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Nov 12Thu
  1. AWS Machine Learning Blog58

    Introducing the Web Search API on Amazon Bedrock AgentCore

    AWS announced the Web Search API on Amazon Bedrock AgentCore, which lets developers call the InvokeWebSearch operation directly from AWS SDKs or the AWS CLI with SigV4-signed IAM credentials, without creating a gateway or other resources. It returns up to 25 ranked results from an Amazon-operated web index, each with a text extract and, when available, title, URL, and publication time, and supports domain and publication-date filtering. It is available in six Regions and billed at $7 per 1,000 queries, complementing the existing AgentCore Gateway path.

  2. AWS Machine Learning Blog46

    Detecting and recovering from silent data corruption on Amazon SageMaker HyperPod

    This post describes adding three checks to a PyTorch DDP training loop to detect silent data corruption (SDC), where hardware such as a GPU returns a wrong but plausible number without raising an error: a non-finite gradient check, a ring replay audit that recomputes another node's micro-batch and compares loss bits and gradient fingerprints, and a weight fingerprint comparison after the optimizer step. When a check fires, the suspect rank is mapped to its node via the Kubernetes node name, the node is cordoned, and SageMaker HyperPod replaces it, with training resuming from a checkpoint saved before the suspect window. The checks were tested with software-injected faults on a HyperPod cluster with 4 ml.p5.48xlarge instances (32 NVIDIA H100 GPUs) and repeated on three instances, with full code in an accompanying GitHub repository.

  3. AWS Machine Learning Blog34

    Semantic diffing of formal policies with anti-unification

    The post describes an open source engine that computes semantic diffs of formal policies by anti-unification over an e-graph, using declared algebraic laws and domain rewrites so that shared structure appears once and each genuine disagreement is kept as a Variants node. Worked examples cover SMT-LIB-style rules, Cedar and Dogwood authorization policies, and OpenShell and CEL encodings, showing how presentational differences are absorbed while real bugs such as a weakened conjunction or a dropped guard remain visible. The engine builds from source with a pinned Rust toolchain and reads a single S-expression file.

  4. AWS Machine Learning Blog38

    OpenAI Codex on Amazon Bedrock

    This AWS post explains how developers can run OpenAI Codex on the workstation while routing model inference through Amazon Bedrock using supported OpenAI models such as GPT-5.6 Sol, Terra, and Luna. It compares three access paths—Native AWS Access with IAM Identity Center, AgentCore Gateway, and an LLM Gateway—and recommends starting with a small, least-privilege pilot before expanding. It also covers validation steps, identity-isolation testing, OpenTelemetry and CloudWatch observability, cost allocation, plugins, hooks, MCP servers, phased rollout, and cleanup.

  5. Databricks Blog8

    Brickster Voices: Meet Alasdair Anderson

    In this Q&A, Databricks Lead Solutions Architect Alasdair Anderson describes balancing hands-on coding with coaching colleagues, and explains that after two decades in financial services he joined Databricks because tasks that took days or weeks on traditional stacks ran in seconds or minutes. He discusses how tools like Agentbricks, Lakebase and AI Apps reshaped FSI work within 12 months, and how Apache Spark, Unity Catalog and Unity Gateway support governed AI/ML workloads across banking, insurance and capital markets.

  6. Databricks Blog28

    Detecting credential-driven attacks on Databricks

    Databricks describes how credential-driven attacks unfold on its platform in six non-linear stages—initial access with valid credentials, environment mapping, credential harvesting, execution via UDFs and jobs, persistence, and data collection with cleanup—and what to look for in verbose audit logs at each stage. The post explains how to investigate these attacks with Genie and the Detection App, how to respond once a compromise is confirmed, and which preventive controls such as context-based ingress, least privilege, and credential rotation limit what a stolen credential can do.

  7. AWS Machine Learning Blog38

    ICYMI: What landed for AI builders in October 2026

    AWS recaps its October 2026 releases for AI builders, including new Amazon Bedrock models such as Claude Haiku 5.5, OpenAI GPT-6.1 Terra, Amazon Nova 2.5 Sonic, GLM 5.3, and TwelveLabs Pegasus 1.5. Amazon Bedrock AgentCore gains a generally available CLI 1.0, model fallback and InvokeModel support in Gateway, Step Functions workflows as agent tools, and usage-based memory pricing, while Strands adds Bidi Agents, the Box local sandbox, red teaming in Strands Evals, and Decider on Gemma 4. The post also covers structured outputs for Claude models, Web Search domain filtering, a new Guardrails Standard tier for contextual grounding, and Amazon Bedrock cost breakdowns in AWS billing tools.

