OpenAI Completes $11 Billion Portion of Funding at $1.25 Trillion Value
OpenAI has closed on new funding of roughly $11 billion, the initial part of a round that values the company at $1.25 trillion, according to people familiar with the matter.The funding was wired to the company as of Friday, said the people, who spoke on condition of anonymity as the information is not public. The remainder of the round, which could increase to as much as $20 billion in total, is expected to be completed in the coming weeks, one person said.The AI developer has been in talks for
Google Takes Over Wyoming Data Center That Crusoe Had Pitched
Alphabet Inc.’s Google has bought out Crusoe’s data center site in southeast Wyoming, opting to take on the project itself after the AI computing upstart failed to lock in customers.
Tech Stocks Rebound as Dip Buyers Return to AI Trade
Bloomberg’s Tim Stenovec takes a look at what's driving a rebound in tech stocks as dip buyers step in to support the battered AI trade. Plus, Anthropic's IPO plans are hit by the post-election selloff, prompting prospective investors to rethink the company's expected valuation; and the CEOs of Lyft and DraftKings join to break down their earnings results. (Source: Bloomberg)
Anthropic IPO Investors Weigh Valuation as Low as $1.2 Trillion
Anthropic's IPO plans are running into a punishing post-election selloff, prompting a rethink among prospective investors of the company's expected valuation, which could now be as low as $1.2 trillion, according to sources. Bloomberg's Seth Fiegerman joins Tim Stenovec on “Bloomberg Tech.” (Source: Bloomberg)
Free Chinese AI Models Are Getting Scary Good at Hacking
An experiment in which AI models were asked to break into simulated networks showed the hacking skills of DeepSeek and GLM to be not far behind OpenAI’s most advanced cyber model, which isn’t public.
Google DeepMind Says It Has Used AI Agents to Break Legacy RSA-1024 Encryption Faster Than Anyone Thought Possible
Google DeepMind has published new research showing that AI agents, working under human supervision, can dramatically accelerate cryptanalysis — the discipline of stress-testing... The post Google DeepMind Says It Has Used AI Agents to Break Legacy RSA-1024 Encryption Faster Than Anyone Thought Possible appeared first on OfficeChai.
Meta’s best AI model now trains the one most of its users get
Starting on Friday, everyone using Meta’s Muse agent and Meta AI gets new models the company trained using Muse Wonder, The post Meta’s best AI model now trains the one most of its users get appeared first on The New Stack.
Accelerating Reinforcement Learning Weight Refit with the Reshard Collective
During reinforcement learning (RL) post-training, training trajectories are generated on the fly by running inference with the current policy model. For...
SageMaker Inference now supports Multi-Instance GPU to maximize GPU utilization for model endpoints
Amazon SageMaker Inference now supports GPU partitioning with NVIDIA Multi-Instance GPU (MIG), which divides one GPU into hardware-isolated partitions so you can run a different model in each or take a right-sized fraction of a newer accelerator. This post shows how two optional API fields place one model per partition, and what we measured against a whole older GPU.
Get a jump start on the US trading day with Dani Burger on "Bloomberg Open Interest." A blowout jobs report fuels expectations for another Fed rate hike, even as Wall Street reels from a nearly $4 trillion tech selloff and mounting questions about the AI trade. Plus, Anthropic's IPO prospects and valuation reset, BlackRock CIO Rick Rieder explains the AI unwind and emerging credit opportunities, Kevin Hassett, director of the White House National Economic Council, discusses inflation and Fed policy, and Greg Ebel, CEO of Enbridge Energy, weighs in on the growing energy demands of AI infrastructure. (Source: Bloomberg)
Anthropic IPO Buyers See Valuation as Low as $1.1 Trillion
Anthropic PBC’s initial public offering plans ran into a punishing post-election selloff, prompting a rethink among prospective investors of the company’s expected valuation. Bloomberg's Anthony Hughes joins to discuss. (Source: Bloomberg)
Microsoft Winding Down Oracle Deal to Rent AI Cloud Capacity
Microsoft Corp. is winding down an arrangement to rent AI computing from Oracle Corp., part of a larger reassessment of billions of dollars in cloud partnerships.
The Blueprint: Orchestrating 5,000+ AI assets for a World Cup TV spot
Welcome back to The Blueprint, a regular feature where we highlight how Google Cloud customers are tackling unique and common challenges across industries using the latest AI and cloud technologies. We hope to inspire others looking to innovate in their work. AI is rapidly transforming video production at virtually every step of the process, from ideation and storyboarding to filming, editing, and release. At Mito, we’re striving to democratize AI-powered video creation, enabling everyone from solo artists to large enterprises to get the most out of the best creative technologies available. The Challenge When we founded Mito, our goal was to eliminate the complex technical friction that stops creators from telling long-form, narrative stories with generative AI. However, transitioning from a single five-second clip to a cohesive campaign — such as a 120-second national TV spot for Movistar Plus+, a part of Telefónica, to broadcast across Spain during the World Cup this summer. This effort revealed massive infrastructure and workflow bottlenecks: Asset & workflow overhead: Managing local media libraries across individual workstations was unscalable. For Movistar alone, our production required generating a massive "iceberg" of over 5000 assets (1000 of those videos) generated in around 65 iteration rounds. Zero real-time collaboration: Traditional feedback loops required manual downloads, Google Drive uploads, and fragmented communication across chat apps and email. Rendering latency: Standard AI video rendering takes four to five minutes per short clip. Running these processes synchronously froze our user interface and stalled creative velocity. Model disparity & consistency: Every generative model requires distinct prompting logic. Maintaining character persistence, specific lighting, and camera angles across dozens of shots — while preserving the likeness of real public figures like chef Ferran Adrià or journalist Juanma Castaño — was nearly impossible without central orchestration. Capacity constraints: Operating on public pay-as-you-go model APIs left us vulnerable to rate limits and regional throughput throttling during peak traffic. The Solution To deliver an infinite, real-time creative canvas for filmmakers, we designed a serverless, asynchronous architecture built on Google Cloud. We run our API, AI Director, and background workers as Java services on Cloud Run, which scales with request volume. In order to address message routing challenges, we decoupled job execution using Google Cloud Pub/Sub as our central event bus. Long-running video generations are offloaded to background Cloud Run workers, allowing creators to keep working uninterrupted on the UI canvas. To minimize latency, media assets are stored in Google Cloud Storage and delivered via Cloud CDN. Expiring key signatures keep pre-release client assets strictly private. Keeping our storage alongside the models we call through Vertex AI reduces network transfer delays. An isolated database architecture helps with the heavy business intelligence and analytics workloads while mitigating potential negative impacts on production performance through Cloud SQL and PostgreSQL. We rely heavily on foundational models like Omni, Veo and Nano Banana, which we access through Vertex AI alongside our custom system prompts. Finally, our structured canvas frontend enforces a "Rule of 6" (limiting prompt variables across World, Camera, Light, Texture, Actions, and Character) and prioritizes still-frame generation before video rendering to maximize cost efficiency. The Architecture The Outcome By pairing our creative orchestration platform with Google Cloud’s infrastructure, we successfully delivered a landmark national broadcast campaign that the production team describes as 95% AI-generated: Prime-time scale: The 120-second Movistar campaign for the Spanish National Team aired across every major television channel in Spain, with 1,441 assets live on a single shared Canvas near launch. AI Director copilot: Our conversational agent translates natural language instructions into precise model parameters while maintaining context, lighting, and visual style across every scene. Seamless collaboration: Distributed teams and brand clients can work on the same canvas in real time. Because new generations are saved as separate assets instead of overwriting earlier ones, stakeholders can duplicate projects to explore parallel creative ideas. Continuous dogfooding: Through our internal studio, Mito Films, we put our tools to the test on high-stakes client projects — whether that's global television spots or keynotes for top robotics startups — ensuring direct feedback flows back into engineering. Future-proof foundation: Our architecture is primed for rendering times to collapse from minutes to seconds, positioning Mito to handle upcoming world models, deeper memory states, and personalized content delivery. The Details Building an enterprise-grade platform for AI storytelling required solving several backend and creative challenges. This includes our creation of a virtual queuing system that mitigates third-party API rate limiting during usage spikes for smooth request concurrency, with bounded retries and a clear outcome for every job. Because creative output cannot be fully validated with standard unit tests, we built an automated evaluation harness powered by Gemini. Acting as an independent judge, it evaluates AI Director outputs against original user intents across an automated test suite, which we run alongside standard tests for high-impact Director changes. We knew early on that we would need multi-model intelligence routing. As such, we built the AI Director to dynamically coordinate tasks across multiple specialized models — including Sonnet, Gemini, and ElevenLabs for audio — treating the spatial canvas like a live code repository to infer adjacent contextual cues. We also needed to embrace an “imperfect aesthetic” to arrive at a more authentic outcome. In our Movistar spot, the story follows Tommy, a 17-year-old student making an AI video project. At the climax, the AI misunderstands a prompt, making coach Luis de la Fuente say "In the same milkshake" while holding a drink. Tommy edits the prompt live to "In the same heartbeat," and the video recalibrates instantly. By incorporating surreal visual elements — like stadium stands built into Galician cliffs or a neighborhood bar covered in pitch grass — we showcased how generative AI can elevate human storytelling rather than obscure it.
