AI

Musk’s ‘Terafab’ gambit with Intel sharpens focus on looming SpaceX–X public listing: could crypto be next?

A councilmember backed a data center project. Then 13 bullets and a ‘No Data Centers’ note hit his home

The AI trade is over. Top Wall Street analysts say the AI opportunity might be just starting

Firmus, the ‘Southgate’ AI datacenter builder backed by Nvidia, hits $5.5B valuation

Anthropic debuts preview of powerful new AI model Mythos in new cybersecurity initiative

Anthropic is giving companies, including Amazon, Apple, and Microsoft, access to its unreleased Claude Mythos model to prepare cybersecurity defense

AI agents get a new DeFi rail with ERC-8211 ‘smart batching’

Solana’s privacy narrative sharpens as SOL Strategies buys Darklake Labs

AVAX One pivots to “AI infra + Bitcoin hash” with 10MW Alberta microgrid

Cysic’s Venus zkVM goes open source as Ethereum eyes proof markets

Eightco turns into a listed bet on Worldcoin and OpenAI

Proposed Ethereum Standard Aims to Help AI Agents Execute Complex DeFi Trades

Xiao-I (AIXI) Stock Explodes Over 500% Following Major Chinese Supreme Court Victory Against Apple

Meta to roll out open source AI models in next phase of development

Anthropic’s refusal to arm AI is exactly why the UK wants it

Broadcom (AVGO) Surges on Multi-Billion Dollar AI Chip Partnerships with Google and Anthropic

Intel is going all-in on advanced chip packaging

JPMorgan CEO says AI will transform banking faster than the internet era

Bitcoin miners face a new rival for cheap power as Anthropic signs multi-gigawatt compute deal

Position: Science of AI Evaluation Requires Item-level Benchmark Data

Researchers argue that current AI evaluation methods have systemic validity failures and propose item-level benchmark data as essential for rigorous AI evaluation. They introduce OpenEval, a repository of item-level benchmark data to support evidence-centered AI evaluation and enable fine-grained diagnostic analysis.

Toward Full Autonomous Laboratory Instrumentation Control with Large Language Models

Researchers demonstrate how large language models like ChatGPT can automate laboratory instrument control, reducing programming barriers for scientists. The study shows LLMs can create custom scripts and operate as autonomous AI agents for lab equipment management.

VERT: Reliable LLM Judges for Radiology Report Evaluation

Researchers introduced VERT, a new LLM-based metric for evaluating radiology reports that shows up to 11.7% better correlation with radiologist judgments compared to existing methods. The study demonstrates that fine-tuned smaller models can achieve significant performance gains while reducing inference time by up to 37.2 times.

When Adaptive Rewards Hurt: Causal Probing and the Switching-Stability Dilemma in LLM-Guided LEO Satellite Scheduling

Research reveals that adaptive reward mechanisms in AI-guided satellite scheduling systems actually hurt performance, with static reward weights achieving 342.1 Mbps versus dynamic weights at only 103.3 Mbps. The study found that fine-tuned LLMs performed poorly due to weight oscillation issues, while simpler MLP models achieved superior results of 357.9 Mbps.

Selective Forgetting for Large Reasoning Models

Researchers propose a new framework for 'selective forgetting' in Large Reasoning Models (LRMs) that can remove sensitive information from AI training data while preserving general reasoning capabilities. The method uses retrieval-augmented generation to identify and replace problematic reasoning segments with benign placeholders, addressing privacy and copyright concerns in AI systems.

Rashomon Memory: Towards Argumentation-Driven Retrieval for Multi-Perspective Agent Memory

Researchers propose Rashomon Memory, a new AI agent memory architecture where multiple goal-conditioned agents maintain parallel interpretations of the same events and negotiate through argumentation at query time. The system allows AI agents to handle conflicting perspectives on experiences rather than forcing a single interpretation, using Dung's argumentation semantics to determine which proposals survive retrieval.