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Language Models

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Monday, 24 August 2026

Google Research Introduces ME-POIs: A Mobility-Informed Framework that Adds “How a Place Is Used” to Text-Based POI Embeddings

MarkTechPost 1 month ago 19

Google Research and USC released Mobility-Embedded POIs (ME-POIs), a framework that adds aggregate movement patterns to text-based place embeddings. It reports relative gains up to 81.9% F1 for visit-intent on Los Angeles mobility data. Deployability is limited because the paper is released without public code or weights and requires licensed foot-traffic/visit logs plus POI polygons.

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Google Language Models

Canonical backs quest to translate mountains of C into safe Rust with AI

The Register 1 month ago 2

Canonical is co-funding a three-year PhD project at the University of Bristol to study whether large C codebases can be translated into safe Rust using an LLM-based approach. The project is planned for 3 years. The work will shift from “bots rewriting everything” to generating evidence on feasibility, including evaluating decomposition of hundreds of thousands of C lines and testing candidate targets like snap-confine and AppArmor.

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Language Models

Kids outlearn AI—and we still don’t know why

MIT Technology Review 1 month ago 36

Researchers say today’s large language models need far more training data than human children to learn language, creating a “data efficiency gap” that remains unexplained. BabyLM—the benchmark competition meant to test child-scale learning—asks teams to train models on a developmentally plausible corpus of 100 million words (10 million for the toddler track). The field is shifting toward evaluating and designing more data-efficient AI systems that better match how children acquire grammar, instead of relying only on scaling up data.

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AI Benchmarking Language Models AI Efficiency AI & Academia

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