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All news with #agentic ai tag

850 articles · page 21 of 43

AWS Neuron: Agentic Development for Trainium Kernels

🔧 AWS announced Neuron Agentic Development, an open-source set of agents and skills that bring agentic coding capabilities to development on AWS Trainium and AWS Inferentia. The initial release focuses on Neuron Kernel Interface (NKI) kernel development, enabling an agentic IDE to author, debug, profile, and analyze custom kernels. Developers can request kernels from natural-language descriptions, get automated fixes for compilation errors, and receive performance reports identifying bottleneck lines of code.
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Agents Can Now Provision Cloudflare via Stripe Integration

🤖 Agents can now provision Cloudflare resources and complete billing through Stripe Projects, enabling end-to-end deployment without manual dashboard steps. Using a co-designed protocol, an agent can discover available services, create or link a Cloudflare account, and receive API credentials to deploy code and register domains. Stripe supplies a payment token (not raw card data) with a default $100/month cap, and human approval can be requested when needed. Any platform with signed-in users can adopt the same orchestration flow.
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Amazon Quick adds Microsoft 365 extensions in preview

🧩 Amazon Quick has introduced preview Microsoft 365 extensions for Excel, PowerPoint, and Word that let the service perform tasks directly inside users’ Microsoft 365 environments. The Excel extension supports complex spreadsheet analysis including pivot tables, charts, and data import/cleaning. PowerPoint enables template-driven deck creation and refinement from Quick data, while Word gains formatted document generation, sweeping edits with track changes, and reviewer participation in comments. The extensions are available in multiple AWS regions for early access.
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Re-permissioning to curb excessive AI agent autonomy

⚖️ Re-permissioning aligns AI agents' access with clear operational needs so they execute tasks safely rather than accumulate unnecessary powers that enable unauthorized actions. As agents evolve from responders into execution engines, interoperability standards like MCP and agent-to-agent flows expand reach but also multiply where things can go wrong. Organizations should enforce continuous permission audits, mandatory human-in-the-loop checks for sensitive operations, strict least-privilege context sharing, and vet integrations, libraries and third parties while running tabletop prompt-injection exercises to validate controls and prevent data exposure or integrity-impacting changes.
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Securing and Governing AI Agents Through an AI Gateway

🔒 Palo Alto Networks announced its intent to acquire Portkey and integrate Portkey’s AI Gateway into Prisma AIRS to provide a centralized control plane for agentic AI. The combined platform will offer a unified API to thousands of LLMs, an agent registry, semantic routing, caching and runtime protections such as Agent Artifact scanning and automated red teaming. Integration with CyberArk is intended to enforce agent identity and least‑privilege controls. The goal is to enable enterprises to move autonomous workloads from development to production with consistent governance and minimal performance tradeoffs.
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Google Cloud Next '26: Agent, Data, Compute for Startups

🚀 Google Cloud Next ’26 introduced an integrated AI stack for startups centered on Gemini Enterprise, an end‑to‑end agent lifecycle platform with an Agent Development Kit, Agent Studio, and production runtimes that support sub‑second starts and persistent memory. The Agentic Data Cloud and zero‑ETL features enable cross‑cloud data access and high‑accuracy text‑to‑SQL to avoid costly migrations. Infrastructure updates (TPU 8t/8i, Axion N4A, new networking machines, and GKE sandboxes) plus agentic security integrations and a $750M partner fund aim to accelerate prototyping, secure production deployments, and enterprise go‑to‑market.
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Autonomous Exposure Validation: Webinar on AI-Driven Threats

🔒 In February 2026 researchers flagged a major shift: threat actors now deploy custom AI agents that automate attacks through the kill chain, from Active Directory mapping to rapid Domain Admin takeover. Join a technical webinar with Picus Security leaders Kevin Cole and Gursel Arici for a deep dive into Autonomous Exposure Validation. Learn how to safely ingest threat intelligence, simulate attacks, and close the gap between CTI, Red, and Blue teams to speed detection and remediation.
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AI-Powered Honeypots: Turning the Tables on Malicious Agents

🛡️ Generative AI enables defenders to deploy large numbers of convincing, adaptive honeypots — from Linux shells to IoT devices — using simple text prompts. These AI-driven decoys are particularly effective against automated attackers that favor speed over stealth, allowing analysts to observe tactics and tooling in real time within a controlled environment. By exploiting the lack of awareness in AI agents, organizations can shift from passive detection to active manipulation, turning attacker automation into a defensive liability. Prototype implementations show how a listener, simulated vulnerability, and an AI responder combine to emulate targeted systems at scale.
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Public Sector Embraces Agentic AI: Highlights from Next '26

🤖 At Google Cloud Next, public sector leaders showcased how they are using AI agents to boost productivity and mission impact across government and research organizations. Google introduced the Gemini Enterprise Agent Platform—an evolution of Vertex AI—plus the Gemini Enterprise App with Gemini 3.1 Pro and an Agent Designer for inspectable, schedule‑based workflows. The announcement also covered AI infrastructure (TPU 8 series), an Agentic Data Cloud, enhanced security and Agentic Defense, partner initiatives, and upskilling through the GEAR program.
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Google-managed MCP Servers Now Available Across Google Cloud

🔌 At Google Cloud Next ’26, Google announced that more than 50 Google-managed MCP servers are generally available or in preview, enabling AI agents to connect securely to Google and Google Cloud services without local MCP deployments. The managed endpoints integrate with major agent runtimes and frameworks including Gemini CLI, LangChain, ADK, and others, supporting Resources and Prompts as protocol primitives in addition to Tools. The offering emphasizes enterprise-grade security, governance, and observability through native IAM controls, Model Armor content safety, OpenTelemetry tracing, and Cloud Audit Logs.
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Amazon Bedrock Offers OpenAI Models, Codex, Managed Agents

