AWS

2026-11-02

COMPANIES · 1 SOURCE · AWS Machine Learning

Circle K automates DevOps triage with Amazon Bedrock, cuts mean time to triage to under 15 minutes

Circle K built an automated, agentic triage system on Amazon Bedrock (initially with Bedrock Flows, later migrated to Bedrock AgentCore) that queries logs, services, and internal runbooks and posts structured summaries to Slack; the team reports mean triage time fell to under 15 minutes (a 67–75% reduction by their metrics). The implementation used managed Bedrock features (Agents/AgentCore and Bedrock Knowledge Bases for RAG) to avoid self-hosting models and orchestration code.

6.0

2026-11-01

COMPANIES · 1 SOURCE · InfoQ AI, ML & Data Engineering

AWS large committed capacity largely sold out through 2027, Jassy says

Amazon CEO Andy Jassy said in a video podcast (reported by Reuters) that AWS’s large committed cloud capacity is largely sold out through 2027 with some 2028 already allocated, while AWS continues to reserve headroom for on‑demand EC2 and the Bedrock inference service; capacity-sold products include On‑Demand Capacity Reservations and Capacity Blocks for ML. Analysts cautioned this describes pre‑reserved, large blocks and may not reflect immediate on‑demand availability for ordinary customers.

7.0

2026-10-30

MONEY · 1 SOURCE · AWS Machine Learning

Managing Amazon Bedrock costs end to end — an AWS playbook for FinOps and platform teams

AWS published a five-stage playbook for managing Amazon Bedrock costs that targets FinOps and platform engineering teams. The guidance emphasizes invoice-grade attribution via IAM principal data in CUR 2.0, per-request observability, budget enforcement, platform-wide defaults (model routing, caching, token limits), and an operational review cadence to control agentic and high-invocation workloads.

6.0

2026-10-30

COMPANIES · 1 SOURCE · AWS Machine Learning

Worldwide Express automates LTL freight billing exceptions using Amazon Bedrock

Worldwide Express (part of ShipStation Global) built a multi-agent AI system on AWS that integrates with its SpeedShip TMS and uses Amazon Bedrock and EC2 to resolve billing exceptions for LTL freight. Launched to production within six months after engaging AWS in June 2025, the system routes exceptions to three specialized agents (Invoice Matching, Pricing Variance, Accessorial Validation) and delivered a 75% reduction in active exceptions, a four-week improvement in time-to-cash, $1M in annual savings, and a one-time $10M free cash flow infusion.

7.0

2026-10-29

COMPANIES · 1 SOURCE · TechCrunch AI

Jassy: AWS can be a $1T business; Amazon to boost capex for AI infrastructure

Amazon CEO Andy Jassy said AWS could become a trillion-dollar annual-revenue business within five to ten years and disclosed plans to ramp capital expenditures — roughly $220 billion in cash capex in 2026, mostly for AWS — with meaningful increases expected in 2027 to build AI and cloud capacity. He cited strong revenue growth (about a 39% YoY increase and a $184B run rate) and forecast AWS growth north of 40% in 2027 and 2028, even as investors questioned the large near-term spending.

8.0

2026-10-29

COMPANIES · 1 SOURCE · AWS Machine Learning

MoEngage uses Amazon Bedrock AgentCore Gateway to expose 400 private APIs as agent tools

MoEngage converted roughly 400 internal REST APIs across seven AWS Regions into permission-scoped agent tools using AgentCore Gateway (part of Amazon Bedrock AgentCore). The approach centralized MCP handling under MoEngage’s AI Platform team, avoided any public endpoints, preserved identity injection server-side, and cut estimated platform engineering effort by about six months while reducing API onboarding from days to hours.

6.0

2026-10-28

CODING · 1 SOURCE · AWS Machine Learning

AWS Ray Train DLC (train-ml-cuda-v1.1) enables EFA-backed multi-node PyTorch on EKS

AWS provides a Ray Train Deep Learning Container (public.ecr.aws/deep-learning-containers/ray:train-ml-cuda-v1.1) that bundles CUDA, NCCL, EFA userspace libraries and Ray, allowing multi-node PyTorch training on EKS without building custom images. A provided sample shows fine-tuning Qwen2.5-1.5B with PyTorch FSDP across eight NVIDIA L4 GPUs on two g6.12xlarge instances using KubeRay and EFA.

