Nous Research added a one-click setup flow in Hermes Desktop that reads a user’s hardware, selects a compatible open-weights model, downloads the weights, and configures the local inference runtime. The flow runs on macOS 12+ and the local setup can be accessed under Settings → Providers → Local Models. As a result, users no longer manually choose quantization, context length, or GPU offload settings before running a model locally, and the app auto-verifies a bundled llama.cpp build for their hardware.
Tech executives including OpenAI’s Sam Altman urged more AI infrastructure inside a G20 event in Chapel Hill, N.C., while hundreds of protesters outside criticized AI and the data center expansion tied to it. Protesters cite data center impacts such as pollution and jobs, and activists staged 142 demonstrations across 42 states in July. As a result, data centers are becoming a major reputational and political flashpoint, with growing local moratoriums or zoning limits and continued public opposition to new sites.
NVIDIA released Personal AI Router (PAIR), a virtual inference router that discovers compatible local machines and schedules independent inference requests across them while proxying existing Ollama and LM Studio endpoints. In its five-subagent demo using Qwen 3.6 35B A3B, it reduced average runtime from 18 minutes on one RTX Spark laptop to 8 minutes 48 seconds on a three-device cluster. This changes local multi-agent inference by routing each request to a single eligible node instead of letting requests contend on one machine, without pooling VRAM or sharding a single request.
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