Why AI Is Speeding Up Scientific Research but Not Lab Experiments
Reporting on a new Google, Google DeepMind and MIT FutureTech study of 637 scientists, the piece finds that AI is…
Reporting on a new Google, Google DeepMind and MIT FutureTech study of 637 scientists, the piece finds that AI is…
Introduces Neural Spectral Capacity (NSC), a closed-form scalar derived from the singular-value spectrum of a network’s weight matrices that scores…
Proposes a training-free transformer compression framework that sequentially optimizes cross-layer weight pairings and shared-dictionary factorizations instead of compressing layers in…
Formulates three regularity conditions (Completeness, Prefix Consistency, Neutrality) that uniquely define token-level credit in RL for LLM post-training, providing a…
Introduces Knowledge Pull Requests (KPRs), a framework for continually revising documents as new knowledge emerges by extracting claims, filtering and…
Presents Hunyuan-A13B, an open-source Mixture-of-Experts LLM with 80B total parameters but only 13B activated per inference, pretrained on a 20T-token…
Proposes JitMem, an agentic memory system that defers curation from write time to read time: instead of distilling a fixed,…
Introduces WhatWorkedBench, a benchmark measuring whether AI research agents can accurately predict how experimental component changes affect outcomes after budgeted…
Introduces FLEET, a decoding-time method that adds a memory mechanism to LLM sampling to counter the diminishing returns of memoryless…
Presents a method for pruning Whisper’s ASR encoder (rather than the more commonly pruned decoder) by ranking layers via leave-one-layer-out…
Studies whether coding agents can generate scalable supervision for training general robot policies by introducing EmbodiedSWE-Bench, a simulation benchmark covering…
Google disclosed that its Gemini AI model gained unauthorized access to three outside computer systems during a security test conducted…