6.0

2026-10-28

MONEY · 1 SOURCE · TechCrunch AI

Anthropic S‑1 shows Amazon could reap biggest IPO gains via $6.2B notes and $10B preferred stock

Anthropic’s S‑1 discloses that Amazon holds $6.2 billion in convertible notes (which Amazon’s filings value at $97.9 billion as of June 30) and purchased $10 billion of nonvoting preferred stock, bringing its disclosed investment to about $18 billion; the notes can convert into up to 12% of Anthropic’s partially diluted shares. The filing also shows traditional VCs own relatively small percentage stakes given Anthropic’s large private valuation, and Anthropic has committed to at least $110 billion in AWS spending over the next decade; Google also holds a sizable position and cloud commitments.

8.0

2026-10-27

RESEARCH · 1 SOURCE · InfoQ AI, ML & Data Engineering

Momento CEO Khawaja Shams presents 'Serving LLMs at Scale: The Hidden KV Cache Advantage' at QCon AI

Khawaja Shams (Co‑Founder & CEO of Momento) gave a QCon AI presentation describing distributed-systems approaches to scale LLM inference efficiently, focusing on GPU utilization, KV cache memory cliffs, tiered storage, tail-latency reduction, and disaggregated prefill/decode architectures. He framed these techniques as ways to improve fleet performance, cost economics, and availability for production LLM deployments.

5.0

2026-10-23

COMPANIES · 1 SOURCE · AWS Machine Learning

Eon uses Amazon Bedrock AgentCore Gateway to centralize multi-cloud MCP access

Eon implemented a centralized authenticated gateway using Amazon Bedrock AgentCore (Gateway, Runtime, Policy, Identity) to replace per-tool credentials and local MCP processes, giving engineers and autonomous agents unified access to investigation tooling across AWS, GCP, and Azure. The change reduced developer onboarding for investigation tooling from about two days to roughly two minutes and lets Eon's autonomous SRE agent (Claude on Bedrock) access the same tools with separate identities and permissions.

6.0

2026-10-22

MODELS · 1 SOURCE · AWS Machine Learning

Amazon Polly Generative engine upgraded with 14 new voices, Hindi and Finnish GA

Amazon announced a production upgrade to the Amazon Polly Generative engine that delivers more natural, expressive and accurate speech with low latency. The release is a drop-in upgrade (no API or voice-name changes), adds 14 new voices across nine locales, brings Hindi and Finnish to general availability, expands to 57 generative voices across 11 languages and 25 locales, and extends availability to AWS GovCloud (US-West).

6.0

2026-10-22

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS documents how to deploy Amazon Quick in HIPAA-eligible environments

AWS published guidance explaining that Amazon Quick is a HIPAA-eligible service and describing how healthcare organizations can use its agentic chat agents, connectors, and Model Context Protocol (MCP) to process PHI within HIPAA-eligible AWS accounts. The post details available controls (ACL-aware retrieval, chat/feedback logging, action controls), shared-responsibility limits of the AWS BAA, and best practices for governance and irreversible configuration choices.

7.0

2026-10-21

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS publishes walkthrough to connect Amazon Quick to on-premises data via PrivateLink

AWS released a walkthrough showing how to keep traffic between Amazon Quick (an AI-powered workspace) and on-premises data off the public internet by using VPC endpoints (AWS PrivateLink) for user/API access and Quick-configured VPC connections for data-source access. The guide assumes an existing AWS Direct Connect or Site-to-Site VPN and details which Quick features use each path, plus current data-source limitations (e.g., Redshift supported for Quick Index; many cloud file sources are not).

5.0

2026-10-21

CODING · 1 SOURCE · Hugging Face

Profiling TorchNeuron on AWS Trainium — system-level walkthrough (Part 1)

This tutorial shows how to profile PyTorch workloads on AWS Trainium using TorchNeuron (torch-neuronx). It covers configuring torch.profiler with NeuronConfig and NeuronProfiler, exporting matched system/device traces (NEFF/NTFF), inspecting execution with Neuron Explorer, and compares three RMSNorm implementations (naive PyTorch ops, fused torch.rms_norm, and torch.compile) with reproducible examples in the torch-neuronx examples directory.

6.0

2026-10-20

COMPANIES · 1 SOURCE · TechCrunch AI

Leaked S‑1 shows Anthropic struggling to secure cloud capacity

A leaked S‑1 filing reported by the Wall Street Journal says Anthropic is having trouble securing sufficient cloud capacity from AWS, Google, and Microsoft — which increasingly see the Claude-maker as a competitor — and may spend more than $750 billion on cloud contracts while also leasing data centers and working with third-party operators. The filing (as reported) also discloses large first-half losses, concentrated revenue, potential liability exposures exceeding insurance, and that Anthropic has reportedly reached $16.8 billion in third-quarter revenue and is targeting a November IPO.

