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NVIDIA releases an extended version of the Agent Toolkit, empowering enterprises to build trustworthy agents based on private data.

NVIDIA’s open-source Agent Toolkit has added core components such as the Agent Knowledge Foundation, integrating the CUDA-X libraries, the Nemotron Retriever and Kumo series of open models, the OpenShell secure runtime, and the NemoClaw blueprint. This enables enterprises to build specialized agents that are auditable, controllable, and capable of deeply understanding business semantics—without migrating data or modifying existing workflows.

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Optimizing the internet for AI agents may make it harder for ordinary users to navigate the web.

With the large-scale launch of personal AI agent apps like OpenAI Dots and Meta Muse, AI agents are emerging as the third category of web visitors, following humans and traditional web crawlers. They perform tasks entrusted by real users—such as booking rooms or comparing prices—at machine speed, but because they don’t fit within the existing “human–machine” dichotomy, they’ve been widely blocked by platforms like Pizza Hut, Yelp, and Amazon. If agent traffic continues to grow, websites may shift toward prioritizing AI agents—for example, Shopify has already created a dedicated checkout channel for them—which could lead to worse interfaces, more frequent verification steps, dynamic pricing, and distorted recommendations for human users. The key issue right now is the still‑unsettled regulatory framework: should agents be allowed to enhance consumers’ bargaining power, or should companies be permitted to keep them out?

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