[AINews] Agents disprove Polysemanticity; greatly improve Interpretability & Alignment
Nick Cammarata out of nowhere with some major claims!
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[AINews] Agents disprove Polysemanticity; greatly improve Interpretability & Alignment
Nick Cammarata out of nowhere with some major claims!
Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline
Scaling Indic Pretraining: 2.8 Trillion Tokens and an Open Data Generation Pipeline
Microsoft releases Magnetar: a universal zero-knowledge virtual machine that supports Rust, Go, and C, with quantum-safe proofs implemented using standard hash functions.
Microsoft Research has unveiled Magnetar, a zero-knowledge virtual machine that, for the first time, simultaneously addresses the three long-standing bottlenecks of zero-knowledge proofs in a single system: low generation efficiency, high development barriers, and insufficient post-quantum security. It enables programs written in mainstream languages such as Rust, Go, and others to be compiled and executed directly, with verifiable proofs generated automatically. On average, it is 10–39 times faster than the fastest existing zkVMs, with proof verification taking only about 12 milliseconds. Moreover, its security relies solely on standard hash functions like SHA‑256 and SHA‑3—NIST‑standardized algorithms that have stood the test of decades of cryptographic scrutiny—eliminating the need for trusted setups, elliptic curves, or novel mathematical assumptions that have not been thoroughly validated.
Bringing GPT-Rosalind to academic research labs
Introducing the Rosalind Academic Plan, offering eligible academic labs sponsored access to GPT-Rosalind and tools to advance life sciences research.
Apertus 1.5 Release Notes
Apertus 1.5 Release Notes
Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint
Granite Switch 4.1: Chat, Decisions, and Speech from One Endpoint
Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta
Welcome Muse Spark Open: open-weight frontier multimodal mixture-of-experts model from Meta
Research@ 2026: 10 ways we're amplifying human ingenuity
General Science
HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost
HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost
Run fast, private agents on-device with LFM2.5-24B-A2B
Run fast, private agents on-device with LFM2.5-24B-A2B
Simulating student learning for better AI tutoring
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
The model that didn't exist, so you made it yourself
The model that didn't exist, so you made it yourself
Does better work always mean better workers?
Does better work always mean better workers?
Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
Introducing Falcon ASR
Introducing Falcon ASR
One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO
One Model Family, Two Gold-Level Results: Fine-Tuning Nemotron for IOI and IMO
Multimodal open d1 decision models for the edge
Multimodal open d1 decision models for the edge