Introducing Z4M: storage-optimized compute for AI/ML and parallel file systems
Today, we’re excited to announce the general availability of our next-generation Storage-optimized Z4M machine series in Google Compute Engine, available as both Virtual Machine (VM) and bare-metal instances. We built Z4M to provide storage for AI/ML training and inference workloads such as checkpointing, distributed key-value (KV) cache and parallel file systems — workloads that handle huge data volumes and require massive parallel data processing, as well as high storage and networking throughput. Low latency access to data is equally critical to keep GPUs and TPUs fully utilized. Powered by the fifth-generation Intel Xeon Scalable processors and paired with the latest enhancements in Titanium, Z4M provides up to 168,000 GiB of Local SSD (LSSD) storage coupled with up to 400 Gbps of Cloud Remote Direct Memory Access (RDMA) networking. RDMA improves the performance of these demanding workloads by reducing data-access latency by up to 60% compared to TCP networking, so you can increase your applications’ throughput while right-sizing your cloud investment. Z4M VMs and bare-metal instances The Z4M VM portfolio lets you scale your infrastructure and clusters to meet workload requirements by providing a large total LSSD capacity as well as 875 GiB of LSSD capacity per vCPU. Further, Z4M bare-metal instances give you direct access to the physical hardware without a virtualization layer, reducing latency for workloads such as custom hypervisors and workloads with specific licensing needs. Z4M bare-metal instances are also ideal for agentic AI workloads, enabling developers to run isolated sandboxes at scale, including with Agent Substrate. In addition to 168,000 GiB of LSSD storage, Z4M VMs and bare metal instances offer up to 192 vCPUs and up to 1,536 GiB of memory for at-scale data processing. Z4M instances are based on Titanium SSDs, which offload local storage processing from CPU resources to deliver real-time data processing, low-latency, high-throughput storage performance and enhanced storage security. Z4M delivers up to 15.6M random-read IOPS and up to 75,600 MiB/s sequential-read throughput, improving the LSSD storage performance and throughput compared to Z3 by up to 70% and 110% respectively. Cloud RDMA and direct storage access Z4M provides low-latency access to the storage layer using 400 Gbps of RDMA-enabled standard networking.This helps keep GPUs and TPUs fully utilized even when processing large multimodal datasets, by transferring massive amounts of data at line rate using NVIDIA GPUDirect Storage and TPUDirect Storage. At the same time, Z4M transfers data at full line rate while processing data locally, with a balanced-LSSD-to-networking-throughput ratio of 1.4:1. Built for demanding workloads Workload Category Typical Applications Z4M Benefits AIML training and inference Checkpointing, distributed Key-Value cache Large LSSD capacity paired with 400 Gbps low-latency RDMA network that supports GPUDirect Storage and TPUDirect Storage, keeping GPUs and TPUs fully utilized even when processing large multimodal datasets. Parallel file systems and Enterprise-class storage Weka, Sycomp, Silk, VDURA Very high vCPU:LSSD ratio of 1:875 combined with a balanced LSSD:networking throughput of 1.4: to improve applications’ performance by processing data locally while transferring data to clients at full line rate. Business-critical enterprise Databases SQL, NoSQL, Vector DBs, data search Sustained LSSD high I/O performance and throughput to sustain a large number of transactions per second. What customers and partners are saying "Nutanix is committed to helping organizations run their applications and data anywhere. Bringing Nutanix Cloud Clusters (NC2) to Google Cloud's new Z4M metal instances reflects that mission and our continued partnership with Google Cloud. By combining Z4M’s exceptional I/O performance and high storage density along with Intel’s advanced compute and AMX-driven efficiency, NC2 on Z4M provides the scale, density, and performance required to power everything from dense VDI clusters to demanding, data-intensive AI workloads." - Saveen Pakala, Vice President of Product Management, Nutanix "Google's Z4M VMs bring Cloud RDMA to a storage-optimized VM with much higher local SSD density than previous generations. In our testing, Cloud RDMA on Z4M demonstrated outstanding performance with up to 3.7x lower latency and up to 6x lower CPU usage than TCP. For our customers, that means faster, more predictable performance across a wide variety of use cases, from I/O-intensive databases to analytics and AI workloads, with the storage density to scale capacity efficiently." - Adik Sokolovski, Chief R&D Officer, Silk “We're excited to support Google Cloud's new Z4M platform as part of the Sycomp Intelligent Data Storage Platform. With greater capacity per node and the continued evolution of the Z-series architecture, Z4M helps customers achieve new levels of performance and efficiency. Supporting innovations like Z4M reinforces Sycomp's commitment to delivering high-performance storage solutions across the Google Cloud ecosystem.” - Scott Fadden, Senior HPC Solutions Architect, Sycomp "We've worked alongside Google Cloud for years on the most demanding AI and machine learning workloads. In our testing, we found the new Z4M machines deliver roughly twice the read throughput and up to 79% more IOPS, generation over generation (Z3 family). This means more data, more tokens, and more finished work. We’re excited to see what our joint customers build with these powerful machines." - Ajay Singh, Chief Product Officer, WEKA Orchestration with Cluster Director You can easily configure, deploy and manage large Z4M clusters using Google Cloud’s Cluster Director, which offers advanced placement and maintenance capabilities alongside the Cluster Toolkit for rapid cluster deployment. You can view and deploy your workloads in a compact topology to maximize performance, or spread topology for high availability by targeting availability domains. You can combine or stagger the maintenance across these availability domains. Additionally, you can co-locate Z4M instances with your GPU and TPU clusters to process very large datasets in real time and at scale. Enhanced maintenance experience Both Z4M VMs and bare-metal instances make it easier for you to plan ahead and schedule maintenance operations by providing notice from the system several days in advance of required maintenance. For Z4M VMs with 42,000 GiB or less of LSSD storage, you can live-migrate an instance during maintenance events. Z4M VMs with 84,000 GiB or more of LSSD and Z4M bare metal instances must be terminated and restarted while preserving your data through planned maintenance events. Support for Hyperdisk Z4M VMs and bare-metal instances support Hyperdisk, Google Cloud’s workload-optimized block storage, which lets you optimize the performance for each workload by independently tuning the storage performance and capacity for each instance. Specifically, they are compatible with Hyperdisk Balanced, Hyperdisk Throughput, and Extreme Hyperdisk storage for scalable, high-performance network-attached storage, supporting up to 512 TiB of capacity per instance. For general-purpose workloads, Hyperdisk Balanced, with up to 320K IOPS per instance, offers a mix of performance and cost-efficiency. Hyperdisk Extreme delivers ultra-low latency and supports up to 500K IOPS and 12,500 MiB/s throughput per Z4M VM and bare-metal instance, making it well-suited for demanding database workloads. Get started with Z4M today Z4M VMs and bare metal instances are available today in select regions worldwide. To start using Z4M instances, choose Z4M under the Storage-Optimized machine family when creating a new VM or GKE node pool in the Google Cloud console. Learn more at the Z4M machine series page. Contact your Google Cloud sales representative for more information on regional availability.
