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      <title>NVIDIA Achieves Leading Agentic Coding Performance on First Agentic AI Benchmark</title>
      <link>https://developer.nvidia.com/blog/nvidia-achieves-leading-agentic-coding-performance-on-first-agentic-ai-benchmark/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 21:12:40 GMT</pubDate>
      <description>AI agents have fundamentally changed the complexity of inference workloads. Until now, the industry has struggled to define a standard for measuring how...</description>
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      <title>NVIDIA Blackwell Leads on First Agentic AI Infrastructure Benchmark</title>
      <link>https://blogs.nvidia.com/blog/nvidia-blackwell-agentperf-artificial-analysis/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 21:00:08 GMT</pubDate>
      <description>AgentPerf from Artificial Analysis, the industry’s first agentic AI benchmark, gives developers, enterprises and infrastructure providers a clear way to compare systems for agentic AI. In the first round of published results, the NVIDIA Blackwell Ultra NVL72 platform delivers leading performance across the agentic AI workloads tested, running 20x more agents per megawatt than NVIDIA […]</description>
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      <title>Building Supercharger: How Rocket Close optimized title operations with agentic AI</title>
      <link>https://aws.amazon.com/blogs/machine-learning/building-supercharger-how-rocket-close-optimized-title-operations-with-agentic-ai/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 20:43:56 GMT</pubDate>
      <description>In this post, we explore how Rocket Close built a solution using Strands Agents, large language models (LLMs), Amazon Bedrock, Amazon Bedrock Knowledge Bases, and Model Context Protocol (MCP) tools. We cover solution features, the rationale for the technology stack, lessons learned, and the business impact at Rocket Close.</description>
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      <title>olmo-eval: An evaluation workbench for the model development loop</title>
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      <dc:creator>Hugging Face</dc:creator>
      <pubDate>Fri, 12 Jun 2026 15:56:10 GMT</pubDate>
      <description></description>
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      <title>Build a meeting prep and follow-up assistant with Amazon Quick and Cisco Webex MCP servers</title>
      <link>https://aws.amazon.com/blogs/machine-learning/build-a-meeting-prep-and-follow-up-assistant-with-amazon-quick-and-cisco-webex-mcp-servers/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 14:49:40 GMT</pubDate>
      <description>This post shows how to build a custom meeting prep and follow-up assistant using Amazon Quick and Cisco Webex MCP servers. From a single prompt, the agent finds an upcoming Webex meeting, reviews prior meeting summaries and transcripts, and pulls related Vidcast highlights and transcript context. It then searches Webex message threads for unresolved follow-ups and creates a concise prep brief. After the meeting, the same assistant can summarize the discussion and identify action items. It can al</description>
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      <title>Deploy Long-Context Reasoning and Agentic Workflows with MiniMax M3 on NVIDIA Accelerated Infrastructure</title>
      <link>https://developer.nvidia.com/blog/deploy-long-context-reasoning-and-agentic-workflows-with-minimax-m3-on-nvidia-accelerated-infrastructure/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 14:43:17 GMT</pubDate>
      <description>As enterprise AI adoption scales, developers are increasingly forced to stitch together fragmented pipelines—separate models for text, vision, and...</description>
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      <title>From PDFs to insights: Architecting an intelligent document processing pipeline with AWS generative AI services</title>
      <link>https://aws.amazon.com/blogs/machine-learning/from-pdfs-to-insights-architecting-an-intelligent-document-processing-pipeline-with-aws-generative-ai-services/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 14:43:11 GMT</pubDate>
      <description>This post outlines the development of a cost-effective and scalable intelligent document processing pipeline on AWS, powered by Amazon Bedrock and its features. BDA is a managed service within Amazon Bedrock that automates the extraction of insights from documents. We demonstrate how BDA extracts and analyzes document content, while Strands Agent hosted on Amazon Bedrock AgentCore Runtime coordinate specialized processing tasks, and Amazon Bedrock Knowledge Base enable contextual understanding a</description>
