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Fem's avatar

You're being very generous with Palantir and super dismissive of Amjad. Amjad's point IS that companies like Palantir will work to diversify their hiring when its someone that's just like them (Karp) but will crap on DEI if it's people that are not like them. It's all the same shit. You want to beleive that Palantir is doing the ideologically consistent thing here because you beleive it includes you. It might not.

The rest of your musing is smart but people can make similarly smart arguments for DEI that have to do with culture, race, communication style, perception etc etc.

Don't be fooled because you want to beleive you're included.

Daniel John Murray's avatar

Vaishnav,

You're describing variance optimization in high-dimensional skill space without realizing you've just argued for hyperbolic geometry.

"Spiky profiles" = high variance in individual dimensions. "Well-rounded" = low variance, clustered near the mean.

In Euclidean space, you'd minimize distance from center (standard hiring: "how close to average?"). In hyperbolic space, you maximize distance along specific dimensions (Palantir: "how far from average in the direction that matters?").

The "outlier advantage" you describe is literally the advantage of hyperbolic embeddings: rare, high-signal patterns are exponentially better separated in hyperbolic space than Euclidean.

Palantir isn't being "pragmatic about neurodivergence." They're doing what any organization optimizing for high-dimensional pattern recognition should do: hire for maximum variance along task-relevant axes.

You just accidentally explained why AI embedding spaces are hyperbolic. Congrats—you've been doing differential geometry this whole time without knowing it.

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