  8. ElevenLabs Blog22

    Voice cloning for content creators: Scale your content workflows with voice AI

    This guide explains how voice cloning turns a recorded voice sample into a digital replica that can narrate new scripts for videos, podcasts, courses, and social clips, covering the capture-modeling-generation process and the difference between Instant and Professional Voice Cloning. It lists criteria for choosing a tool—voice fidelity, delivery control, language coverage, consent safeguards, export options, and commercial licensing—and outlines workflows for podcasters, YouTube, short-form content, courses, and audio articles. It also describes ElevenLabs' consent confirmation, voice verification, restricted voices, and traceability safeguards, plus which plan tiers include cloning and commercial rights.

  9. Modal Blog58

    Modal becomes a gVisor maintainer

    Google is donating gVisor, including its name and trademarks, to the CNCF, and the project is moving to a maintainer-led governance model; Modal is one of three companies, alongside Ant Group and Tines, committing to join gVisor's maintainers, with OpenAI, Tencent and NVIDIA continuing their contributions. Modal says it has run gVisor as its major container runtime since the beginning, launching upwards of 40 million gVisor containers a day for GPU inference, multi-node training, AI coding agents and sandboxes, and has contributed upstream since 2023. The post details upstreamed work including nvproxy GPU support, an rdmaproxy device proxy for RDMA, snapshot/restore, and filesystem and memory performance improvements, and outlines future plans such as multi-GPU memory snapshots and GPUDirect Storage.

  10. Browser Use Blog34

    How to Use Custom Proxies with Browser Use

    This tutorial shows how to connect a third-party (bring-your-own) proxy to Browser Use Cloud by supplying the provider's host, port, protocol, and credentials when creating an agent run or cloud browser, then verifying the browser's exit IP and country via ipwho.is. It also demonstrates using the same credentials with Playwright both locally and against a Browser Use cloud browser over CDP, and compares managed proxy pricing ($5/GB) with BYO (provider rate plus $0.20/GB Browser Use egress). The guide includes setup steps, code samples, a troubleshooting table, and production tips such as preserving cookies alongside sticky sessions and stopping unused browsers.

  11. Pydantic AI Articles34

    What we found testing OpAMP clients against the spec

    Pydantic describes how its Logfire Fleet Management OpAMP clients for Rust, Go, Node.js, Python, Java and .NET share one Rust protocol core, run as WebAssembly or a native library, and are checked against roughly 300 normative spec statements, TLA+ models, Kani and Verus proofs, black-box conformance and fault testing. Running the same scenarios against upstream OpenTelemetry clients surfaced bugs in the Collector's OpAMP extension and Supervisor and in the Java, Python and .NET clients, including instance UID handling, reconnect and status reporting, capability declarations and startup panics, plus one critical security vulnerability that the core is not affected by.

  12. AWS Machine Learning Blog12

    The attendee’s guide to the AWS re:Invent 2026 AI/ML track

    AWS will hold re:Invent from November 30 to December 4, offering over 2,000 learning sessions, with more than 140 in the AI/ML track spanning breakouts, chalk talks, builder sessions, workshops, code talks, and lightning talks. The guide organizes AI/ML sessions around the AWS AI stack—global infrastructure, AI chips (Trainium and NVIDIA GPUs), data foundation, models/training/inferencing (Amazon Bedrock and SageMaker AI), agent development and management (AgentCore), and agentic solutions—plus sessions on trust in agents, sustainability, and Local Zones and AI Factories. Breakout sessions are recorded and posted to the AWS Events YouTube channel a few days later, while other session types are live and not recorded.