Want to know the latest from Google Cloud? Find it here in one handy location. Check back regularly for our newest updates, announcements, resources, events, learning opportunities, and more. Tip: Not sure where to find what you’re looking for on the Google Cloud blog? Start here: Google Cloud blog 101: Full list of topics, links, and resources. aside_block <ListValue: []> Nov 2 - Nov 6 Security for AI workloads with Model ArmorSecuring generative AI applications requires robust runtime protection against prompt injection and malicious inputs. Join Nicola Cardace on Thursday, November 19, 2026, at 5:00 PM CET for a Community TechTalk exploring how to safeguard enterprise AI workloads using Model Armor. Discover practical patterns for implementing active model defense across your LLM endpoints. Register for the November 19 Community TechTalk A5X accelerated by NVIDIA Vera Rubin NVL72 is now Generally AvailableGet the most out of A5X instances with Google Cloud’s AI Hypercomputer. Bringing together compute, storage, networking, and software co-designed as a single system. Read more Oct 26 - Oct 30 Simplify PostgreSQL Monitoring with the New AlloyDB Omni Web UIThe newly released AlloyDB Omni Web UI delivers a centralized, graphical dashboard that simplifies the management of self-managed PostgreSQL workloads across hybrid, multi-cloud, and air-gapped environments. This browser-based console provides database administrators with deep, real-time insights into cluster health, hardware utilization, and active database connections. It also features built-in query diagnostics and performance tracking for AlloyDB’s columnar engine, enabling quick troubleshooting of bottlenecks without manual terminal commands. To learn more about setting up this monitoring interface, read the full AlloyDB Omni Web UI Blog Post. Leveraging "Antigravity" to architect high performance semantic model routers in ApigeeSemantic model routing replaces rigid static paths with a lightweight helper model to dynamically classify and dispatch intent-driven LLM traffic. Join Saravanakumar Rajagopal on Thursday, November 12, 2026, at 5:00 PM CET for a Community TechTalk exploring how to leverage Antigravity and skills to architect these intelligent multi-provider routing patterns natively inside Apigee. Discover how to optimize your AI infrastructure and enhance flexibility at scale.Register for the November 12 Community TechTalk Oct 19 - Oct 23 From prompt to production: End-to-end AI workflows in ApigeeDeploying an enterprise AI gateway does not require deep API or machine learning expertise. Using declarative workflows in Apigee, teams can spin up a fully governed LLM gateway in minutes using a few environment variables. Join Luis Cuellar on Thursday, October 29, 2026 for a Community TechTalk exploring end-to-end AI workflows. Discover how to layer essential defenses—including Model Armor for prompt protection, Cloud Data Loss Prevention (Cloud DLP) for sensitive data redaction, rate limiting, and response caching—before routing autonomous agent interactions through your gateway filters.Register for the October 29 Community TechTalk Zero Standing Privileges with PAM: On-Demand Temporary Access for Humans and AI AgentsAI agents now hand work off to other agents, risking stacked privileges and overpermissioning. Because agents plan their actions on the fly, permanent admin access means one hallucination can cascade into production. Join us on Wednesday, November 18, 2026, at 8:30 AM PST to see how Google Cloud Privileged Access Manager (PAM) brings Zero Standing Privileges to AI delegation, putting humans in command with cloud-native control that doesn't slow developers down.Register for the November 18 webinar Streaming comes to API Gateway: real-time and AI-ready APIsNative streaming support is now in Public Preview for API Gateway, enabling you to run real-time and AI workloads behind your existing gateway. You can now route Server-Sent Events (SSE), WebSockets, gRPC, and chunked transfer encoding without modifying your API spec or managing a split estate. This update also strengthens integration with the Gemini platform, allowing you to stream responses from Gemini, Claude, and OpenAI gpt-oss models seamlessly while maintaining consistent authentication, rate limiting, and observability.Read the blog to get started Oct 12 - Oct 16 AI tokenomics in action: Enforcing tiered token budgets with ApigeeScaling artificial intelligence across an enterprise requires clear token governance to keep LLM spend predictable across departments. Join Tarun Abraham on Thursday, November 5, 2026 for a Community TechTalk on AI tokenomics. Discover how to use Apigee to enforce isolated, tiered token budgets and model access for each team—such as assigning Engineering a dedicated budget for Gemini Pro while covering mixed usage for Marketing—without changing application code. Attendees will also gain access to a sample codebase featuring a reusable Shared Flow.Register for the November 5 Community TechTalk Sept 28 - Oct 2 Claude Sonnet 5.5 is now available on Google Cloud. Built for focused coding and knowledge work, it delivers stronger performance for feature development, and creating presentation-ready documents, while offering more intelligence with a lower cost per task for most work at faster speed. Deploy Sonnet 5.5 directly from Model Garden with Google Cloud’s enterprise security, scale, and governance built in. Try it now. Mastering Storage Management with Storage IntelligenceIn our new blog, explore practical strategies to modernize storage operations using Storage Intelligence Advisor and enhanced Batch Operations. See how customers like Shipt and Palo Alto Networks are using these features to manage their estates at scale. Today, Storage Intelligence is used by 25 of the top 50 GCS customers. 2 in 3 customers have Storage Intelligence enabled for over 90% of their storage footprint.Explore best practices on our blog Cut Gen AI costs by 70% with Apigee X dynamic routingGenerative AI deployments face a harsh cost-performance trade-off: static model selection either wastes budget or compromises quality. Discover how to build an Intelligent AI Gateway using Apigee X to dynamically evaluate prompt complexity in real-time. This new blueprint automatically routes simple queries to lightweight models (like Gemini 3.5 Flash Lite) and complex reasoning tasks to advanced models (like Gemini 3.7 Flash), achieving over 70% cost savings without sacrificing output quality. Read the guide to optimize your Gen AI architecture AI Agent Clinic launches new hands-on session on production agent evaluationsA new episode of the AI Agent Clinic is now available showing organizations how to move past manual "vibe checks" to build robust, production-grade agent evaluations. In this hands-on session, Google Cloud engineer Dani Zamora and Matthew Feroz (Merge) take DocsHound, an open-source LangGraph agent, and build an end-to-end eval pipeline in under an hour. Learn how to standardize multi-turn traces across any framework using OpenTelemetry and OpenInference, pair LLM judges with deterministic checkers, and catch silent quality regressions before shipping. Watch here Drive AI impact: Join Google's Agentic Data Cloud event on Nov 4Every enterprise plans to adopt agentic AI within two years, but data bottlenecks hold them back—AI accesses just 45% of enterprise data today (MIT, 2026). Google's Agentic Data Cloud provides the trustworthy foundation and real-time context AI needs. Join our product leaders November 4th to explore the latest innovations across databases, analytics, business intelligence, and storage, and get direct answers in our executive Q&A with Google Data Cloud VP & GM Andi Gutmans. Register today! Sept 21 - Sept 25 Master MCP tool authorization and agent governance with ApigeeWhile the Model Context Protocol (MCP) solves interoperability for autonomous AI agents, chained actions like CRM edits or database queries quickly expose systems to unauthorized execution. Join our technical