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    <item>
      <title>Built from the inside out: How AWS Professional Services became a frontier team first</title>
      <link>https://aws.amazon.com/blogs/machine-learning/built-from-the-inside-out-how-aws-professional-services-became-a-frontier-team-first/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 13:00:10 GMT</pubDate>
      <description>AWS Professional Services (AWS ProServe) compressed engagement timelines from months to days, not by adding artificial intelligence (AI) tools to an existing process, but by fundamentally rebuilding how we deliver from the inside out. In this post, we share how AWS ProServe became a frontier team, the practices that enabled it, and what your engineering organization can take from our experience.</description>
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      <title>New OpenAI Academy courses for the next era of work</title>
      <link>https://openai.com/index/academy-courses-applying-ai-at-work</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 10:00:00 GMT</pubDate>
      <description>OpenAI introduces three Academy courses that help people build practical AI skills, create repeatable workflows, and apply agents in everyday work.</description>
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    <item>
      <title>How Preply combines AI and human tutors to personalize learning</title>
      <link>https://openai.com/index/preply</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Fri, 12 Jun 2026 00:00:00 GMT</pubDate>
      <description>Preply uses OpenAI to launch AI-generated lesson summaries, providing personalised feedback and language learning exercises.</description>
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      <title>One-Click Multi-Tenant Security with NVIDIA Quantum InfiniBand</title>
      <link>https://developer.nvidia.com/blog/one-click-multi-tenant-security-with-nvidia-quantum-infiniband/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 19:52:37 GMT</pubDate>
      <description>NVIDIA Quantum InfiniBand now offers intent-based security profiles in Unified Fabric Manager (UFM) that enable multi-tenant fabric security in a single...</description>
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      <title>Extract Data with On-demand and Batch Pipelines Dynamically</title>
      <link>https://aws.amazon.com/blogs/machine-learning/extract-data-with-on-demand-and-batch-pipelines-dynamically/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 19:40:33 GMT</pubDate>
      <description>This post demonstrates an intelligent document processing pipeline that consists of both on-demand inference and batch inference options on Amazon Bedrock to enable the flexibility on the document processing time and cost.</description>
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      <title>Evaluate AI agents systematically with Agent-EvalKit</title>
      <link>https://aws.amazon.com/blogs/machine-learning/evaluate-ai-agents-systematically-with-agent-evalkit/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 15:49:47 GMT</pubDate>
      <description>Agent-EvalKit is an open-source toolkit (Apache 2.0) that makes this evaluation infrastructure available by integrating with AI coding assistants, including Claude Code, Kiro CLI, and Kilo Code. This post walks through how Agent-EvalKit works across its six evaluation phases, using a travel research agent built with the Strands Agents SDK and Amazon Bedrock as a running example.</description>
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    <item>
      <title>Spot trends faster, sort smarter: Unlocking Sparklines and Custom Sort in Amazon Quick</title>
      <link>https://aws.amazon.com/blogs/machine-learning/spot-trends-faster-sort-smarter-unlocking-sparklines-and-custom-sort-in-amazon-quick/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 15:36:31 GMT</pubDate>
      <description>Today, we’re excited to announce two new capabilities that make Quick Sight dashboards even more expressive and business-aligned: sparklines and custom sort for controls. In this post, we walk through both features, what they are, when to use them, and how to configure them, with real-world scenarios that bring them together in a practical, decision-ready dashboard.</description>
    </item>
    <item>
      <title>Can LLMs discover quantum error correction codes?</title>
      <link>https://research.ibm.com/blog/ai-for-qec?utm_medium=rss&amp;utm_source=rss</link>
