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Real updates, not press releases. We track emerging AI trends, new product features, and research that shapes the future of business automation.

Advancing GPU Programming with the Triton CUDA Tile IR backend
NVIDIA’s tile-native virtual ISA meets Triton’s Python DSL, promising higher portability and Tensor Core efficiency for ML workloads. Here’s what engineering leaders need to know.
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Google Auto Browse hands-on review: promise vs. reality for Chrome’s new AI agent
Google’s Gemini-powered Auto Browse aims to complete multi-step web tasks inside Chrome. Our review of early testing and announcements finds bold automation claims—but uneven execution and clear caveats.
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Into the Omniverse: Physical AI Foundation Models and Frameworks Advance Robots and Autonomous Systems
At CES 2026, NVIDIA pushed a platform strategy for robots and autonomous systems built around Omniverse simulation and newly opened foundation models—aimed at speeding development, improving safety, and lowering costs.
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AI Toy Data Breach: Bondu Exposed 50,000 Kids’ Chat Logs
Researchers found Bondu’s parent/staff web console left wide open, exposing more than 50,000 children’s chat transcripts and sensitive profiles. The lapse underscores systemic risks in connected AI toys and basic SaaS security failures.
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How to disable Alexa+ Early Access and revert to classic Alexa
Amazon’s LLM-powered Alexa+ is rolling out broadly, with Prime members auto-enrolled. Here’s how to opt out, manage costs, and protect your voice data.
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GPU fairshare scheduling in Kubernetes: Time‑Based Fairshare for Balanced AI Clusters
Run:ai extends Kubernetes to combine strict GPU guarantees with time-based fairshare, enabling balanced, high‑utilization scheduling across teams and workloads. Here’s how quotas, fairshare, fractional GPUs, and preemption work together in practice.
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