deep dive on Thursday, October 1, 2026, at 5:00 PM CEST featuring Christophe from Google Cloud. Learn how positioning Apigee between MCP clients and enterprise backends enables fine-grained authorization (FGA), complete audit trails, and policy evaluation via emerging standards like OpenID AuthZEN.Language and accessibility note: This session will be hosted in French, but non-French speakers can follow along seamlessly by turning on Google Meet live translated captions to read in English, Spanish, German, Portuguese, or Italian.Register for the October 1 Community TechTalk Apigee Trace Viewer Tutorial: Capturing & Analyzing Proxy TracesStreamlining API proxy debugging just got easier with a new tutorial by Apigee Customer Engineer Tyler Ayers. The guide covers end-to-end instructions for capturing debug traces in both Google Cloud Apigee X (or Hybrid) and the local Apigee Emulator, extracting trace JSON data via the web UI or automated REST APIs, and analyzing execution flows, variable mutations, and latency bottlenecks using the open source Apigee Trace Viewer. Read the Apigee Trace Viewer guide today. Automate Apigee proxy testing locallyCatching errors early saves time and money. A new tutorial by Apigee customer engineer Tyler Ayers shows how to use the Apigee Local Emulator for automated testing. Learn to run tests locally, integrate them into CI/CD pipelines, and deploy on Google Cloud Run for shared sandboxes. This approach provides instant feedback and zero cloud costs, helping teams speed up deployment cycles.Read the tutorial Scale your enterprise multi-agent systems with ApigeeDeploying multi-agent architectures in production introduces critical hurdles around security, operational control, and runtime expenses. Discover how Apigee API Hub provides a central discovery surface to eliminate agent sprawl across tools, Model Context Protocol (MCP) servers, and enterprise APIs. Learn how to turn existing backend services into secure MCP tools using Agent Gateway guardrails, while applying semantic caching and intelligent model routing to keep compounding token costs predictable.Join Google Cloud in Chicago in Oct.15 for The AI Evolution. Reserve your seat for Chicago Automate Apigee proxy testing with the Apigee Local EmulatorWaiting on remote deployments to validate API proxy logic slows down release cycles and increases infrastructure overhead. Join Nigel Walters on Thursday, October 8, 2026, at 5:00 PM CEST for a Community TechTalk on shift-left testing for Apigee. Discover how to use the Apigee Local Emulator and apigee-emulator-service to run sub-second assertion suites on local machines, automate CI/CD checks in GitHub Actions, and deploy ephemeral preview sandboxes on Google Cloud Run.Register for the October 8 Community TechTalk Now in Public Preview: AI-assisted EKS-to-GKE migrations with deterministic guardrailsMigrating complex Kubernetes estates from AWS EKS to GKE is traditionally high-friction and error-prone. Now in Public Preview, GKE Agentic Migration is an open-source agent plugin that replaces ad-hoc LLM prompting with an AI-assisted migration workflow protected by deterministic guardrails.Running locally in your development harness, it indexes source IaC, maps cloud-specific primitives (such as Karpenter to Custom Compute Classes), and validates configurations offline—delivering reviewable pull requests and data-migration runbooks with zero live cluster mutations.Learn more in the announcement blog and try the plugin on GitHub. Claude Opus 5.5 is now available on Google Cloud. Built for everyday complex tasks, it delivers stronger agentic coding, research, and analysis while handling long-running work at a lower cost per token. Google Cloud continues to provide enterprise customers with broad model choice to build, deploy, and scale their AI agents securely. Try it here. Import Delta Lake tables with Dataflow Job Builder!Migrating to borderless Lakehouse just got a lot easier. You can now import Delta Lake tables stored in Cloud Storage using Dataflow Job Builder, a no-code/low-code interface for authoring Dataflow pipelines. Because Dataflow is a fully managed service, you are spared the overhead of provisioning and managing virtual machines. For step-by-step guidance, check out the documentation here. Sept 14 - Sept 18 Storage Intelligence Advisor for Google Cloud Storage is now GAGoogle Cloud Storage customers can now manage cloud storage more effectively with Storage Intelligence Advisor, delivering curated metrics, automated anomaly detection, and actionable recommendations right out of the box, with zero setup required.Advisor baselines activity across your projects and automatically detects four key anomalies: surges in operations, unexpected rises in cross-region egress, and spikes in errors. Each finding includes deep drill-down visibility into the resources driving the change, alongside prescriptive steps to remediate issues before they impact performance or cost.Learn more to get started with Storage Intelligence Advisor. Build private WebSockets from Apigee X to Cloud RunReal-time AI agents and streaming architectures often require persistent, bidirectional connections. A new implementation guide by Apigee Customer Engineer Joel Gauci demonstrates how to establish private southbound connectivity between Apigee X and Cloud Run. Using Private Service Connect (PSC) and a Regional Internal Application Load Balancer, teams can enforce API governance and security policies at the edge while keeping backend services completely isolated from the public internet.Explore the step-by-step guide and open-source code Connecting Gemini Enterprise Agent Runtime to Apigee with Private Service Connect Deploying autonomous AI agents often presents security, compliance, and cost challenges. A new reference guide details how to build an end-to-end, private architecture between Gemini Enterprise Agent Runtime and Apigee. This design helps protect internal backends and manage token quotas. Read the full community guide and deploy the code Discover what’s new and next in ApigeeAs enterprise architectures adapt to generative AI and autonomous workflows, Apigee is expanding its proven platform capabilities to support modern AI gateway use cases alongside traditional API management. Join our session on Thursday, September 24, featuring Apigee Product Manager Geir Sjurseth. Get an inside look at recent product releases, explore architectural patterns for securing models and agents, and bring your questions for the live Q&A.Register for the September 24 Apigee product update Managed Service for Apache Kafka supports clusters with public Internet access!With Managed Kafka public clusters, you can now produce and consume messages from clients outside your VPC—including your local machine, for faster, frictionless testing. Public clusters unlock use cases like IoT devices, retail storefronts, and telco network towers. Enable public access on new or existing clusters via the Google Cloud console, gcloud CLI, or REST API. Spin up your first public cluster, or reach out to kafka-hotline@google.com with questions. Stream data directly into Bigtable using Bigtable subscriptions, now in Preview!You can write Pub/Sub messages to a Bigtable table with zero ETL with Bigtable subscriptions. No pipelines, no code, delivered by the serverless, zero-ops experience you already know with Pub/Sub. Power your AI workloads, from model telemetry to real-time context engineering, without the overhead of managing complicated ETL pipelines. Built to be dependable, with native support for dead-letter topics. Try the feature today! Sept 7 - Sept 10 Why Your Voice Agent Needs Session AuditingMoving voice agents to production demands robust quality monitoring. This guide dives deep into the inner workings of the Agent Development Kit (ADK) responsible for audio session auditing. Learn how the ADK's save_live_blob feature intercepts, buffers, and stores raw audio chunks during active Gemini Live sessions. We explore building an automated post-processing