iFeeling Daily
Daily curated AI insights you can't miss.
Nous Research in talks for $1.5B valuation after Hermes agent success
Nous Research is raising a new round at a $1.5 billion valuation, backed by Robot Ventures and USV, just months after its Series A. The open-source Hermes agent competes with OpenClaw by offering built-in skills, auto-learning, and a cloud-hosted tier. The funding will likely accelerate product expansion.
Behavioral Privacy Leakage in Agentic Negotiation
Autonomous negotiation agents are increasingly deployed in high-stakes settings like insurance and procurement, where cryptographic techniques protect explicitly disclosed constraints. However, this paper exposes a subtler threat: behavioral privacy leakage, where an adversary infers private constraints from observable negotiation dynamics—concession trajectories, timing, and convergence patterns. The tension is that even if the agent never reveals its reservation price directly, its behavior during rounds of bargaining leaks enough information for inference attacks.
Using Surprisal to Map Agent Retrieval Performance
Standard pass/fail benchmarks hide where agents actually break. This article shows how using information theory (surprisal) to sweep query ambiguity reveals capability cliffs and sweet spots that single-score evaluations miss. It's a practical guide to building evaluations that produce actionable signals, not just verdicts.
An AI agent startup let its agent run its $100 million fundraise
Lyzr used its own AI agent, SivaClaw, to run its $100 million Series B fundraise—fielding investor questions, drafting memos, and tracking slide engagement. The story shows how AI agents can handle high-stakes business development when capital is abundant and traction is proven.
AlphaEvolve: Google’s algorithmic discovery agent goes GA
AlphaEvolve, Google's agent for systematic algorithmic discovery, is now generally available on the Gemini Enterprise Agent Platform. Early adopters report dramatic gains across logistics, chip design, genomics, and ML training — including an 80% improvement in supply chain models and doubled training throughput — by turning optimization into a search problem that machines explore autonomously.
Modal CTO on the 100,000 Sandbox Problem and AI Infrastructure
Modal CTO Akshat Bubna explains why Kubernetes fails at AI workloads, how Modal's 17-cloud capacity pool and GPU snapshotting handle bursty inference and RL rollout sandboxes, and why observability matters more when agents write the code.
Claude Cowork Expands to Mobile and Web: The Agentic Coworker Arrives
Anthropic expands Claude Cowork to mobile and web, letting Max subscribers run background tasks across devices. New usage data shows business process ops (33.4%) and content creation (16.4%) dominate, while coding is only 8.7% — a strong signal that the real value of AI agents is in the administrative work that keeps companies running, not just software development.
Claude Code usage data shows domain expertise, not coding skill, drives success
Anthropic analyzed ~400,000 Claude Code sessions and found that domain expertise, not coding skill, is the strongest predictor of success. Experts achieve verified success more than twice as often as novices, and every major occupation succeeds at nearly the same rate as software engineers when using the tool.
Project Fetch Phase Two: Claude Opus 4.7 Outpaces Humans on Robot Tasks
Anthropic's follow-up to Project Fetch shows Claude Opus 4.7 completing robotics tasks up to 37 times faster than human teams from eight months earlier — without any human assistance. While closed-loop physical control remains a challenge, the rapid general scaling of LLMs is closing the gap between helpful assistant and autonomous physical agent.