AI Pulse News

U.S. debt suddenly draws weaker demand as $10 trillion must be rolled over this year amid Iran war. ‘The bond market remains undefeated’

Ripple turns to AI to stress-test the XRP Ledger as institutional use cases scale

XRP Ledger Gets AI Security Upgrade As Ripple Prepares For Bigger Growth

Meta orders 10 gas-fired power plants for its Hyperion AI campus in rural Louisiana—more than triple the initial plan

Kalshi moves toward margin trading with new regulatory approval

Crypto Biz: Stablecoin jitters meet institutional momentum

Alphabet (GOOG) Stock: Google Backs Anthropic’s Massive $5B Texas AI Data Hub

Microsoft secures 900 MW AI capacity at Crusoe Texas campus with mid 2027 target

Intercontinental Exchange Fulfills $1.6B Polymarket Investment

Isabel Schnabel: Monetary policy in times of geopolitical fragmentation

Nasdaq Enters Correction Zone Amid Iran Conflict and Tech Stock Selloff

The big stock market correction that Trump can’t talk his way out of is official

Prediction markets top $20 billion in monthly volume as geopolitics now drives majority of activity: TRM Labs

Super Micro Computer (SMCI) Stock Plunges Amid Reports of PLA-Affiliated Universities Acquiring Banned Nvidia Chips

Rogue AI is already here

Nonagon Capital and Startale Group Partner to Advance JPYSC Agentic Payment Use Cases

Federal Court Halts Trump Administration’s Anthropic AI Ban Over First Amendment Concerns

Anthropic wins court pause on Pentagon Claude ban

Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach

Researchers have developed the first formal mathematical framework for verifying AI agent protocols, specifically comparing Schema-Guided Dialogue (SGD) and Model Context Protocol (MCP). They proved these systems are structurally similar but identified critical gaps in MCP's capabilities, proposing MCP+ extensions to achieve full equivalence with SGD.

Supervising Ralph Wiggum: Exploring a Metacognitive Co-Regulation Agentic AI Loop for Engineering Design

Researchers developed a novel Co-Regulation Design Agentic Loop (CRDAL) system that uses metacognitive agents to improve AI-driven engineering design by reducing design fixation. The system showed better performance than traditional approaches in battery pack design tasks without significantly increasing computational costs.

ReLope: KL-Regularized LoRA Probes for Multimodal LLM Routing

Researchers introduce ReLope, a new routing method for multimodal large language models that uses KL-regularized LoRA probes and attention mechanisms to improve cost-performance balance. The method addresses the challenge of degraded probe performance when visual inputs are added to text-only LLMs.

FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context Protocol

ElephantBroker: A Knowledge-Grounded Cognitive Runtime for Trustworthy AI Agents

Researchers have introduced ElephantBroker, an open-source cognitive runtime system that combines knowledge graphs with vector storage to create more trustworthy AI agents with verifiable memory. The system implements comprehensive safety measures, evidence verification, and multi-organizational access controls for enterprise AI deployments.

RubricEval: A Rubric-Level Meta-Evaluation Benchmark for LLM Judges in Instruction Following

Researchers introduce RubricEval, the first rubric-level meta-evaluation benchmark for assessing how well AI judges evaluate instruction-following in large language models. Even advanced models like GPT-4o achieve only 55.97% accuracy on the challenging subset, highlighting significant gaps in AI evaluation reliability.

UniAI-GraphRAG: Synergizing Ontology-Guided Extraction, Multi-Dimensional Clustering, and Dual-Channel Fusion for Robust Multi-Hop Reasoning

Researchers have developed UniAI-GraphRAG, an enhanced framework that improves upon existing GraphRAG systems for complex reasoning and multi-hop queries. The framework introduces three key innovations including ontology-guided extraction, multi-dimensional clustering, and dual-channel fusion, showing superior performance over mainstream solutions like LightRAG on benchmark tests.