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      <dc:creator>IBM Research</dc:creator>
      <pubDate>Thu, 11 Jun 2026 15:15:00 GMT</pubDate>
      <description>Researchers at IBM created an LLM-guided evolutionary framework that quickly found 465 distinct quantum error correction code candidates.</description>
    </item>
    <item>
      <title>Optimize blueprint extraction accuracy in Amazon Bedrock Data Automation</title>
      <link>https://aws.amazon.com/blogs/machine-learning/optimize-blueprint-extraction-accuracy-in-amazon-bedrock-data-automation/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 15:11:56 GMT</pubDate>
      <description>Blueprint instruction optimization is a BDA feature that automatically refines your extraction instructions to address this challenge directly. You provide three to ten example documents with expected values, and BDA refines your blueprint instructions to improve accuracy in minutes, not weeks. No separate model fine-tuning is required. By the end of this post, you can optimize your blueprints to improve accuracy, run the optimization workflow through the Amazon Bedrock console or the API, and a</description>
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    <item>
      <title>Save Big and Play Bigger: GeForce NOW Summer Sale Brings Major Membership Savings</title>
      <link>https://blogs.nvidia.com/blog/geforce-now-thursday-summer-sale-2026/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 13:00:17 GMT</pubDate>
      <description>The GeForce NOW summer sale kicked off today with limited-time savings of up to $70 off a 12-month membership, making now the perfect time to upgrade to get the best of the cloud and see just how far Ultimate gaming can go. PC gamers are driven by one thing: the love of the game. But […]</description>
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    <item>
      <title>Prototype and validate fermionic circuits faster with ffsim</title>
      <link>https://research.ibm.com/blog/ffsim?utm_medium=rss&amp;utm_source=rss</link>
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      <dc:creator>IBM Research</dc:creator>
      <pubDate>Thu, 11 Jun 2026 04:00:00 GMT</pubDate>
      <description>Open-source Python library for fast simulation of fermionic quantum circuits enables efficient prototyping and benchmarking for real quantum hardware.</description>
    </item>
    <item>
      <title>How frontier teams are reinventing AI-native development</title>
      <link>https://aws.amazon.com/blogs/machine-learning/how-frontier-teams-are-reinventing-ai-native-development/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:54:42 GMT</pubDate>
      <description>Frontier teams are not just using AI to code faster. They’re redesigning how software gets built. The result is 4.5x productivity gains, in some cases more than 10x.</description>
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    <item>
      <title>Supporting Europe’s work in ensuring a trustworthy AI ecosystem</title>
      <link>https://openai.com/index/supporting-eu-trustworthy-ai-ecosystem</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description>OpenAI supports the EU Code of Practice on AI content transparency, advancing provenance standards and tools to help people understand AI-generated content.</description>
    </item>
    <item>
      <title>How an astrophysicist uses Codex to help simulate black holes</title>
      <link>https://openai.com/index/using-codex-to-simulate-black-holes</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description>Discover how astrophysicist Chi-kwan Chan uses Codex to build black hole simulations, helping scientists study extreme physics and test Einstein’s theory of general relativity.</description>
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    <item>
      <title>BBVA puts AI at the core of banking with OpenAI</title>
      <link>https://openai.com/index/bbva</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description>Learn how BBVA scaled ChatGPT Enterprise to 100,000 employees and partnered with OpenAI to accelerate AI-powered banking transformation worldwide.</description>
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    <item>
      <title>OpenAI to acquire Ona</title>
      <link>https://openai.com/index/openai-to-acquire-ona</link>
      <guid isPermaLink="false">provider-c3f06ceec6a17e4b54</guid>
      <dc:creator>OpenAI</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description>OpenAI plans to acquire Ona to expand Codex with secure, persistent cloud environments, enabling long-running AI agents across enterprise workflows.</description>