pipeline to seamlessly stitch these fragments into cohesive, playable audio files. Discover how to leverage these vital audio audit trails to monitor real-world interactions, diagnose failures, and ensure enterprise-grade reliability. Read the full guide here. AlloyDB Omni Red Hat RPM Orchestrator now Generally AvailableAlloyDB Omni Red Hat RPM orchestrator is now Generally Available. The AlloyDB Omni Red Hat RPM orchestrator offers a new way to manage PostgreSQL-compatible workloads on bare metal or VM platforms, combining the high performance of AlloyDB, access to generative AI features and Gemini models to build AI agents and applications, and full automation. The orchestrator simplifies cluster provisioning and lifecycle management by allowing you to define reference architecture specifications, customizable by adjusting instance parameters, node configurations, and networking options — discover all details in full blog post. Aug 31 - Sept 4 Automate VM guest software lifecycle with VM Extension Manager, now GAGoogle Cloud VM Extension Manager is now generally available, eliminating the need for custom startup scripts to manage guest OS extensions across Compute Engine fleets. Define declarative, project-wide policies that enforce desired software states across all regions and zones. Benefit from continuous drift detection with automatic self-healing, multi-zone phased rollouts with automated rollbacks on failure, and centralized fleet health visibility integrated with Cloud Monitoring.Explore VM Extension Manager documentation Assess Apigee migrations without a target environmentPlanning a migration to Apigee X or Hybrid? You can now assess your legacy Apigee Edge SaaS or OPDK environment earlier in your planning cycle. Using the updated --skip-target-validation flag in the Apigee Migration Assessment Tool, teams can generate a full inventory and establish scope baselines before target infrastructure or IAM credentials are provisioned.Read the guide to learn more. Claude Fable 5.1 is now available on Agent Platform. It brings performance improvements over Fable 5 across reasoning, full-lifecycle coding, multi-tool workflows, and knowledge work. Anthropic also announced Enterprise Frontier Safeguards, a solution that gives customers the option to safely deploy Anthropic’s most capable models while storing their data in cloud infrastructure they control. We continue to offer enterprise customers options across frontier models to build, deploy, and scale securely on Google Cloud. Aug 24 - Aug 28 Grok 4.6 is now available in Preview on Gemini Enterprise. xAI's most capable model, built for coding, agentic tasks, and knowledge work, Grok 4.6 joins Grok 4.3 and Grok 4.20 in Model Garden and becomes the flagship of the Grok family. It supports reasoning, function calling, and structured output for multi-step agentic workflows, and accepts text and image input.Get started today Empowering autonomous agents with advanced security governanceAI agents offer incredible productivity gains, but granting them access to read emails, query databases, and trigger APIs introduces critical new security risks. In fact, 79% of tech leaders cite security and governance as their biggest challenge to scaling AI. Traditional tools are no longer enough to handle automated threats like prompt injection and dynamic permissions. Discover how forward-thinking enterprises are using secure-by-default design, agent identity governance, and human-in-the-loop controls to deploy agents with confidence.Read more Stateful processing is available in BigQuery continuous queries in PreviewStateful operations significantly expand what’s possible with BigQuery continuous queries. This feature allows users to leverage functions like JOINs, aggregations, and windowing functions directly in their streaming queries. Now you can calculate metrics over time (for example, a 30-minute average) to power your downstream applications and AI agents with much richer, real-time signals. Try out our feature here and share your feedback with bq-continuous-queries-feedback@google.com! Synthetic data generator tool is available for Managed Service for KafkaYou’ve launched your first Kafka cluster. Now what? The next thing to do is to produce some data to the cluster, but that involves modifying a client application somewhere or spinning up a virtual machine. The synthetic data generator tool, now generally available, can start sending mock data to your cluster in 3 clicks, and will get data streaming into your cluster in less than two minutes. The perfect utility for those moments you just want to test your cluster and new features. Try our quickstart today! Dataflow pipeline updates are faster & more flexibleDataflow pipeline updates can now stop-and-replace pipelines, a major addition to the existing in-place-update feature. The new parallel pipeline option accelerates the migration between the old & new pipeline, resulting in reduced disruption to your business. You can also set a timeout on drains that prevents runaway costs for your pipeliness in the event of stuck processing. This feature is generally available. Try it here! Aug 17 - Aug 21 Webinar: Agent Identity as the backbone for secure AI innovationAn AI agent with a stolen API key looks identical to a legitimate one. As autonomous agents scale across enterprise systems, static credentials and legacy IAM policies can no longer keep up with machine-speed execution. Join Shaun Liu, Product Manager at Google Cloud, on August 27 at 1 PM ET to explore Google Cloud’s vision for unifying agent, human, and nonhuman identity into a workload-centric platform using verifiable cryptographic identities (SPIFFE, ID-JAG, OAuth).Register for the webinar now Aug 10 - Aug 14 Diagnosing Apigee Hybrid Cassandra Read Latency for Peak PerformanceDiagnose real-time Cassandra read latency and resolve API key verification bottlenecks in Apigee Hybrid with this step-by-step troubleshooting guide. Learn how to deploy a debugging client and query performance tables to maintain sub-millisecond response times. Read the Apigee Hybrid Cassandra Troubleshooting Guide Keep moving with agents! The All Things Agentic Hackathon is officially live.We're challenging builders to build next-generation agents that take on the busy work and handle the heavy lifting in the background using Gemini 3.5 and Google Cloud. Compete for your share of $190,000 in prizes, cash, and Google Cloud credits! Submissions are open from August 3, 2026, to August 31, 2026.Learn more and register. Sign up for GEAR to get exclusive updates and your badge. # Accelerate PostgreSQL migrations using Gemini in Database Migration ServiceEnterprise database migrations often stall during the "last mile" of translating legacy stored procedures, triggers, and custom functions from Oracle or SQL Server. Database Migration Service (DMS) now provides AI-assisted code conversion powered by Gemini in Databases. By combining deterministic compiler rules for 1:1 syntax with Gemini contextual synthesis for complex procedural blocks, DMS converts legacy code into native PostgreSQL and AlloyDB with full schema awareness and side-by-side validation.Read the full blog post to learn how to streamline your database code conversion. Compute Flex CUDs now available for G2 and G4 GPU VMsCompute Flexible Committed Use Discounts (Flex CUDs) are now available for G2 (NVIDIA L4) and G4 (NVIDIA RTX Pro 6000) VMs. You can now lock in predictable savings while retaining the flexibility to adapt across VM families, migrate between regions, and combine general-purpose compute, GKE, Cloud Run, and G2 & G4 GPU VMs under a single spend commitment. Flex CUDs for G-series VMs let you lock in savings today while preserving the agility to upgrade to latest hardware without disruption!Explore VM instance pricing or learn more about Flex CUDs. Rapid Bucket accelerates the training and checkpoint performance in PyTorch Ecosystem via GCSFSWith the release of GCSFS 2026.8.0, organisations can now unlock maximum ROI from their