Lumbra announced on November 10, 2026 that it raised a $25 million Series A co-led by Point72 Ventures and Ansa, with continued participation from existing investor Costanoa, to expand its controlled AI-agent platform
Charta Health announced on November 10, 2026, that it had raised a $55 million Series B to expand its AI chart-review technology. Insight Partners led the financing, which also drew QuantumLight and returning investors
Motif Technologies plans to launch a global application programming interface business based on a next-generation model due to be released next year. The company aims to monetise in overseas coding and AI agent markets, where use of open-weight models is more active. Motif has begun developing its next AI model, Motif 4, and plans to release it as an open-weight model in the first quarter of next year. It expects model performance and token costs to determine profitability.
Microsoft researchers have discovered “Lazarus,” a backdoor technique that can reprogram dormant neurons in an AI model, causing an otherwise normal AI agent to execute malicious commands when a hidden trigger appears. The threat is especially serious for AI agents with tool or terminal access. A triggered model could quietly download and run attacker code, […]
SPARETECH announced on November 10, 2026, that it had raised $20 million in Series B funding co-led by Blume Equity and Insight Partners, with participation from Headline. The company will use the capital to develop AI
Ricursive Intelligence introduces Ripple-65B Preview, a 65B parameter dense Transformer model pretrained on 12 trillion tokens with support for up to 1M context length. Ripple-65B Preview delivers strong results on agentic coding, scoring 80.52 on TerminalBench 2.1 and…
Generation-free world action models (WAMs) retain future-video prediction during training but act from internal video features at inference, leaving unclear what these features should preserve for control. Our representation diagnostics show that representations with more…
FORM is a domain-specific symbolic manipulation language widely used in particle physics for processing the very large algebraic expressions arising from multi-loop Feynman diagram calculations. Despite its central role in precision theoretical physics, no…
Recurrent models must preserve information that changes future behavior while suppressing hidden-state error. These objectives conflict: contraction improves stability, but contraction along a future-distinguishing direction destroys memory. We formalize this boundary through…
Recent advances in large language models (LLMs) have led to the emergence of coding agents capable of performing complex engineering tasks, including register-transfer level (RTL) design and optimization. Existing RTL benchmarks mainly evaluate functional correctness and…