  13. AWS Machine Learning Blog40

    How DXC Technology built a multi-model AI substrate on Amazon Bedrock

    DXC Technology built DXC OASIS, a harness for mission-critical IT operations, on a governed multi-model substrate in Amazon Bedrock that provides access to Anthropic Claude, Amazon Nova, Meta Llama, and open-weight models through one managed interface, with Bedrock Guardrails, AWS PrivateLink, and serverless scaling as system-level controls. DXC separates the substrate from its own orchestration, governance, and assurance layer, and reports that since general availability in March 2026, DXC OASIS has reduced resolution time by 95% on average across 56 measured use cases. The post describes the architecture, model routing, and authority tiers, and states that DXC is evaluating Amazon Bedrock AgentCore alongside its current orchestration layer.

  14. AWS Machine Learning Blog34

    Automating AWS Agent Registry updates with push-based architecture

    This post describes an event-driven pipeline using AWS CloudTrail, Amazon EventBridge, and AWS Lambda that detects Amazon Bedrock AgentCore UpdateAgentRuntime events and syncs MCP server tool schemas into AWS Agent Registry records, supporting both single- and multi-account setups. The Lambda extracts the runtime ARN, obtains an OAuth bearer token via AgentCore Identity, calls the MCP server's initialize and tools/list methods, then updates the matching APPROVED registry record only when normalized tool definitions differ. Updated records revert to Draft status and require curator approval before becoming discoverable, and the post notes limitations such as no automatic registration of new servers and no retry on cold starts.

  15. Codex Releases10

    0.167.2

    This page is a GitHub navigation menu and changelog index entry labeled "0.167.2," listing platform sections such as Copilot, Actions, Codespaces, and Code Quality along with add-ons like GitHub Advanced Security and Copilot for business. It contains no release notes or details about the version itself.

  16. Google Research58

    Using wearables to enable cardiovascular-kidney-metabolic (CKM) risk profiling for personalized coaching

    Google researchers describe an investigational framework that builds a "coachable health age" from wearable signals such as resting heart rate, steps, sleep duration and Active Zone Minutes, plus a Sensor World Model trained on over 2.2 million person-weeks of Fitbit data to simulate 12-week "what-if" habit trajectories. In blinded evaluations, lifestyle coaches preferred counterfactual-grounded plans in 71.4% of cases, and physicians rated 99.2% of those plans within safe exercise intensity limits. A companion study extends the approach to multi-organ CKM health by combining wearables with routine blood biomarkers including cholesterol-to-HDL ratio, eGFR and HOMA-IR.

  17. AWS Machine Learning Blog42

    Accelerating generative AI delivery with reusable assets

    AWS's Generative AI Innovation Center, now part of AWS Frontier AI Engineering & Services, offers a catalog of 23 production-ready open source reusable assets such as RAG pipelines, document processors, and agent scaffolding. The post cites DoorDash and Lyft using the Contact Center GenAI Agent and Ricoh using the GenAI Intelligent Document Processing accelerator, reporting results including a 50x increase in testing capacity and a 7-fold throughput increase. It also walks through deploying the Contact Center GenAI Agent and lists the full asset catalog on GitHub and AWS Labs.

  19. Databricks Blog22

    Databricks Doubles Down on AI Products, Opens New 235,000-Square-Foot San Francisco Headquarters

    Databricks opened its new headquarters at One Sansome Street in San Francisco, currently 201,000 square feet and expanding to 235,000 square feet by next fall, as part of a commitment of over $1 billion into its San Francisco operations by early 2028. The company highlighted AI Research work including KARL, MemCurrent, and Adaptive Instructed Retriever, plus products like Lakebase, Genie, and Unity Gateway, and noted it has grown to over 12,000 employees, a $7 billion revenue run-rate, and 20,000+ customers.

  20. Google Blog AI80

    Gemini Decisions API: Fast, calibrated multimodal decisions

    Google introduced the Gemini Decisions API, powered by the new Gemini Decision 1 model (gemini-decision-1) and available through the Gemini API in Google AI Studio, for closed-set decisions such as tool selection, policy checks, model routing, and context grading. It accepts one multimodal input (text, images, audio, video, PDFs up to 256K tokens) with up to 1,000 yes/no, multiple-choice, and rubric-scoring questions, scoring options in a single forward pass with confidence scores at 150-250 ms end-to-end latency and $0.10 per 1M input tokens with zero output tokens billed. Google reports that Gemini Decision 1 leads across agent routing, reasoning, ranking, and multimodal benchmarks with the lowest calibration error, and is nearly 5x cheaper than Gemini 3.5 Flash-Lite with the Interactions API across the shared benchmark suite.