AI/ML infrastructure by eliminating data starvation on GPUs in PyTorch ecosystem when they are using Frameworks like Dask, Pandas, PyTorch , PyTorch Lightning, Hugging Face Datasets, Ray dataetc. By making adaptive concurrent prefetching the default, GCSFS dynamically predicts and background-fetches sequential read patterns—boosting single-file throughput by 5x, and scaling up to 21 GiB/s , saturating the NIC when paired with Rapid Bucket. Saturating the NIC translates to significantly improved accelerator goodput and reduced training wait times with zero integration friction. Training and checkpoint restore workflows benefit from intelligent memory management that automatically drains the buffer during random reads to completely avoid bandwidth or memory penalties. Aug 3 - Aug 7 Navigate data sovereignty and AI innovation with hybrid cloudFor enterprises facing strict compliance rules, keeping sensitive data on-premises often means missing out on cutting-edge AI. Data from the 2026 State of AI Infrastructure report reveals that 52% of IT leaders are adopting hybrid cloud strategies to bridge this gap. Our latest blog post explores how Google Distributed Cloud (GDC) helps organizations deploy connected or air-gapped models to run advanced AI entirely within secure environments—mitigating geopolitical risks without sacrificing innovation. Read more. SAP and Google Cloud Launch BDC Connect for BigQueryFor years, enterprises have struggled with the cost, risk, and complexity of moving mission-critical SAP data into advanced analytics platforms. The general availability of SAP Business Data Cloud (BDC) Connect for BigQuery marks a turning point. By introducing revolutionary zero-copy, bi-directional data sharing, this new capability seamlessly bridges SAP systems with Google Cloud's powerful data and AI ecosystem. Instead of wrestling with manual data duplication and lost business context, organizations can now eliminate silos, dramatically lower their analytics costs, and rapidly deploy trustworthy, agentic AI solutions grounded in real-time operational reality. Read the full announcement to learn how to transform your data strategy. Google Cloud Cortex Framework version 7 is now generally available!This release helps you modernize your data architecture for AI agent readiness, enabling you to quickly deploy, customize, and extend robust data products while simplifying orchestration and reducing infrastructure overhead. It provides data product accelerators for SAP-sourced data to build trusted, high-quality data products ready for advanced analytics and agentic use cases. The Framework integrates with Google Cloud products including BigQuery, Dataform, Knowledge Catalog, and Gemini Enterprise Agent Platform. Learn more in our announcement blog, technical documentation, or try a demo deployment today. From API Management to AI Gateway with ApigeeMassive LLM adoption unlocked automation but exposed critical vulnerabilities, from unpredictable token costs to security risks like prompt injection. Without central management, organizations face accelerated technical debt. Learn how to transform Apigee into an enterprise AI Gateway to centralize governance. This architectural roadmap details how to utilize semantic cache to optimize token costs, implement prompt protection policies for security, and productize tools using the emerging MCP standard.Read the full architectural roadmap on the Apigee Community Hub Centrally govern enterprise AI traffic with Apigee AI GatewayManage, track, and secure model communication across your entire infrastructure from a single pane of glass. In a new video walkthrough, Principal Architect Tyler Ayers demonstrates how Apigee AI Gateway simplifies agentic governance. Learn how to transparently proxy model traffic, log real-time token counts, and apply runtime security quotas without impacting your developer workflow.Watch the Apigee AI Gateway demo Maximize Provisioned Throughput UtilizationSudden traffic micro-spikes can exceed per-second quotas, triggering 429 errors or forcing overflow into shared resource pools. A new architectural guide demonstrates how to build a serverless "shock absorber" using Cloud Run and Google Cloud Tasks. By decoupling request ingestion from execution, this queue-based pattern flattens volatile traffic bursts and smoothly drips requests to Gemini at your exact quota rate, maximizing Provisioned Throughput utilization while eliminating job failures during peak usage. Read the step-by-step setup guide. Eliminate security blindspots in agentic tool agentic tool calls via the Model Context Protocol (MCP) can introduce critical security risks to your enterprise architecture. Join our technical deep dive on Thursday, August 13, to discover how to position Apigee as a centralized security gateway. Featuring the new ParsePayload policy and payload operations groups in API Products, this session demonstrates how to enforce granular tool filtering, manage execution quotas, and scale secure agent ecosystems without impeding developer velocity. Register for the August 13 Community TechTalk Jul 27 - Jul 31 Data Cloud and Apigee CDMX: The AI Agent Evolution | August 12, 2026Enterprise AI demands evolution beyond basic conversational assistants. To generate real value, AI models must connect with the organization's core systems and live data sources. Join us this August 12 at Google CDMX for the exclusive event AI Evolution: Powering Tomorrow's Enterprise. Learn how to design an agile and secure ecosystem by unifying the power of Gemini, Apigee, and data agent technologies through practical demonstrations led by Google Cloud engineers.Secure your spot for the in-person session in Mexico City Register now! Vast Edge, built on GCP, launches the first live recovery interface for cloud backups, enabling IT teams to inspect backup contents in real time. This transforms backups from a blind, log-based process into an interactive platform where teams can instantly search, preview, and validate the exact data available for restore.This platform protects Google Workspace, NetSuite, Salesforce, Workday and many SaaS environments, providing complete visibility and enterprise-grade oversight.Visit Vast Edge Backup & Disaster Recovery and get a free trial of their backup solutions on the GCP Marketplace for Google Workspace Backup, NetSuite Backup, Salesforce Backup, and Workday Backup. Jul 20 - Jul 24 Claude Opus 5, Anthropic’s latest model, is now available on Agent Platform. It brings performance improvements over Opus 4.8 across coding, long-running agents, and knowledge work.The model is Zero Data Retention (ZDR) compatible. For safety, high-risk workflows — such as penetration testing or exploit generation — it will notify you and fall back to Opus 4.8.We’re excited to continue to offer enterprise customers options across frontier models to build, deploy, and scale AI securely. Try it here. Apigee Northam Roadshow 2026 | The AI Agent Evolution: Powering Tomorrow's EnterpriseAI is evolving. As your organization deploys autonomous agents, the integration between APIs and models becomes critical. Join Google Cloud specialists for an exclusive day of deep-dive sessions and live demos. Discover how the unified power of Apigee and the Google Cloud Agent Platform allows you to build, govern, and scale high-performance AI agents with complete control. Call to Action: Register for Sunnyvale | Register for NYC | Register for Chicago Deploy an Apigee Proxy for MCP Registry Discovery Learn how to deploy an Apigee X proxy to format Apigee API Hub data into the Model Context Protocol (MCP) Registry format. This tutorial by Tyler Ayers guides developers through cloning the sample repository, deploying using the Apigee Feature Templater (aft), and testing the endpoint to make API data easily discoverable by coding agents. Read the full community tutorial to get started. Simplify AI Infrastructure: Getting Started with Apigee AI GatewayManaging a complex AI landscape with multiple backend environments can present