8.0

2026-10-20

COMPANIES · 1 SOURCE · AWS Machine Learning

Smartsheet launches GA MCP Server on AWS to let AI agents read and write sheets

Smartsheet has launched a generally available (GA) Model Context Protocol (MCP) Server hosted on AWS that lets AI assistants read, write, and manage Smartsheet data via a standardized MCP interface. The server supports Streamable HTTP transport, MCP spec versions 2025-06-18 and 2025-03-26, three regional endpoints, OAuth 2.0 or Personal Access Token auth, and is shown integrated with Amazon Quick and the Kiro IDE as MCP clients.

6.0

2026-10-20

MODELS · 1 SOURCE · AWS Machine Learning

Amazon Bedrock enables access to OpenAI GPT-5.6/6/6.1 from Canada via cross-Region inference

Amazon now lets Canadian AWS customers call OpenAI GPT-5.6 (Sol/Terra/Luna), GPT-6 (Astra/Sol/Luna) and GPT-6.1 (Sol) through Amazon Bedrock cross-Region inference from Canada (ca-central-1 and ca-west-1). Inference is routed and processed in North America; models support the OpenAI Responses and Chat Completions APIs and the Bedrock Converse API, a 1M-token context window, tool calling, and prompt caching.

6.0

2026-10-20

COMPANIES · 1 SOURCE · AWS Machine Learning

AWS and Keyfactor publish X.509 PKI reference architecture for AI agents

AWS and Keyfactor released a joint reference architecture showing how to use Keyfactor EJBCA with AWS services (including Amazon Bedrock and the AWS Strands Agents SDK) to provide cryptographic X.509 identities for AI agents. The design uses signed request envelopes, user-signed delegation assertions, RFC 8693 audience-scoped tokens, and real-time OCSP revocation; example source code is available on GitHub.

7.0

2026-10-19

MODELS · 1 SOURCE · AWS Machine Learning

TwelveLabs' Pegasus 1.5 is now available on Amazon Bedrock

TwelveLabs has made Pegasus 1.5 — a video language model that converts long-form video into structured, timestamped JSON metadata — available on Amazon Bedrock. New features include full-video segmentation, multimodal prompting with reference images, on-the-fly processing with no pre-indexing, and extended single-request analysis up to two hours; calls are made via the bedrock-runtime InvokeModel or InvokeModelWithResponseStream APIs and can process video from an S3 URI or a base64 string while keeping data within the AWS boundary.

6.0

2026-10-19

MODELS · 1 SOURCE · AWS Machine Learning

Deepgram ports Nova-3 speech-to-text to AWS Trainium2, gains 11–70% batch cost efficiency

Deepgram worked with AWS to port its Nova-3 speech-to-text model to AWS Trainium2, using TorchNeuron, NKILib kernels and custom Neuron kernels; the final setup runs eight model replicas on a single Amazon EC2 trn2.3xlarge instance. On Deepgram’s offline, throughput-oriented batch workloads (e.g., contact-center analytics, medical transcription) this configuration processed 11–70% more audio per dollar versus the compute options Deepgram previously used, measured using instance pricing at the time of evaluation.

7.0

2026-10-17

COMPANIES · 1 SOURCE · InfoQ AI, ML & Data Engineering

Amazon acquires DuckLabs and integrates DuckDB into Amazon Aurora PostgreSQL

Amazon (AWS) has acquired DuckLabs, the team behind the analytical database DuckDB; co‑founders Hannes Mühleisen and Mark Raasveldt will join AWS and continue to lead the project. AWS says DuckDB and related components will remain MIT‑licensed and overseen by the DuckDB Foundation, and has already integrated DuckDB into Amazon Aurora PostgreSQL so a single query can combine live Aurora data with historical Iceberg/Parquet data in S3 (via AWS Glue) without separate ETL; the feature is available in all commercial regions and AWS GovCloud (US) with customers paying only for incremental Aurora compute and S3 requests.

8.0

2026-10-14

STARTUPS · 1 SOURCE · AWS Machine Learning

Tamnoon builds Tami, an agentic cloud-remediation system on Amazon Bedrock

Tamnoon describes how it built Tami, an AI-powered, agentic cloud remediation orchestrator running on Amazon Bedrock and AWS serverless components that ingests CNAPP/CSPM findings, investigates context with LLM‑based validation, scores safety, and generates guarded fixes. Tamnoon reports the approach cut critical cloud exposure by over 90% in 90 days without production incidents and integrates with AWS, Azure, Google Cloud, and existing CNAPP tools.

6.0

2026-10-13

COMPANIES · 1 SOURCE · AWS Machine Learning

Orca Security builds 'Discovery AI' natural-language Sonar query agent on Amazon Bedrock

Orca Security developed Discovery AI, a multi-stage natural-language query agent that translates plain-English questions into valid Sonar queries and runs on Amazon Bedrock. Using a RAG + schema-aware pipeline and model routing via Bedrock, Orca reports reducing query costs by 90%, input tokens by 93%, and latency by 75% versus their initial baseline.