    </item>
    <item>
      <title>Profiling in PyTorch (Part 2): From nn.Linear to a Fused MLP</title>
      <link>https://huggingface.co/blog/torch-mlp-fusion</link>
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      <dc:creator>Hugging Face</dc:creator>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description></description>
    </item>
    <item>
      <title>Access OpenAI models and Codex through your Oracle cloud commitment</title>
      <link>https://openai.com/index/openai-on-oracle-cloud</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 20:00:00 GMT</pubDate>
      <description>Access OpenAI models and Codex through Oracle Cloud, using existing commitments to build and deploy AI with enterprise security and governance.</description>
    </item>
    <item>
      <title>For Robotaxis, Safety Must Be Built In, Not Bolted On</title>
      <link>https://blogs.nvidia.com/blog/halos-os-robotaxi-safety/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 19:00:12 GMT</pubDate>
      <description>A car pulls up to the curb. The app says, “Your ride is here.” No one’s in the driver’s seat. For people who live in one of the dozens of cities now hosting robotaxi services, this is already a reality. The robotaxi industry has moved from prototype milestones to commercial operations, with an expanding ecosystem […]</description>
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    <item>
      <title>DiffusionGemma: 4x faster text generation</title>
      <link>https://deepmind.google/blog/diffusiongemma-4x-faster-text-generation/</link>
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      <dc:creator>Google DeepMind</dc:creator>
      <pubDate>Wed, 10 Jun 2026 16:24:11 GMT</pubDate>
      <description></description>
    </item>
    <item>
      <title>Run DiffusionGemma on NVIDIA for Developer-Ready, High-Throughput Text Generation</title>
      <link>https://developer.nvidia.com/blog/run-diffusiongemma-on-nvidia-for-developer-ready-high-throughput-text-generation/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 16:16:30 GMT</pubDate>
      <description>Developers building real-time AI—such as chat assistants, copilots, and agentic workflows—are often constrained by token-by-token generation speed. This...</description>
    </item>
    <item>
      <title>NVIDIA Accelerates Google DeepMind’s DiffusionGemma for Local AI</title>
      <link>https://blogs.nvidia.com/blog/rtx-ai-garage-local-gemma-diffusion/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 16:15:20 GMT</pubDate>
      <description>Today, Google DeepMind released DiffusionGemma — an experimental open model built for exceptionally fast text generation. NVIDIA has optimized DiffusionGemma to run even faster across NVIDIA GeForce RTX GPUs, the NVIDIA RTX PRO platform and NVIDIA DGX Spark systems, from local PCs to the cloud. Rather than generating text one word at a time, DiffusionGemma generates multiple words in parallel to output whole blocks of text, opening a new, low-latency frontier for the kind of single-user workload</description>
    </item>
    <item>
      <title>Stop hand-tuning kernels: How Neuron Agentic Development accelerates AWS Trainium optimizations</title>
      <link>https://aws.amazon.com/blogs/machine-learning/stop-hand-tuning-kernels-how-neuron-agentic-development-accelerates-aws-trainium-optimizations/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 15:26:45 GMT</pubDate>
      <description>Today, we’re announcing the Neuron Agentic Development capabilities: a collection of AI agents and skills that make this possible for developers building on AWS Trainium and AWS Inferentia. In this post, we explain how the Neuron Agentic Development capabilities accelerate the kernel development workflow.</description>
    </item>
    <item>
      <title>Build an AI-Powered Equipment Repair Assistant Using Amazon Bedrock AgentCore</title>
      <link>https://aws.amazon.com/blogs/machine-learning/build-an-ai-powered-equipment-repair-assistant-using-amazon-bedrock-agentcore/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 15:21:35 GMT</pubDate>
      <description>In this post, you build an AI-powered equipment repair assistant using Amazon Bedrock AgentCore that helps farmers and field technicians diagnose equipment problems, identify required parts, and access manufacturer-approved repair procedures through natural language. The solution uses AgentCore Runtime with the Strands Agents SDK, Amazon Nova 2 Lite as the foundation model, Amazon Bedrock Knowledge Base for retrieval-augmented generation (RAG), and AgentCore Memory for conversation persistence.</description>
