Agencies look to AI to modernize legacy processes, but disparate data and systems pose a challenge, says Salesforce's federal data and integration director.
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
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
Insider Brief PRESS RELEASE — Turnout, an AI-powered consumer advocacy service that reimagines how Americans navigate complex government and financial bureaucracies, has announced a $35 million Series A, bringing the total company valuation to $400 million. The round was led by HighPost Capital, with participation from Shine Capital, LGVP, Mangusta Capital, Honeystone Ventures, and investor Omri Casspi. […]
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 […]
NASA has relied on the core Flight System framework to run everything from telescopes to avionics to command and control instruments since the early 2000s.
We implement an end-to-end workflow for Salesforce CodeGen, loaded from Hugging Face. We move past basic inference by adding function extraction, syntax checking, static safety checks, and unit-test validation. We rerank best-of-N candidates, compose multi-turn program synthesis, and experiment with prompt styles. We finish by visualizing a mini benchmark and exporting the generated artifacts as reusable files.
The post Salesforce CodeGen Tutorial: Generate, Validate, and Rerank Python Functions With Unit Tests and Safety Checks appeared first on MarkTechPost.
