Perplexity trusts GPT-6 Astra with end-to-end systems
Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.
Perplexity uses Astra to write communications, change software, and monitor production systems, and checks in much less frequently than with earlier models.
GPT‑6 Astra improves Devin’s ability to test software and show that it works, with the goal of helping engineers review less code and ship more.
Combine zero-shot forecasting with Amazon Chronos2 and multi-agent orchestration on Amazon Bedrock AgentCore to turn demand forecasts into validated purchase orders. No per-product model training, with business rules, auditability, and cost that scales to zero.
近日,以“赋能AI计算的未来”为主题的Arm Everywhere China年度大会盛大召开。在AI从生成式走向智能体的关键节点上,产业界对计算底座的关注度正在急剧升温。行业需要一个既能提供开发者所需一致性,又能赋能差异化创新的平台。Arm正在试图证明,它就是这样的平台。
Checking agent-generated code usually means hopping between tabs. Learn how to view diffs, run terminal commands, and preview web apps side by side in the GitHub Copilot app. The post GitHub Copilot app for Beginners: Using the diff, terminal, and browser appeared first on The GitHub Blog .
This blog post is the fourth and final installment of The Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry. The post The Economics of Agent Optimization: How AI agent governance controls cost and proves ROI appeared first on Microsoft Azure Blog .
Meet the Data agent in ChatGPT Work. Connect company data, uncover insights, and build interactive dashboards with AI using natural language.
Introducing ChatGPT for Financial Services, combining built-in financial data and GPT-6 Astra for research, modeling, and client-ready materials.
日前,Arm 控股有限公司举办 Arm Everywhere China 年度大会,以“赋能 AI 计算的未来”为主题,吸引近 2000 名来自产业链上下游的行业领袖、开发者及生态伙伴报名参会,共同探讨智能体时代的计算创新与产业发展机遇。
Enterprise work spans messages, decisions, projects, and obligations that change over time. An AI agent that starts without this context must reconstruct it...
AI agents are learning to do more by working together. A lead agent can break a complex task into smaller jobs and assign those jobs to specialized subagents....
AI cost optimization goes beyond model selection. Discover how context engineering in Microsoft Foundry helps lower AI costs by improving knowledge retrieval, tool selection, memory, and agent performance at scale. The post The Economics of Agent Optimization: Context engineering for enterprise AI agents appeared first on Microsoft Azure Blog .
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On July 28, 2026, MCP made its protocol core stateless, removing the initialize handshake and session header. This post maps the MCP 2026-07-28 specification to the AWS Well-Architected Agentic AI Lens, pillar by pillar, and shows why the stateless design lets you delete the sticky sessions and session stores your MCP servers needed on AWS.
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Most teams give AI agents either full access or read-only, leaving value unused or risk unmanaged. This post describes graduated autonomy, an architectural pattern in which agents earn expanded permissions through sustained reliability and lose them when performance degrades, built on Amazon Bedrock AgentCore, Amazon DynamoDB, and AWS CodePipeline.
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Cloudflare's new Bot Preference Sync automatically aligns your robots.txt file with your AI bot policies for Search, Agent, and Training. Easily manage which bots access your content without maintaining static files.
With native vector search in Amazon DynamoDB, you can store vector embeddings alongside your operational data in a single table. This post shows how to build a unified AI agent architecture where an Amazon Bedrock agent uses one DynamoDB table for both structured lookups and semantic search, with a DynamoDB Streams pipeline that keeps embeddings in sync.
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