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Tactile robotics is expanding from sensor hardware into datasets, foundation models, and evaluation benchmarks. Research shows touch improves physical reasoning and robot success, but inconsistent sensor formats create major cross-device transfer challenges.
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.
Flock is testing an AI tool that tracks and identifies people based on their driving habits. The system goes beyond conventional license-plate monitoring, raising significant surveillance and privacy concerns.
Calendly is expanding beyond scheduling by entering the crowded meeting note-taking market. It is also releasing Callie, a meeting scheduling assistant.
Fei-Fei Li discusses her AI research, her $1 billion startup World Labs, and why she believes the next phase of AI will extend beyond chatbots. The conversation outlines a broader vision for AI’s future rather than announcing a specific product release.
The article argues that China’s AI industry is moving beyond simply accumulating accelerator cards and toward measuring the economic value produced by each Token. It frames 2026 as a pivotal period for lowering Token production costs and improving compute efficiency.
WIRED reconstructed the code behind Flock’s next-generation AI surveillance system. The system is already being used by some police departments and appears capable of tracking more than license plates.
Z.ai argues that model scaling should account for data, compute allocation, inference cost, sparsity, effective depth, and post-training—not parameters alone. The post presents GLM-5.3 as a controlled experiment using the same total and activated parameters as GLM-5.2 while scaling long-horizon environments and reinforcement learning for one month.
A community test on an AMD R9700 with ROCm reports noticeable quality and long-context retention differences between FP16 and q8_0 KV cache for Qwen3.8-27B. FP16 reportedly produces more careful structured output and maintains performance beyond 120k tokens, challenging the assumption that both formats are equivalent.
The article examines three strategic questions that companies must answer before AI becomes a sustainable business: where they are positioned, whom they should work with, and how to generate recurring profits. It frames AI adoption as a business execution challenge beyond simply deploying models.