    Why it matters: It documents a new Google model and API with pricing, latency, and benchmark claims, useful for teams weighing low-latency classification and routing options.

  21. Apple Machine Learning Research34

    Weighted State Souping for Efficient Long-Context Retrieval

    The paper proposes weighted state souping, a method that learns query-dependent weights for composing cached state encodings from an SSM, addressing the degradation of state souping and vanilla SSMs on long, crowded contexts. The authors report substantial long-context improvements across single- and multi-hop document QA, needle-in-a-haystack retrieval, variable tracking, and tool use, plus a sparse variant with near-constant encoding cost relative to context length. They also present theoretical arguments on why souping works and when it may fail.

  22. Apple Machine Learning Research34

    On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models

    This paper argues that the gating mechanism in modern recurrent networks explains both the successes and failures of State Space Models (SSMs) on in-context learning and retrieval tasks: theory and experiments show gating causes SSMs to first learn an in-weights "memorization" solution while delaying or preventing convergence to a correct in-context learning solution, even when the architecture and memory capacity impose no fundamental limits. The authors also find that gating is often beneficial for improving generalization to long sequence lengths.

  23. Apple Machine Learning Research34

    Evaluating the Evaluators: Investigating LLM Judges for Personalized Writing Style Assessment

    This NeurIPS 2026 workshop paper examines how well LLM judges evaluate personalized writing tasks, testing how the writing task, generator-judge pairing, evaluation objective, and general reasoning ability affect judge performance across four LLMs and three long-form writing tasks with human pairwise labels. The authors find judge quality correlates weakly with MMLU-measured ability (Pearson's ρ ≤ 0.2), varies by task and criteria, and that paired comparisons yield more consistent results than independent scoring, while the strongest LLMs do not most reliably reproduce human evaluations.

  24. Mastra Blog30

    Introducing Mastra Forward

    Mastra Forward is an annual service providing a named forward-deployed Mastra engineer who works in your codebase alongside your team, backed by Mastra core engineering. It includes Mastra Factory installed in your repo to run a swarm of agents, an Enterprise license on hosted, self-hosted, or BYOC deployment, a Trace Intelligence pool with evals run as a service, and a quarterly architecture review. Mastra says it costs less than one senior AI hire and is invoiced quarterly or prepaid at a discount.

  25. NVIDIA Technical Blog18

    Validating GPU Platforms with Runtime AI Inventory via the NVIDIA DSX AI Factory

    As teams deploy and scale AI workloads using NVIDIA Dynamo, Kubeflow, or Slurm, tracking what actually runs requires visibility beyond the platform configuration captured in a recipe. Application teams define and update these workloads independently of the platform recipe, so a reproducible deployment bundle alone cannot establish which workload artifacts are running on each node.

  26. Comfy Blog58

    Doubling LLM token rates in ComfyUI

    ComfyUI rewrote the hot path of local text generation for Qwen3.x LLMs, letting the same checkpoints on the same GPU generate tokens up to twice as fast with no change to model or output quality; on an RTX 5090, Qwen3.5 9B went from 106 to 219 tokens per second. The changes include a re-laid-out GEMV kernel, fused prologue operations, new attention and DeltaNet decode kernels, and an adaptive-tree MTP speculative decoding algorithm, all available in ComfyUI v0.45.0 with the Text Generate node's mtp option left on auto.

  27. Amazon Science33

    Using mathematics to validate network configurations

    AWS describes using its automated-reasoning tool Tiros to statically validate network segmentation in Cloud WAN by converting configurations from route tables, attachments, and policy documents into logical propositions and querying which attachments can reach which with which destination IPs. The system checks that no path exists between segments the policy declares off limits, succeeding if actual reachability matches expected segmentation and alerting an operator if they differ, with analyses possible as often as hourly. The post illustrates this with a production/development segmentation example across us-east-1 and us-west-2 and notes the approach extends to tools like IAM Access Analyzer and VPC Reachability Analyzer.

