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…
Generating coherent meta-reviews from multiple peer reviews is challenging when reviewer evidence conflicts and varies in reliability. Existing approaches typically formulate meta-review generation as a multi-document summarization task and aggregate reviewer feedback…
In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object detection. Existing methods establish semantic relationships between base categories and unseen novel categories by placing a…
We present a method for synthesizing reactive character behaviors for continuous games as compact, human-readable programs. Game AI practice still relies heavily on manually authored behavior trees, state machines, and scripts, while academic reinforcement learning typically…