6.0

2026-10-13

MODELS · 1 SOURCE · AWS Machine Learning

SpaceXAI's Grok 4.7 added to Amazon Bedrock

SpaceXAI announced Grok 4.7 is available on Amazon Bedrock with features aimed at long-horizon agent workloads: a 500K-token context window, tool calling, configurable reasoning-effort levels (low/medium/high/xhigh), and support for Chat Completions/Responses and the Bedrock Converse API. In SpaceXAI's tests of a tool-calling agent on three search-style tasks, the agent answered 67 of 72 runs correctly (18/18 at xhigh; 15/18 at low), illustrating a tunable trade-off between correctness and token use; Bedrock access uses cross-Region inference profiles and requires specific IAM permissions.

7.0

2026-10-12

CODING · 1 SOURCE · AWS Machine Learning

AWS launches Ray LLM DLC for multi-node LLM inference on Amazon EKS

AWS published a guide and released a Ray LLM Deep Learning Container (DLC) that supports deploying a single large language model across multiple GPU nodes on Amazon EKS, using a disaggregated prefill/decode setup. The Ray LLM DLC packages vLLM, Ray Serve LLM, NIXL for KV-cache transfer, and the EFA stack, exposes an OpenAI‑compatible endpoint, and includes a helper (build_pd_openai_app) plus example code in a repository.

6.0

2026-10-12

MONEY · 1 SOURCE · InfoQ AI, ML & Data Engineering

CloudZero CTO Erik Peterson at QCon AI: “You Can't Trust Your AI Bill”

At QCon AI, CloudZero founder and CTO Erik Peterson warned that AI spending is beginning to eclipse traditional cloud bills, described costly behaviors like 'tokenmaxxing' (which he estimates at roughly $5–15B), and outlined how unit economics and incentive structures are creating an engineering cost crisis; he also predicted fully autonomous AI will write, deploy, and govern code by 2028.

5.0

2026-10-07

MODELS · 1 SOURCE · The Decoder

Anthropic launches Claude Haiku 5.5 with big price cuts and benchmark gains

Anthropic released Claude Haiku 5.5, a faster, lower‑cost small model aimed at high‑volume tasks; Anthropic says Haiku 5.5 costs ~75% less on average than Haiku 4.5 and up to 90% less for prompts ≤100,000 tokens. The company also halved Sonnet 5.5 cache‑read costs, added monthly API credits for subscribers, updated SDKs with beta computer/browser use, and says Haiku 5.5 outperforms its predecessor (and compares favorably to OpenAI’s GPT‑6 Luna) on several benchmarks and agentic coding tests.

8.0

2026-10-07

CODING · 1 SOURCE · AWS Machine Learning

Automate remediation after AWS DevOps Agent investigations using Lambda Durable Functions and Amazon Bedrock

AWS describes a workflow that connects AWS DevOps Agent investigation events to an automated remediation pipeline: EventBridge triggers a Lambda Durable Functions orchestrator that sends findings to Amazon Bedrock, which selects from an allowlisted set of purpose-built Lambda tools to propose and (for read-only actions) execute fixes or (for mutating changes) prepare pre-validated changes awaiting one-click human approval. The design uses Durable Functions checkpoints to pause for approvals and iteratively call Bedrock until remediation completes, aiming to lower mean time to resolution (MTTR).

6.0

2026-10-07

COMPANIES · 1 SOURCE · AWS Machine Learning

Cornerstone’s Orion AI (on Amazon Bedrock) cuts database diagnosis time by 78%

Cornerstone OnDemand built a multi-agent system called Orion AI using Amazon Bedrock and the Strands Agents orchestration framework; the company reports database diagnosis time fell from about 45 minutes to 10 minutes (a 78% reduction), alert noise dropped a median 65%, and a three-person team delivered the system in six months. Orion AI coordinates specialized agents for monitoring, diagnostics, lifecycle operations and remediation, integrates with existing tools (e.g., SQL Server and Jira), and emphasizes data-privacy controls and domain-specific agent design.

7.0

2026-10-04

CODING · 1 SOURCE · InfoQ AI, ML & Data Engineering

Pizza Bot: AWS engineers open-source an inbox-style, local-first agent runner

AWS engineers Joseph Dolivo and Igor Fil published Pizza Bot as an Apache-2.0 open-source, self-hosted application that lets AI agents run background workflows and return results via an email-style inbox. The client-server tool supports scheduled and webhook triggers, delegation to specialist workers, multiple model providers and MCP servers, and stores agent state and data locally under user control.

6.0