  28. Meta Engineering40

    Intelligent Delivery: Making Every Unit of Compute Serve Better Ads

    Meta describes Intelligent Delivery, an ML-driven system that allocates compute across its ads serving stack toward a system-wide optimum, contributing roughly 10% incremental ranking performance on top of model and system advancements from 2017 through the first half of 2026. It combines a shared Resource Core Model (6B sparse and 20M dense parameters) that predicts each request's outcome, compute consumption, and latency impact, with a hierarchy of allocation engines spanning region, hardware SKU, and host-level decisions. Agentic AI now helps propose and test optimizations, contributing to about 20% of Intelligent Delivery optimizations in the first half of 2026 and about 80% of engineering effort on the most automated mechanism, with engineers approving every change.

  29. AWS Machine Learning Blog42

    Accelerating product development with AI-driven lifecycle management (AI-PDLC) in AWS Quick

    This AWS blog post describes AI-PDLC, a framework of six AWS Quick agents (an Orchestrator plus Discovery, Prioritize, Working Backwards, Spec Generator, and Designer) that guide product teams through the Discover, Decide, Design, and Prototype phases, with human approval required at every gate. The agents pull context from enterprise connectors such as Slack, Jira, Salesforce, SharePoint, ServiceNow, and Outlook, store artifacts in shared Quick Spaces, and produce a prototype_spec.md that can be handed to coding agents like Kiro or Claude Code via the Agent Client Protocol (ACP). The post includes step-by-step setup instructions, Deep Discovery and Fast Track pacing modes, and three scenarios: new product development, feature additions, and bug fixes.

  30. Google Developers Blog78

    A2UI 1.0: Build delightful, fast, reliable, agentic experiences

    Google released A2UI 1.0, the first stable version of its open protocol for generative UI, which lets AI agents respond with interactive screens that each app renders with its own native components. Version 1.0 adds bidirectional function calls, accessibility support and extensions, plus open-source renderers for React, Angular, Lit, Flutter, SwiftUI and Jetpack Compose (currently v0.9.1) and agent SDKs for Python, TypeScript and Dart. Atlassian, Alation, Bloomberg and ByteDance are already building with it, and the web and Flutter renderers work inside MCP Apps such as Claude and Gemini.

    Why it matters: It marks the first stable release of an open generative-UI protocol, with concrete renderer, SDK and partner details useful for developers evaluating agent interfaces.

  31. Vapi Blog58

    Agent Loop is here: Better voice agents, every call

    Vapi has launched Agent Loop in early access, a self-improving harness on top of its voice agent platform that builds an agent from a plain prompt, scores every call against a business goal, clusters misses into issues, drafts and tests fixes, then ships them as experiments on a slice of live traffic with automatic rollback. It relies on primitives including Simulations and Traffic Splitting (available in the dashboard now) and Goals, Call Health and Experiments (coming soon), with human approval required before any change ships. GA is planned for early next year, and Vapi is taking waitlist signups ahead of VapiCon on November 11.

  32. ElevenLabs Blog60

    ElevenLabs and NVIDIA expand collaboration to bring voice agents to enterprises and governments globally

    ElevenLabs and NVIDIA are expanding their partnership across models, infrastructure and sovereign deployments, with NVIDIA Nemotron 3.5 Super VL now available in ElevenAgents and ElevenLabs adding 15MW of NVIDIA Blackwell Ultra and Vera Rubin compute. ElevenLabs models and NVIDIA infrastructure power a sovereign voice agent for Poland's national e-Health appointment system, and the companies are exploring on-device voice AI for robotics and physical AI.

    Why it matters: It shows how voice-agent stacks are being bundled with model and compute partnerships, and includes a concrete sovereign healthcare deployment with stated operational details.

  33. ElevenLabs Blog58

    Building the interaction layer for AI: Everything announced at ElevenLabs Summit NYC

    At its New York Summit, ElevenLabs announced new models, agents, and deployment options, including plans to fine-tune open-source language models and ElevenLabs voice models for businesses, a previewed Interaction Engine that manages turn-taking and selects LLMs per task, and ElevenAgents upgrades such as Memory and Routines. It also introduced ElevenAI, an app for enterprise teams that takes meeting notes and action items using Scribe v3, launched the ElevenLabs Partner Program and Marketplace, and announced an expanded NVIDIA partnership.

