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This post presents a five-stage operating model for managing Amazon Bedrock cost: attribute every dollar to an owner, make every request observable, enforce budgets, optimize platform defaults, and operate a review cadence. Written for FinOps and platform engineering teams.
Amazon Bedrock AgentCore Session endpoints give each runtime session an authenticated URL that forwards any HTTP method, path, and WebSocket connection to the ports you allow. In this post, you deploy a coding agent that keeps a Vite website running in its session, then watch the live site update in your browser as the agent edits files.
Five MIT faculty members and two additional alumni are honored with fellowships to advance research on beneficial AI.
MIT professors Adam Berinsky and Chara Podimata discuss a new project to track how AI chatbots are responding to questions about the 2026 U.S. midterm elections.
From ICPC World Finals to competitive programming clubs to building generalist audio models as the first engineer at a YC startup.
Dylan left Minnesota for San Francisco to build AI agents for CAD software as the first engineer at Adam (W25).
A principal engineer left consumer-scale software to build AI-native scientific analysis tools as the founding engineer at 10x Science.
A math major who turned down safe internships to lead high-stakes deals at a YC S26 startup supplying data for frontier AI labs.
A veteran engineer finds his next act helping scientists discover cures, one amino acid at a time, at YC W26 startup 10x Science.
After 10 years at Google Research and DeepMind, Yair Alon joined Poetiq to build an AI that improves itself.
From Lyft's self-driving division to fixing HSA/FSA payments, Varsha joined Flex as its first engineer and built from scratch.
A layoff, two years of travel, and a self-taught pivot to software led Sherif Amer to become the founding engineer at Indemni.
Worldwide Express automated its less-than-truckload freight billing-exception process with a multi-agent solution built on Amazon Bedrock. Six months after launch, the company cut active exceptions by 75%, improved time-to-cash by four weeks, and unlocked $10 million in free cash flow.
The ChatGPT desktop app is now available on Amazon Bedrock in AWS GovCloud (US). This post walks through a controlled local deployment that routes model inference to Amazon Bedrock in AWS GovCloud (US-West) using API-mode sign-in, a managed device policy, a named AWS profile, and network restrictions, so a security team can validate it before broader use.
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Today, we’re announcing that spend caps on Google Cloud Budgets are generally available. With this release, we’re delivering ways to protect your workloads from runaway costs without risking resource deletion. More importantly, we’re introducing three major updates, directly inspired by your feedback since the initial preview, to bring programmability, real-time visibility, and automated guardrail
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Dense 3D tracking from monocular video requires establishing point correspondences over time, estimating their depth, and inferring their trajectories during occlusion. Existing methods typically learn these tasks jointly, a demanding objective given the scarcity of 4D supervision. We show that strong pretrained 2D trackers and 3D geometry models provide an effective foundation: lifted trajectorie
We launched Sierra just over two and a half years ago. This week, we hit $400M+ in ARR, adding $150M+ in ARR in Q3 alone. That’s more ARR in one quarter than we generated all of last year.
OpenAI will honor a shared robots.txt signal to help website operators communicate their AI training preferences to participating providers.
OpenAI is strengthening violence prevention in ChatGPT with expanded safeguards, earlier interventions, and a new commitment to public safety reporting.
Gravitational waves from eccentric compact binary coalescences trace dynamical binary formation, but matched-filtering searches responsible for most detections rely on quasicircular templates. Quantifying any sensitivity loss is crucial for assessing population completeness and the need for dedicated eccentric template banks. We present the first systematic GstLAL search study spanning eccentricit
Existing sketch generation methods often rely on image guidance and are largely limited to individual objects or simplified scenes, leaving text-guided complex scene sketching underexplored. We present SketchDirector, an agentic framework that mimics the human sketching workflow for automatic multi-concept scene sketching. Given a scene-level text prompt, SketchDirector first employs a large langu
OpenAI shares excerpts from court briefs by creators, academics, accessibility advocates, and legal experts, among others, on how fair use supports AI training and innovation.
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The UK Amazon Quick User Group's 2026 roundup: three quarterly meetups, 150+ attendees, and customer stories from Arriva, Carsa, and Propulse Lab on using agentic AI and Amazon Quick to turn data into faster decisions, higher satisfaction, and scalable growth.
Recommendation systems that optimize for the average user can fail to capture the preferences of diverse demographic groups. We consider a dynamic recommendation system, where arriving users can belong to different demographic groups. Importantly, these groups can intersect, and a user may belong to several groups. We first show that over time, any group-blind policy (which excludes all current-us
World action models (WAMs) learn latent variables from observations and use these to both predict the evolution of the scene and to generate actions. The prediction has to be of the whole scene, whereas only a portion of the scene causes actions. WAMs fitted to demonstrations do not, in general, guarantee that they will generate actions solely from the latent causes of the demonstrated actions (th
Recent work shows that a frozen robot policy performs far better inside an agent harness, where control code decides when to query the policy, consult vision tools, or command the arm directly. Yet today these harnesses are built by hand and redesigned for each new robot or benchmark. We show that harness design can be automated, offering a strong alternative to finetuning on a novel setup. In Rob
Short-video search needs compact query rewriters that recover users' personalized intent from ambiguous queries under strict latency constraints. Existing LLM-based methods have improved rewriting by using synthetic reasoning and subsequent consumption-behavioral feedback. However, overemphasizing subsequent consumption can favor engaging content over the user's immediate need, causing intent drif
Andrew “Geeky” Hawkes knows what it takes to bring a new combat aircraft into service. As one of the first-ever Royal Air Force pilots to train and fight on the Eurofighter Typhoon, he helped introduce cutting-edge capabilities and develop tactics for the force. At Shield, he’s known to his colleagues almost exclusively as Geeky, a […]
Epsilon's Agentic Platform team delivers UI testing as a managed, multi-tenant service built on Amazon Nova Act and Amazon Bedrock AgentCore Browser Tool. Tests are written in plain English and run on browsers managed by AWS, giving every product team resilient, intent-driven testing with zero per-team infrastructure overhead.
