Vol. I · No. 111SAT, AUG 8, 2026
Archive

The Archive

Search the full wire by company, model, lab, or keyword. Every story we have ever aggregated.

Gemini API Managed Agents: 3.6 Flash, hooks, and more

Google ships Gemini API Managed Agents with Gemini 3.6 Flash and tool-use hooks for production agent deployment.

·

Perplexity’s Personal Computer turns Windows PCs into AI agents

Perplexity has expanded its agentic Personal Computer tool to Windows, allowing computers running the world's most popular OS to be used as a locally run AI system. Like the Mac version that Perplexity launched in April, Personal Computer for Windows operates like a "general-purpose digital worker" that can access local files and apps to perform actions on your behalf, such as creating documents and updating spreadsheets. This launch builds on Personal Computer integrations that Perplexity launched for Microsoft's 365 workspace apps and Teams virtual meeting software in May. Personal Computer...

·

The path to artificial superintelligence

Imagine a healthcare system made up of multiple AI agents: one that manages symptom assessment, another scheduling, a third insurance, and a fourth pharmacy. Each is an expert in its domain. But they all have their own distinct knowledge and objectives. Today they can exchange data, but they are not yet able to actually coordinate…

·

Building the enterprise environment for agentic AI

For the enterprise, the promise of agentic AI is much more than just a better chatbot. It is software agents that execute business tasks end-to-end across people, business workflows, data, and systems. The platform best-suited to run agents is built with proper CPU capacity, resilient data access, policy-aware tool use, observability, memory management, and the…

·

NVIDIA Nemotron 3 Ultra Leads Open Models on Accuracy and Efficiency in Agentic RTL Coding

Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware... Modern chip design is increasingly limited by engineering time. Register transfer level (RTL) development and verification require specialized hardware knowledge, precise reasoning, and repeated interaction with electronic design automation (EDA) tools. LLMs have accelerated code generation, and AI agents extend their impact by using verification feedback to iteratively correct errors. Source

·
30 matches