🚀 Amazon announced that Amazon Bedrock now provides access to the latest OpenAI models, Codex, and a Managed Agents offering in limited preview. OpenAI models and Codex integrate with Bedrock controls such as IAM, AWS PrivateLink, encryption, and CloudTrail, and usage can be applied toward existing AWS cloud commitments. Managed Agents run on Bedrock AgentCore, log actions per agent, and keep inference within the customer's AWS environment.
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AWS Launches Amazon Connect Decisions for Supply Chains

🚀 AWS announced the general availability of Amazon Connect Decisions, an agentic AI planning and intelligence solution that helps supply chain teams shift from firefighting to proactive operations. The service combines 30 years of Amazon operational science with 25+ specialized supply chain tools so persistent AI teammates can adapt to business rules, learn from human decisions, and continuously improve. These agents harmonize demand signals into consensus forecasts, generate constraint-aware supply plans, and run 24/7 monitoring that detects variances, performs automated root-cause analysis, and triages exceptions, surfacing only prioritized, actionable recommendations to help prevent stockouts and reduce working capital waste.
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CISOs Rethink Identity as Agentic AI Raises Stakes

🛡️ Identity management is changing as AI agents introduce a new class of non‑human identities that can act, decide, and access resources at machine speed. Experts including Dustin Wilcox and Michael Adams recommend an identity-first security posture built on clean directories, enforced least privilege, and clear offboarding. They warn that legacy models and inventory processes won’t track proliferating tokens and agents, so organizations should catalog non‑human identities, assign ownership, and treat MFA as a baseline while moving toward phishing‑resistant methods and continuous verification.
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Future of Google AI Infrastructure: Scaling for Agents

🚀Google announced a broad expansion of AI infrastructure at Google Cloud Next, presenting the AI Hypercomputer — an integrated stack of dedicated hardware, software, and flexible consumption models. The release highlights new accelerators including TPU 8t and TPU 8i, A5X GPU instances, and Axion N4A CPUs, plus megascale Virgo networking and storage improvements. These changes target agentic workloads to improve latency, utilization, and cost-efficiency for enterprise and consumer AI.
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Google Cloud Next 26: New Compute and Fluid Compute

⚙️ At Google Cloud Next '26, Google announced Fluid Compute and a broad set of compute, networking, and storage updates to support both traditional and agentic AI workloads with better performance and lower cost. Key moves include GA of the Arm-based Axion N4A, a GKE Agent Sandbox running on Axion, previews of bare-metal Axion C4A.metal and network-optimized C4N, and expanded Flexible Committed Use Discounts. The changes emphasize elastic scaling for spiky agent workloads, isolated runtime sandboxes, and higher I/O and VM-to-VM bandwidth to reduce contention and TCO.
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AI as Manager: Elevating the SOC Tier 1 Analyst Role

🤖 AI agents are shifting the Tier 1 SOC analyst role from manual triage to oversight and decision-making. Instead of spending hours pivoting across logs and telemetry, analysts can delegate evidence collection to agentic AI that queries systems, correlates signals and builds evidence chains in real time. The human role becomes orchestration—reviewing outcomes, validating uncertainty and aligning actions with business risk. Trust is earned via transparency, staged deployments and practitioner-led adoption.
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Autonomous AI Agents Create a New Enterprise Attack Surface

🔒Attackers are increasingly hijacking legitimate AI agents and compromised credentials to extract sensitive information, turning in-house assistants into active threats. These agents become 'agentic endpoints'—autonomous identities with broad privileges that often evade traditional controls by using plugins, extensions, and stolen API tokens. Organizations need a consolidated security platform, continuous verification through PAM and Zero Trust, and board-level governance to manage this accelerated, AI-driven risk.
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Amazon Quick Integrates Visier's Vee for Workforce AI

🔗 Amazon Quick now integrates with Vee, the AI assistant from Visier, via the Model Context Protocol (MCP), enabling HR, finance, and operations leaders to access governed workforce intelligence directly inside the Quick workspace. After connecting to Visier’s remote MCP server, users can ask natural-language questions about headcount, attrition, tenure, and open requisitions and receive answers grounded in Visier’s governed data model. Vee can also be invoked from automated Quick Flows to run recurring reviews or draft documents, and Quick augments responses with enterprise knowledge from Quick Spaces—such as budgets, policies, and plans—so answers reflect the broader organizational context. The Visier integration is available in all AWS Regions where Amazon Quick is offered.
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Google Cloud Next '26: Agentic Era and 260 Announcements

🤖 Google Cloud Next '26 in Las Vegas showcased a broad enterprise push into the agentic era, with over 32,000 attendees and 260 product, partner, and customer announcements. Highlights include the new Gemini Enterprise Agent Platform, the Gemini Enterprise app, 8th-generation TPUs, and a host of agent-focused capabilities for development, runtime, memory, observability, and governance. The week emphasized production readiness, cross-cloud data integration, and strengthened security through the Wiz acquisition and Model Armor integrations.
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Amazon Connect adds eight AI agent performance metrics

📊 Amazon Connect now exposes eight new metrics to evaluate AI agent outcomes, including goal success rate, faithfulness score, and tool selection accuracy. These metrics give contact center teams visibility into whether AI-driven interactions resolve customer requests and where contextual hallucinations occur. Metrics are accessible from the AI Agent Performance dashboard, the GetMetricDataV2 API, or a zero-ETL data lake for custom reporting. This capability is available in all Regions that support Amazon Connect AI Agents.
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