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Nokia is reportedly planning further layoffs, facility closures, and a major reduction of its mainland China operations, potentially retaining only limited after-sales services. The retreat is part of a global restructuring toward AI and cloud businesses, but it may reduce Nokia’s access to China’s large-scale 5G deployment data needed for AI-RAN and future 6G research.
Researchers introduce an open-source benchmark separating olympiad geometry solving from accurate diagram construction. Across 954 problems, current foundation models achieved only a 36.14% average diagram compilation success rate, revealing a substantial gap between mathematical reasoning and faithful visual construction.
FinSkillBench is a new benchmark for testing AI agents on portfolio construction, risk management, and fundamental analysis. Across nine models, curated procedural skills raised mean performance from 0.366 to 0.528, while self-generated skills delivered little benefit.
Xiaomi stabilized in Q2 2026 while expanding its AI strategy across models, chips, and robotics. Its MiMo-V2.5 model led OpenRouter call charts, the Xuanjie chip passed mass verification, and a humanoid robot began factory operations with a reported 98% success rate.
PTC has launched the FeatureScript MCP Server for its Onshape CAD/PDM platform. Engineers can use natural language and AI to create custom CAD features.
OpenAI reaffirmed Zero Data Retention for eligible API customers using frontier models. It also previewed Private Safety Processing, designed to support advanced AI safety work without compromising customer data privacy.
OpenAI said it will enhance safety processes for paying users who access its most advanced AI models. The move responds to customers using AI for increasingly complex tasks and handling more sensitive information.
Eagle Point Credit Management is providing roughly $1.3 billion in private credit for a large Texas data center tied to Anthropic. The financing gives the investment firm a significant role in a major AI infrastructure project.
AWS outlines enterprise patterns for operating many agentic AI systems across diverse frameworks, models, and providers. The guidance focuses on preserving flexibility and enabling multi-agent systems to scale together without vendor lock-in.
Generative recommenders are shifting recommendation objectives from embedding similarity toward predicting a user's next action or item. The approach uses user-history sequences and large catalogs to rethink how recommendation systems are trained and served at scale.