    </item>
    <item>
      <title>EC2’s formally verified “isolation engine” provides mathematical assurance of virtual-machine isolation</title>
      <link>https://www.amazon.science/blog/ec2s-formally-verified-isolation-engine-provides-mathematical-assurance-of-virtual-machine-isolation</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 15:00:00 GMT</pubDate>
      <description>Splitting the “separation kernel” off from the rest of the Nitro security system and using only a subset of the Rust programming language to code it enabled its formal verification.</description>
    </item>
    <item>
      <title>Graviton5’s improved design increases speed and energy efficiency — beyond Moore’s law</title>
      <link>https://www.amazon.science/blog/graviton5s-improved-design-increases-speed-and-energy-efficiency-beyond-moores-law</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 15:00:00 GMT</pubDate>
      <description>A new chiplet architecture, custom die-to-die connectivity, and support for DDR5-8800 memory and the latest PCIe gen6 interconnects improve performance by 25% for general-purpose and agentic AI workloads.</description>
    </item>
    <item>
      <title>PRC-linked influence operations are targeting AI debates in the US</title>
      <link>https://openai.com/index/prc-linked-influence-operations-ai-debates</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 12:00:00 GMT</pubDate>
      <description>A new report from OpenAI details PRC-linked influence operations using AI to target U.S. tech debates, data center narratives, tariffs, and false claims about ChatGPT.</description>
    </item>
    <item>
      <title>Investing in multi-agent AI safety research</title>
      <link>https://deepmind.google/blog/investing-in-multi-agent-ai-safety-research/</link>
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      <dc:creator>Google DeepMind</dc:creator>
      <pubDate>Wed, 10 Jun 2026 10:21:19 GMT</pubDate>
      <description>Google DeepMind and partners announce a $10M funding call for multi-agent safety research.</description>
    </item>
    <item>
      <title>From data to decisions: how LSEG is scaling trusted AI</title>
      <link>https://openai.com/index/lseg</link>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Wed, 10 Jun 2026 00:00:00 GMT</pubDate>
      <description>See how LSEG uses OpenAI to scale trusted AI across its global business, accelerating insights, shrinking release cycles, and empowering 4,000 employees.</description>
    </item>
    <item>
      <title>NVIDIA Confidential Computing to Help Expand Apple’s Private Cloud Compute</title>
      <link>https://blogs.nvidia.com/blog/nvidia-confidential-computing-apple-private-cloud-compute/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 22:34:27 GMT</pubDate>
      <description>NVIDIA GPUs with Confidential Computing are now used for confidential inference in Apple’s Private Cloud Compute (PCC), as it expands beyond Apple’s data centers to Google Cloud. Unveiled during Apple’s annual WWDC gathering for developers from around the globe, NVIDIA GPUs will support server-side inference for Apple Foundation Models, custom-built by Apple and Google, leveraging […]</description>
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    <item>
      <title>Scale Robot Reinforcement Learning with NVIDIA Isaac Lab on Amazon SageMaker AI</title>
      <link>https://aws.amazon.com/blogs/machine-learning/scale-robot-reinforcement-learning-with-nvidia-isaac-lab-on-amazon-sagemaker-ai/</link>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 20:07:24 GMT</pubDate>
      <description>In this post, we show how to train robot policies for the Unitree H1 humanoid with NVIDIA Isaac Lab on Amazon SageMaker AI across two compute options: Amazon SageMaker HyperPod and Amazon SageMaker Training Jobs.</description>
    </item>
    <item>
      <title>Delivering Lifecycle Control for AI Infrastructure at Scale with NVIDIA DGX Spark Enterprise Manageability</title>
      <link>https://developer.nvidia.com/blog/delivering-lifecycle-control-for-ai-infrastructure-at-scale-with-nvidia-dgx-spark-enterprise-manageability/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 19:00:00 GMT</pubDate>
      <description>As AI infrastructure scales, enterprise expectations for operational maturity are increasing. Organizations expect these systems to be provisionable,...</description>
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    <item>
      <title>Model Quantization: Turn FP8 Checkpoints into High-Performance Inference Engines with NVIDIA TensorRT</title>