Turn a PHP-to-Java migration from a one-time leap of faith into a measurable, repeatable process with Kiro. This post walks through a reusable engine: a mechanical discovery scanner and an eight-phase, parity-first workflow that treats the original PHP application as the specification and verifies the Java port with a parity harness.
We are excited to announce that Dr. Mitesh Patel is joining Sierra as our Head of Clinical.
OpenAI’s updated Model Spec outlines five core values to guide more capable AI toward sound judgment, human agency, and faithfulness to human intent.
AWS Batch quota management is a new scheduling capability you can use to divide GPU capacity into quota shares per team or project, automatically lend idle capacity across shares, and use preemption to run your highest-priority SageMaker Training jobs first, all without manual coordination.
MoEngage turned roughly 400 private REST APIs across 7 AWS Regions into permission-scoped agent tools with Amazon Bedrock AgentCore Gateway. No per-service MCP servers, no public endpoints, and no 400-tool context bloat. See how OpenAPI specs, Cedar policies, and managed Amazon VPC Lattice egress made it work.
NVIDIA Nemotron 3.5 Super VL is a 120B-parameter mixture-of-experts model that pairs reasoning and tool use with multimodal understanding. This post explores its architecture and use cases, then shows how to deploy it on Amazon EKS, EKS Auto Mode, and Amazon SageMaker HyperPod EKS with NVIDIA Dynamo and vLLM.
Over the last year we’ve been sharing our work leveraging large language models to catch bugs on the fly — a novel approach we call Catching Just-in-Time Tests (JiTTests). Now, we’re sharing the results and positive impact we’ve seen with Catching JiTTests deployed into production. Our paper, “Just-in-Time Catching Test Generation at Meta,” fully details [...] Read More... The post Catching Bugs B
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Carrier-aggregation (CA)-assisted affine frequency division multiplexing (AFDM) is conceived for integrated sensing and communication (ISAC) systems. A frequency-modulated continuous-wave (FMCW)-inspired dechirping receiver is developed to exploit the inherent pulse-compression property of AFDM chirp subcarriers for accurate delay-Doppler estimation. To further enhance sensing performance, a pair
An observer sees only part of the surrounding world, yet must keep track of what lies beyond the current view. Spatial perception therefore involves more than recognizing individual images: it calls for a persistent spatial state that is updated under self-motion and used to guide action. Do visual foundation models provide representations that support such a state? We study this question through
Federated learning traditionally relies on a fixed aggregation rule despite shifting client state and wireless dynamics. We present FedMaJ, a framework that dynamically selects aggregation rules via Majority Judgment voting. During voting rounds, clients evaluate candidate models across performance, resource utilization, channel condition, and fairness metrics. The server adopts the majority-prefe
OpenAI uses layered monitoring to detect frontier model misalignment and unauthorized agent behavior so responders can intervene before incidents escalate.
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Ropes & Gray is developing AI for transactional diligence with OpenAI. Lawyers review grouped documents, summaries, and reports before advising clients.
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Superluminous supernovae, among the brightest stellar explosions, are thought to be powered by newborn magnetars. One such event, SN 2024afav, ``chirped'', displaying sinusoidal, increasing-frequency ($P(99\textrm{ d})\sim39\pm8$ d to $P(166\textrm{ d})\sim17\pm5$ d) light-curve modulations. The model explaining this chirp, a precessing disk falling onto the dimming magnetar, generalizes to a norm
LONDON (October 29, 2026) — Shield today announced an agreement with Leonardo under which Leonardo will use Shield’s Hivemind software to further develop autonomy capabilities for integration onto Proteus, Leonardo’s autonomous uncrewed rotorcraft. The agreement expands Leonardo’s tools to build its own mission autonomy software for new and existing systems. Using the Hivemind Software Development
Credit Saison’s ChatGPT Enterprise pilot delivered 954% ROI. See how leaders and employees helped turn the results into companywide adoption.
One-step and few-step text-to-image generation must accurately render the details specified in the prompt despite limited opportunities for refinement. Distribution matching distillation (DMD) uses score differences to bring the generated distribution closer to a reference distribution. Following prior work, we estimate this difference with internal velocity branches, avoiding a separate fake-scor
Formula-Driven Supervised Learning (FDSL) enables vision pre-training without real images, but existing methods cast pre-training as classification on discretized labels, discarding continuity in the generative process. We propose Formula-Driven Supervised Metric Learning (FDSML), which derives relational supervision from image-generation parameters beyond discrete class labels. FDSML combines Fin
Interactive world models generate visual content conditioned on user actions, yet maintaining spatial consistency over long-horizon exploration in real time remains challenging. Existing approaches rely on either temporal context or explicit 3D memory, both of which scale poorly because memory grows with the length of the generated stream. Moreover, explicit 3D memories condition latent video gene
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