Solving an ARD problem in AI: Agentic Resource Discovery

The resurgence of CPUs in AI inference tasks could reshape the semiconductor landscape, challenging Nvidia's dominance and impacting market dynamics. The post Chipmakers renew performance tussle as CPUs challenge Nvidia’s dominance appeared first on Crypto Briefing.

Enterprises implementing agentic AI face a challenge: Which tools should they allow their agents to use, where can they be found, and how can they be used safely? A new protocol, Agentic Resource Discovery, or ARD, aims to let agents answer those questions for themselves. Behind it are Google, Microsoft, Cisco, Nvidia, Salesforce and others. ARD aims to standardize the way that tools and services are shared across systems within a corporate domain. For example, when investigating a production problem, an agent may want to query engineering documentation and open support tickets, deployment history and observability systems, all of which could be managed by different registries and across different silos. There is no common layer that pulls them together. ARD has been designed to be that layer. It operates across two levels. Catalogs and Registries. In the first, an organization publishes a catalog setting out its available capabilities. The Registries layer act as a form of search engi

An IT executive changing jobs usually attracts little attention outside a narrow group of people, but Noam Shazeer’s move from Google to OpenAI is as momentous as any high-value soccer transfer. He announced the news in a post on X: “I’m excited to share that I’ll be joining OpenAI and look forward to working with the exceptional team there.” Shazeer initially achieved fame as one of the eight co-authors of the influential AI paper Attention Is All You Need, published when he was working at Google Brain. He is also one of the creators of the transformer technology that lies at the heart of modern AI models. He left Google when the company failed to back his chatbot Meena and was tempted back when Google subsequently bought the company he founded, Character.AI, for $2.7 billion. That company achieved notoriety when it was sued by a grieving mother, who alleged that a Character.AI chatbot had contributed to her son’s death by suicide. The company subsequently settling out of court. Shaze

An IT executive changing jobs usually attracts little attention outside a narrow group of people, but Noam Shazeer’s move from Google to OpenAI is as momentous as any high-value soccer transfer. He announced the news in a post on X: “I’m excited to share that I’ll be joining OpenAI and look forward to working with the exceptional team there.” Shazeer initially achieved fame as one of the eight co-authors of the influential AI paper Attention Is All You Need, published when he was working at Google Brain. He is also one of the creators of the transformer technology that lies at the heart of modern AI models. He left Google when the company failed to back his chatbot Meena and was tempted back when Google subsequently bought the company he founded, Character.AI, for $2.7 billion. That company achieved notoriety when it was sued by a grieving mother, who alleged that a Character.AI chatbot had contributed to her son’s death by suicide. The company subsequently settling out of court. Shaze

Amazon Web Services is in early talks to sell its proprietary Trainium AI chips to external companies for use in their own data centers, marking a significant potential escalation in the rivalry between AWS and Nvidia. The move was confirmed by Amazon’s AI chief Peter DeSantis, who declined to name prospective buyers, and by AWS […]

Zaro.ai, a London-based enterprise AI startup, has emerged from stealth with $5.1 million in pre-seed funding led by Cherry Ventures. The company was founded by Michael Bajwa and Qian Zheng, who previously built AI agent products at Convergence before it was acquired by Salesforce, where the team worked on Agentforce. Additional investors include Thomas Wolf […]

Google, Microsoft, OpenAI, and others want to help enterprises demonstrate that their AI applications are behaving themselves through the creation of a new foundation. The Appia Foundation will, it explained rather impenetrably, “establish modular specifications that provide a connecting layer to bridge foundational global standards with practical, trusted assessments across the global AI value chain.” Those specifications will help AI users ascertain whether the systems they are using meet all the obligations that apply to them in the form of standards and regulations, it said. It’s a challenging task with so much regional variation in requirements, and where the EU, for example, is more tightly controlled than the US. The Foundation has established a set of criteria to demonstrate conformity with what is expected. There are two layers: the Requirements and Guidance layers will help users determine what is actually required, while the Assessment Enablement layer will look at how those

Google, Microsoft, OpenAI, and others want to help enterprises demonstrate that their AI applications are behaving themselves through the creation of a new foundation. The Appia Foundation will, it explained rather impenetrably, “establish modular specifications that provide a connecting layer to bridge foundational global standards with practical, trusted assessments across the global AI value chain.” Those specifications will help AI users ascertain whether the systems they are using meet all the obligations that apply to them in the form of standards and regulations, it said. It’s a challenging task with so much regional variation in requirements, and where the EU, for example, is more tightly controlled than the US. The Foundation has established a set of criteria to demonstrate conformity with what is expected. There are two layers: the Requirements and Guidance layers will help users determine what is actually required, while the Assessment Enablement layer will look at how those