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Perplexity's Photon cuts retrieval latency 92%; Liquid AI releases zero-token decision model

Perplexity shipped Photon, a Rust-based retrieval engine reducing p99 latency from 800ms to 65ms; Liquid AI released d1, a decision model returning calibrated probabilities without generated tokens.

1 min read 3 sources

Perplexity has deployed Photon, an in-house retrieval and ranking engine written in Rust, across its production search infrastructure. The system replaces a previously forked open-source engine and now handles retrieval and ranking for all production traffic, reducing p99 latency from 800 milliseconds to 65 milliseconds according to the company. Photon powers a new Fast Search mode in Perplexity’s product (MarkTechPost).

Liquid AI released d1, a decision model designed for structured choice problems rather than text generation. The model accepts context and a set of typed questions, then returns calibrated probabilities across a fixed set of outcomes in a single inference call with zero generated tokens, targeting workflows where many teams currently use text-generation models (MarkTechPost). Separately, NVIDIA researchers introduced Physis-Lang, a framework that uses learned language representations to improve physics accuracy in video world models, lifting Cosmos 3 past Veo 3.1 on physics benchmarks (MarkTechPost).

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