significant operational and governance challenges. A new tutorial walks you through how to build a unified API proxy using Apigee AI Gateway. By establishing a single, secure entry point for all model traffic, teams gain access to real-time analytics, comprehensive tracing, and financial operations auditing—completely seamlessly, and with absolutely no modifications required to client environments or user configurations. Read the step-by-step setup guide Your AI agents are ready. Is your data?The biggest bottleneck to scaling AI isn't the models—it's giving them access to business context. As enterprises move to proactive systems of action, legacy infrastructure often buckles under the nonlinear speed of AI agents. Google Cloud’s new Agentic Data Cloud, built on AI-native infrastructure, solves this by unifying data, AI models, and operational databases. Discover how a borderless Lakehouse and active Knowledge Catalog can empower your AI agents with trusted, real-time context without unnecessary engineering overhead. Read more. Secure and govern your AI at Apigee AI Horizon in LondonMoving AI from basic prompts to complex agentic workflows requires trust and control. Join us on Tuesday, 1st September 2026 at Google London for our 5th edition of Apigee AI Horizon. Discover how Google Cloud product leaders and architects are using Apigee and Model Armor to secure LLM APIs, implement policy controls, and manage token consumption. Do not miss this one—register soon!Secure your spot for AI Horizon London Jul 13 - Jul 17 Resource-Based CUD Sharing is Now Enabled by DefaultStarting June 16, 2026, the default setting for Google Cloud Resource-based Committed Use Discount (CUD) sharing will change from disabled to enabled for new billing accounts and eligible existing accounts without active CUDs. This update automatically maximizes your savings by pooling underutilized discounts across your resources.You retain full control and can adjust your CUD sharing preferences at any time by changing your CUD scope configuration. For instructions, see Enable CUD sharing or Disable CUD sharing. Webinar for India: Google Cloud for EdTech: Optimizing Traffic and Token Governance at ScaleAPI traffic surges and AI model integration are reshaping the EdTech landscape. Join Satyam Maloo for the webinar Google Cloud for EdTech: Optimizing Traffic and Token Governance at Scale on July 23, 2026. Learn to implement advanced rate limiting, gain granular token visibility, and leverage real-time analytics to govern your platform effectively. Whether you’re scaling for peak academic seasons or integrating complex AI workflows, this session provides the infrastructure blueprint you need.Register Now Scaling AI Agents: Treat prompts like software artifactsAs AI agents move into production, monolithic system prompts often result in configuration drift, merge conflicts, and silent runtime failures. The solution is adopting a Prompts-as-Code architecture. By breaking prompts into modular skill files and using a build-time transpiler, engineering teams can introduce dependency resolution, static validation, and CI/CD rigor to their agent's control plane. Stop manually editing massive text files and start building deterministic, reliable agent infrastructure.Read more here. Jul 6 - Jul 10 Webinar: Introducing Google Cloud NGFW Enterprise advanced malware protection - powered by Palo Alto NetworksDiscover the new Cloud NGFW advanced malware sandbox, arriving in preview later this year. Powered by Palo Alto Networks Advanced Wildfire, it leverages data from 70,000+ customers to help defeat advanced malware. Join us on July 16 at 11 AM EDT to learn how to build a resilient, zero-trust cloud infrastructure that protects your apps and data, wherever they reside.Register for the webinar now Safely run AI-generated code in Cloud Run sandboxesCloud Run sandboxes, now in public preview, are lightweight, isolated execution boundaries that you can spawn near-instantly within your existing Cloud Run service instances.Whether you need to let an LLM run a dynamically generated Python script to calculate business margins or spin up a headless browser to perform web research, Cloud Run sandboxes give you a secure, isolated sandbox to run these tasks without leaving your serverless environment.Read the blog to learn more and get started today. Australia API Horizon: Scaling Enterprise Governed AI AgentsThe transition from AI chatbots to autonomous agents is the most critical integration point for your business. Join Google Cloud at our upcoming events to explore exclusive deep-dive sessions on architecting for the agentic era.Discover how to use Apigee as an intelligent AI Gateway to govern, secure, and scale high-performance architectures. You will learn to seamlessly build AI tools from your existing APIs and maintain control over your entire ecosystem.Join us in your preferred city: Sydney: July 28, 2026, at Google Sydney, One Darling Island. Canberra: July 29, 2026, at Hotel Realm. Melbourne: August 4, 2026, at Google Melbourne. Build highly available, multi-region services on Cloud RunMaintaining uptime for business-critical applications just got a lot easier on Cloud Run. Service health, now Generally Available, automates cross-region failover by leveraging readiness probes for instance-level health checks with a simple, two-click setup. You can configure service health with global external Application Load Balancers for public-facing applications or cross-region internal Application Load Balancers for private networking traffic.Learn how to configure service health for Cloud Run. Report: 83% of organizations need infrastructure upgrades for agentic AIThe shift from conversational bots to autonomous agents is breaking legacy systems. Our new State of AI Infrastructure report details how engineering leaders are adapting to these massive new workloads. To eliminate inference bottlenecks, control hidden scaling costs, and manage agent sprawl, the industry is rapidly moving toward fluid compute, centralized governance, and unified, co-designed architectures.Explore our key infrastructure insights Stop tinkering, start scaling: the industrialized AI PlaybookDid you know that only 5% of custom AI investments actually return measurable business value? The problem isn’t the technology—it’s how organizations are wired to run it.In this compelling read, Google Cloud Consulting breaks down the operational blueprint that bridges the stark gap between "cool tech experiments" and real, P&L-impacting enterprise ROI.Read the full article on Medium AI Agent Clinic: Slashing App Latency by 80%Prototyping an AI agent is easy, but scaling for live traffic presents unique challenges. In the latest AI Agent Clinic, our technical experts partner with a developer to optimize PlaybackIQ, a live football analysis agent. This session demonstrates how to use OpenTelemetry to trace bottlenecks in the Gemini Enterprise Agent Platform and deploy to Cloud Run for high-concurrency scaling, achieving an 80% reduction in response time. Learn production-grade debugging strategies to optimize your own LLM applications.Watch the 60-minute teardown Jun 29 - Jul 3 Claude Sonnet 5, Anthropic’s latest model, is now available on Agent Platform. This addition serves as a drop-in replacement for Sonnet 4.6, giving organizations expanded choice for task completion across enterprise workflows. It features enhanced reasoning, cleaner code generation, and computer use capabilities for desktop and browser workflows.By continuing to rapidly bring frontier models to our platform, Google Cloud offers an uncompromised choice of the industry's best technology to build, test, and scale enterprise-grade AI.Get started today. Automate your AI governance with Apigee and YAMLManual API gateway configurations can quickly slow down your AI engineering velocity. Join the Apigee community on Thursday, July 16, to discover an automated, declarative blueprint for model garden management. Learn how a simple, repeatable YAML pattern lets your