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Chad Collins

1,104 articles published

Stop Identity Abuse and Runtime Threats to AI: Practical Controls for Cloud, Kubernetes and LLM Workloads

What Happened Two themes dominate recent defensive research: attackers are exploiting trusted collaboration and identity channels to harvest credentials and tokens, and enterprise runtime gaps across cloud and Kubernetes are increasing exposure for workloads — including AI models and agentic components. Unit 42 documented identity abuse via trusted collaboration channels where impersonation, malicious…

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How AWS Service Updates Reduce Operational Risk and Speed AI Deployments

What Happened Amazon EKS added managed certificate authority (CA) rotation with automated lifecycle safeguards (expiration notifications, automatic successor CA appending/activation, rollback). AWS updates managed components; customers must replace worker nodes and update external clients. Available in all commercial Regions via CLI, APIs, CloudFormation or Console [1]. CloudFront now supports Origin Access…

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Prepare CI, Billing and Security Workflows for GitHub’s VS2026 Runners and Code Quality Changes

What Happened GitHub published a set of coordinated updates that affect CI runners, code‑scanning workflows and audit telemetry: The Windows 11 arm64 image with Visual Studio 2026 is now generally available; workflows can opt in immediately with runs-on: windows-11-vs2026-arm. GitHub will migrate the existing windows-11-arm image to Visual Studio 2026 by default between…

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Cut Hallucinations, Improve Retrieval, and Harden Agent Safety — Actionable Research Findings for Production AI

What Happened A large set of new papers expands practical techniques across retrieval, safety, recurrent computation, multimodal grounding, low‑resource language tooling, and domain‑specific models. Selected highlights: Retrieval: Dual‑Bounded Relational Recall (DBRR) improves evidence recovery by splitting budget between seed passages and graph‑adjacent context, boosting full supporting‑evidence recall on HotpotQA by +23.8pp vs flat…

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Data Science, Python & R — August 20, 2026

What Happened The PyTorch community published its North America conference program highlighting platform and research priorities that signal where Python tooling investment is concentrating: native hardware support, agent workloads, model customization, improved linear algebra for research, and open-science workflows. The conference program lists speakers across PyTorch Foundation, major cloud and hardware vendors, and applied AI…

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How to Build Reliable, Secure Agentic AI Systems: Lessons from Recent Agent Framework Updates

What Happened Three recent releases across the agent ecosystem illustrate practical fixes and feature directions you should expect when building production agent systems. LangChain-style agent fixes: a patch rejected synchronous Agent.run_sync() calls during agent execution to prevent reentrancy/deadlock, stopped sending empty Anthropic “thinking” blocks, and relaxed FunctionModel to accept any callable as a…

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Illustration for the Kimbodo News & Research briefing “How to Pick GPUs, Cloud AI Services and Deployment Tooling for Production-Grade AI” (AI Infrastructure, GPUs & Deployment).

How to Pick GPUs, Cloud AI Services and Deployment Tooling for Production-Grade AI

What Happened Recent vendor and platform updates have hardened the production story for AI across cloud, edge and agentic workflows. Key advances include built-in agent policy enforcement and autoformalization (Amazon Bedrock AgentCore + Dogwood) for real‑time governance [1]; enterprise patterns for scaling agentic AI that separate control and execution planes and centralize identity, policy and…

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How Recent Llama.cpp and Inference-Engine Improvements Make On‑Prem and Edge LLMs More Deployable and Secure

What Happened Over the past series of commits, the llama.cpp/ggml codebase received multiple concrete engineering changes focused on quantized inference, cross‑platform acceleration, testing and supply‑chain assurances. Key changes include: FA dequant / quant K/V changes: the code now implements dequant q8_0 KV once in coopmat1, enforces KV‑cache layout for FA dequant paths, skips…

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How to Cut LLM Workflow Costs with Hybrid Streaming and Agentic Orchestration

What Happened Google described a production pattern for building cost-effective, high-throughput generative AI workflows in Dataflow using a hybrid architecture: cheap CPU inference for most events, and agentic LLM execution only for the small subset that needs reasoning or remediation [1]. The example pipeline ingests messages from Pub/Sub into an Apache Beam/Dataflow streaming job. A…

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AI Agents Are Entering Critical Workflows — How Businesses Can Adopt Them Without Losing Control

What Happened Several technology shifts moved from experimental to operational at the same time: AI agents are being connected to money, enterprise apps, research workflows, physical infrastructure, and consumer devices. AI agents gained more authority. Binance’s Agent OS now integrates with ChatGPT, Claude Code, and Cursor, allowing AI agents to participate in trading…

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Use AWS’s Latest Updates to Add Fresh Web Grounding, Safer Agents, and Better Observability Without Sacrificing Control

What Happened Amazon Bedrock Web Search — external web access: Bedrock Web Search, originally in‑AWS only, gained an external_web_access option so server‑side grounding can retrieve live public web content. Enable by granting the IAM permission bedrock-websearch:ExternalWebAccess and leaving external_web_access true; set it false to restrict retrieval to Amazon’s in‑AWS index and knowledge graph.…

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