AI

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

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

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

Beyond Static Vision: Scene Dynamic Field Unlocks Intuitive Physics Understanding in Multi-modal Large Language Models

Researchers identify critical limitations in current Multimodal Large Language Models' ability to understand physics and physical world dynamics. They propose Scene Dynamic Field (SDF), a new approach using physics simulators that achieves up to 20.7% performance improvements on fluid dynamics tasks.

Event-Driven Neuromorphic Vision Enables Energy-Efficient Visual Place Recognition

Researchers developed SpikeVPR, a bio-inspired visual place recognition system using event-based cameras and spiking neural networks that achieves comparable performance to deep networks while using 50x fewer parameters and consuming 30-250x less energy. The neuromorphic approach enables real-time deployment on mobile platforms for autonomous robot navigation.

AI Governance Control Stack for Operational Stability: Achieving Hardened Governance in AI Systems

Researchers propose a six-layer AI Governance Control Stack for Operational Stability to ensure traceable and resilient AI system behavior in high-stakes environments. The framework integrates version control, verification, explainability logging, monitoring, drift detection, and escalation mechanisms while aligning with emerging regulatory frameworks like the EU AI Act and NIST standards.

Profile-Then-Reason: Bounded Semantic Complexity for Tool-Augmented Language Agents

Researchers introduce Profile-Then-Reason (PTR), a new framework for AI language agents that use external tools, which reduces computational overhead by pre-planning workflows rather than recomputing after each step. The approach limits language model calls to 2-3 times maximum and shows superior performance in 16 of 24 test configurations compared to reactive execution methods.

Compliance-by-Construction Argument Graphs: Using Generative AI to Produce Evidence-Linked Formal Arguments for Certification-Grade Accountability

Researchers propose a compliance-by-construction architecture that integrates Generative AI with structured formal argument representations to ensure accountability in high-stakes decision systems. The approach uses typed Argument Graphs, retrieval-augmented generation, validation constraints, and provenance ledgers to prevent AI hallucinations while maintaining traceability for regulatory compliance.

Structured Multi-Criteria Evaluation of Large Language Models with Fuzzy Analytic Hierarchy Process and DualJudge

Researchers developed DualJudge, a new framework for evaluating large language models that combines structured Fuzzy Analytic Hierarchy Process (FAHP) with traditional direct scoring methods. The approach addresses inconsistent LLM evaluation by incorporating uncertainty-aware reasoning and achieved state-of-the-art performance on JudgeBench testing.

FactReview: Evidence-Grounded Reviews with Literature Positioning and Execution-Based Claim Verification

Researchers introduce FactReview, an AI system that improves academic peer review by combining claim extraction, literature positioning, and code execution to verify research claims. The system addresses weaknesses in current LLM-based reviewing by grounding assessments in external evidence rather than relying solely on manuscript narratives.