  34. ElevenLabs Blog22

    How enterprise clients are putting ElevenLabs AI to work

    ElevenLabs says enterprises now account for more than 55% of its revenue, with employees at nearly 70% of Fortune 500 companies using its platform, which supports languages spoken natively by 5.5 billion people and 16,000 voices. The company detailed enterprise uses including Yahoo adding real-time voice to its Scout answer tool via ElevenAgents, Westgate Resorts deploying a voice agent named "Sarah" trained on 8,000 support transcripts, and KPN launching Mobiel AI for Dutch small businesses after fine-tuning raised identity-verification accuracy from roughly 50% to 90%. Other customers cited include Doppel for vishing simulations, Pocket for transcription, and Twilio integrating ElevenLabs voices into Conversation Relay.

  35. ElevenLabs Blog22

    McKinsey and ElevenLabs collaborate to take natural AI conversations to enterprise scale

    McKinsey and ElevenLabs announced an alliance combining McKinsey's industry and enterprise transformation expertise, underpinned by QuantumBlack's AI engineering, with ElevenLabs' conversational AI technology and ElevenAgents platform to help organizations prove value through initial use cases before scaling across the enterprise. Each deployment pairs multilingual conversational technology with agent design, systems integration and operating-model changes, and the companies cite KPN, the Dutch telecom company, as an early example using AI-powered solutions for customer interactions from order enquiries to technical appointment management. The alliance aims to extend beyond telecommunications to service-intensive industries such as insurance, supporting claims intake, policy servicing and everyday customer questions.

  36. ElevenLabs Blog25

    ElevenLabs expands partner program to help enterprises adopt AI agents faster

    ElevenLabs launched an expanded Partner Program with enhanced commercial incentives, new certifications, joint go-to-market opportunities, and dedicated technical support, citing over 550 active partners in 44 countries and $52 million in partner-sourced and partner-influenced revenue this year. The program aims to help partners earn $3 in services revenue for every $1 ElevenLabs generates, and includes a new certified partner directory plus forward-deployed engineers who work alongside partners on complex implementations.

  37. ElevenLabs Blog42

    Introducing the ElevenLabs Marketplace for enterprise-ready AI applications

    ElevenLabs launched the ElevenLabs Marketplace, a curated collection of industry-specific AI and voice applications built on ElevenLabs by partners including Salesforce, IBM, NiCE, Twilio and Zendesk, spanning financial services, insurance, healthcare, telecommunications, retail and government. Enterprises can explore solutions and connect directly with the partners behind them, while ElevenLabs says it plans to let customers purchase eligible partner solutions through existing ElevenLabs commitments starting next year.

  38. Codex Releases12

    0.170.0-alpha.1

    This entry is a GitHub Changelog page for version 0.170.0-alpha.1, consisting mainly of site navigation menus covering GitHub products such as Copilot, Actions, Codespaces, and Advanced Security. The material contains no release notes or details about the version itself.

  39. Databricks Blog38

    Air gapped, not data dark: how Bright Machines gives customers live factory dashboards without opening the plant

    Bright Machines captures PostgreSQL changes at the factory edge with Debezium, writes them as Apache Iceberg, pushes them out over a single auditable outbound path, and reads them in place in Databricks via Unity Catalog federation, with zero inbound ports to the plant. A row committed on the line is queryable in Databricks in one to two minutes, dashboards refresh every ten minutes, and a heartbeat check detects a broken pipeline in under thirty minutes. The first customer-visible dashboard went live about two months after kickoff, replacing nine loosely coupled services with one governed platform plus one edge path.

  40. Google Blog AI47

    Try Tabletop: Customizable, collaborative spaces for groups to plan, play and do more together.

    Google is introducing Tabletop, a new Google Labs experiment for real-time group collaboration where users add links, files and ideas, then prompt @tabletop or pick a starter template to generate interactive trip itineraries, dinner polls, expense splitters and tournament brackets. Once a space is ready, an invite link can be shared in a group chat so everyone can use it at the same time, like in a Google Doc. Tabletop is rolling out in the U.S. (18+) via waitlist at labs.google/tabletop.