

First, just like background, like we're talking about the artificial analysis intelligence index, which is our synthesis metric that we pull together currently from ten different eval data sets to give what we're pretty confident is the best single number to look at for how smart the models are.

Obviously, doesn't tell the whole story.

That's why we published the whole website of all the charts to dive into every part of it and look at the trade offs, but

Pessen gonna be.

So right now it's got on it a bunch of QA type data sets that have been very important to the industry, like a couple that you just mentioned.

It's also got a couple of agenc data sets, it's got our own long context reasoning data set and some other use case focused stuff.

As time goes on.

The things that we're most interested in that are gonna be important to the capabilities that are becoming more important of AI, what developers are caring about, are gonna be first around agenda capabilities.

Surprise, surprise, we're all loving our coding agents and how the model's gonna perform like that and then do similar things for different types of work are really important to us.

The linking to use cases, to economically valuable use cases, are extremely important to us.

And then we've got some of these um

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