      <link>https://developer.nvidia.com/blog/model-quantization-turn-fp8-checkpoints-into-high-performance-inference-engines-with-nvidia-tensorrt/</link>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 18:27:52 GMT</pubDate>
      <description>Converting a quantized checkpoint into an NVIDIA TensorRT engine bridges the gap between model optimization and production deployment, enabling faster...</description>
    </item>
    <item>
      <title>Hands-free first notice of loss: Using Strands Agents and Amazon Bedrock AgentCore Browser Tool for intelligent claims intake</title>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 16:43:28 GMT</pubDate>
      <description>In this post, we demonstrate how a hands-free FNOL intake system combines agents built with the Strands Agents SDK for domain reasoning with Amazon Bedrock AgentCore Browser Tool for live portal interaction. This approach preserves human expertise while removing repetitive screen work.</description>
    </item>
    <item>
      <title>Accelerating Federated Learning Research with AI Agents and NVIDIA FLARE Auto-FL</title>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 16:35:08 GMT</pubDate>
      <description>Federated learning (FL) research often begins with a deceptively simple question: What should we try next? A new aggregation rule, a FedProx coefficient, a...</description>
    </item>
    <item>
      <title>Build an agentic incident triage assistant with Amazon Quick and New Relic</title>
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      <dc:creator>Amazon AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 16:10:37 GMT</pubDate>
      <description>This post shows engineering teams how to apply that principle to one of the most time-sensitive workflows in engineering: incident triage. You will build a custom incident triage assistant agent using Amazon Quick that orchestrates a response with the New Relic Model Context Protocol (MCP) Server and Asana through native integrations. From a single prompt, the Amazon Quick agent investigates the incident, assembles a root cause analysis (RCA) brief with evidence links, and creates a tracked Asan</description>
    </item>
    <item>
      <title>Introducing North Mini Code: Cohere’s First Model For Developers</title>
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      <dc:creator>Hugging Face</dc:creator>
      <pubDate>Tue, 09 Jun 2026 15:56:23 GMT</pubDate>
      <description></description>
    </item>
    <item>
      <title>Fluid, natural voice translation with Gemini 3.5 Live Translate</title>
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      <dc:creator>Google DeepMind</dc:creator>
      <pubDate>Tue, 09 Jun 2026 15:16:25 GMT</pubDate>
      <description>Gemini 3.5 Live Translate brings near real-time, natural speech translation to Google AI Studio, Google Translate and Google Meet.</description>
    </item>
    <item>
      <title>Evaluate Clinical ASR Models Faster with Agent Skills and NVIDIA Nemotron Speech</title>
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      <dc:creator>NVIDIA AI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 15:00:00 GMT</pubDate>
      <description>Training a speech AI model to correctly recognize or synthesize clinical terminology is surprisingly difficult. Drug names like Acetaminophen, Amlodipine,...</description>
    </item>
    <item>
      <title>Introducing Gemma 4 12B: a unified, encoder-free multimodal model</title>
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      <dc:creator>Google DeepMind</dc:creator>
      <pubDate>Tue, 09 Jun 2026 14:10:19 GMT</pubDate>
      <description></description>
    </item>
    <item>
      <title>Powering the future of robotics in Europe</title>
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      <dc:creator>Google DeepMind</dc:creator>
      <pubDate>Tue, 09 Jun 2026 14:02:33 GMT</pubDate>
      <description></description>
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      <title>How engineers at Nextdoor use Codex to build without limits</title>
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      <dc:creator>OpenAI</dc:creator>
      <pubDate>Tue, 09 Jun 2026 12:00:00 GMT</pubDate>
      <description>How engineers at Nextdoor use Codex with GPT-5.5 to investigate hard-to-reproduce issues, build across platforms, and focus on product outcomes.</description>
    </item>
    <item>
      <title>How an Agent Built a 3D Paris Gallery by Chaining Two Hugging Face Spaces</title>
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      <dc:creator>Hugging Face</dc:creator>
      <pubDate>Tue, 09 Jun 2026 10:46:19 GMT</pubDate>
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