Ceipal announced on November 10, 2026, the launch of Ceipal Ora, an agentic AI platform that uses software agents to execute staffing workflows, and reported that 650 customer companies were already running at least
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To prevent AI agents from going rogue, OpenAI has developed Control Room, which lets researchers quickly stop AI models if something goes wrong. It takes around 35 seconds to shut them down. The system acts as an emergency brake as the company works to make its increasingly powerful AI models safer.
The Council on AI and Digital Technology released its report on Tuesday, warning about how artificial intelligence services exploit users' 'vulnerabilities.'
Meta has introduced Muse Ember, a lightweight AI model designed for agent execution. The model focuses on repetitive tasks, multimodal processing, and lower operating costs for businesses deploying AI agents at scale. Meta Superintelligence Labs has ...
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…
Introduction Hello! We are arr0w (ML) and utdoi (Backend), Product Engineers at Mercari. Our team, the Product Data Team, works on integrating product data held by external businesses to improve the coverage and quality of our product catalog (data that consolidates information…
Multilingual code language models transfer skills across programming languages (PLs), but whether any PL occupies a privileged pivot position remains contested: geometric analyses point to C-family languages and Go, while behavioral evidence highlights Python. We revisit this…
Automated operations research (OR) modeling requires LLMs to translate natural-language decision problems into correct mathematical programs. Existing methods can improve individual formulations, but they often solve problems in isolation, retaining little reusable experience…
Physics-informed neural networks (PINNs) use one shared representation over the computational domain, which can become difficult to optimize on long domains and for high-order operators. We study a minimal alternative: multiply the first hidden activation of an otherwise…
Robotic grasping is typically formulated as the problem of identifying successful actions from a space of candidate grasp poses. However, the organization of successful actions within this space has received less attention. We study the multiscale structure of viable robotic…