AI practitioners instantly spin up secure, policy-backed enterprise configurations without friction. Bring your questions and connect during our live Q&A session. Register for the July 16 Community TechTalk Build next-generation AI portals for autonomous agentsStandard developer portals were designed for human developers to subscribe to static APIs. Today, autonomous agents, LLM toolkits, and dynamic runtimes demand a central nervous system for governance. Join our technical deep dive on Thursday, July 23, to explore Apigee's new AI Portals solution. You will see exactly how to deploy full-service, MCP powered hubs to safely manage enterprise self-service for models, tools, and agents. Register for the July 23 Community TechTalk Protect your infrastructure from advanced cyberattacks at the API layer (Presented in Portuguese)In an era of increasingly sophisticated threats, relying solely on traditional firewalls leaves critical data gaps. Join our technical community TechTalk on Thursday, July 30—conducted in Portuguese—to learn how to proactively mitigate risks directly at the gateway layer. This session demonstrates how to configure and govern essential Apigee security policies to build a robust line of defense, ensuring maximum availability and complete integrity for your enterprise microservices. Register for the July 30 Portuguese Community TechTalk Jun 22 - Jun 26 Accelerate TPU model loading while saving RAM on GKE.Large model cold starts often stall scaling and leave high-value TPUs idle. The open-source Run:ai Model Streamer now natively supports TPUs with Google Cloud Storage in TPU vLLM 0.18.0. This integration accelerates inference pipelines on GKE by streaming tensors directly into CPU memory, bypassing local disk bottlenecks and the "double-buffering" trap. In benchmarks, loading a 480B parameter model was over 2x faster while cutting peak host memory usage by half. Read the full guide and get started today. Stop Training Blind: Scaling AI with the New OpenTelemetry-Based TPU AI Telemetry Collector AgentGoogle Cloud’s new AI Telemetry Collector agent standardizes TPU monitoring using OpenTelemetry. It optimizes enterprise ML workloads by identifying silent failures and providing zero-cost operational metrics without draining host CPU cycles. The agent seamlessly routes telemetry to Google Cloud Monitoring or Prometheus and custom Grafana setups. Pre-installed on Google-optimized Ubuntu images or available via Docker, it tracks memory, network latency, and core utilization to maximize multi-node training efficiency.You can read more of this capability by clicking this link. Jun 15 - Jun 19 Join us for a deep dive into agentic AI control with AppyThingsYour integrations aren’t failing—they are evolving. When users interact with AI agents, they no longer arrive directly at your site, resulting in experiences stripped of your context, expertise, and intended experience. Join us on Thursday, June 25, for a community tech talk in partnership with AppyThings to learn how to solve this new gateway challenge. We will explore how MTN laid an integration foundation with the Model Context Protocol (MCP) to deliver accurate, consistent experiences. Our technical experts will demonstrate how to leverage Apigee as a centralized tools management solution to govern agent access. Register for the session Optimize Spot VM Deployments with Capacity Advisor for Spot, Now in Public PreviewGoogle Compute Engine has launched Capacity Advisor for Spot to Public Preview, now open to all customers. This tool turns Spot capacity discovery into a data-driven process by providing real-time deployment recommendations to maximize obtainability and minimize preemption risks. Query the Capacity Advisor API for obtainability and minimum estimated uptimes, or use the new Console UI featuring a global availability map, spot price lookups, and historical preemption rate trends to visually find the most cost-efficient compute capacity.Get started today to start optimizing your Spot VM deployments! Build a multi-tenant agentic AI systemWhen scaling generative AI across different business units, your teams need specialized AI agents with unique operational rules and tools. Our new reference architecture helps you build a centralized multi-tenant platform to prevent fragmented silos, eliminate data exposure risks, and maintain unified compliance. Read the guide to design and deploy a multi-tenant agentic AI system in Google Cloud. How to Configure Gemini Enterprise to Connect to a Custom MCP ServerThe Gemini Enterprise MCP Connector was a big announcement at Google Cloud Next because it introduces the ability to connect Gemini Enterprise to MCP servers. This blog post provides a step-by-step guide on how to configure your first Custom MCP Server connector using the Google Maps Ground Lite MCP server as an example. Once you understand this flow, you can configure multiple MCP servers with Gemini Enterprise to bring all the context you need. Jun 8 - Jun 12 Simplify Multi-Cloud Planning with Cloud Location Finder, now Generally Available Cloud Location Finder provides up-to-date data on public regions, zones, and Google Distributed Cloud Connected locations across Google Cloud, AWS, Azure, and OCI. You can now programmatically discover locations based on provider, proximity, territory, and carbon footprint to optimize your global infrastructure strategy for performance, compliance, and sustainability. Get started for free today Jun 1 - Jun 5 Modeling the physical world with BigQuery GraphManaging complex supply chains requires more than just spreadsheets; it requires a digital replica of the physical world. In this post, Guru Rangavittal and Candice Chen explore how BigQuery Graph enables organizations to build a digital twin by turning physical assets into an interconnected map of nodes and edges. By moving beyond traditional relational databases, businesses gain real-time clarity into operations—from executing surgical ingredient recalls to analyzing weather-driven logistics risks. Discover how BigQuery Graph transforms reactive firefighting into proactive, precision modeling, allowing you to see critical connections in seconds and future-proof your supply chain. Apigee for AI: Govern LLMs and MCP Servers (Presented in Spanish)Learn how to securely transition your AI initiatives from experimental prototypes to enterprise-ready deployments. Join Luis Cuellar on June 18 for a technical deep dive (presented in Spanish) exploring Apigee’s latest AI gateway capabilities. Discover how to centralize governance over Model Context Protocol (MCP) servers, protect Large Language Models (LLMs) with robust API gateway security policies, and manage token-based quotas.Register for the June 18 Spanish Community TechTalk May 25 - May 29 Anthropic’s Claude Opus 4.8 is now available on Gemini Enterprise Agent Platform. As we continue to expand our platform's model offerings, this addition gives organizations more options for handling complex, multi-stage enterprise workflows. Claude Opus 4.8 brings strong capabilities in agentic coding, allowing developers to manage extensive refactors and tracking dependencies over extended sessions. API Horizon Munich July 6, 2026: Orchestrating the Next Era of AI and APIs Master the orchestration of next-gen AI and digital ecosystems. Join Google Cloud experts and DACH tech leaders on July 6 for an exclusive look at the Apigee roadmap, Agent Management, and Model Context Protocol (MCP). Gain real-world insights and connect with the regional integration community.Register now Securing AI Agents: The Extended Agent Gateway PatternLearn how to prevent autonomous AI agents from invoking unauthorized APIs. Join Apigee Specialist Joel Gauci on June 4 for a technical deep dive into the Extended Agent Gateway pattern. This session covers enforcing Fine-Grained Authorization (FGA), implementing secure token exchange, and establishing Model Context Protocol (MCP) governance at the API gateway layer to protect enterprise backend services.Register for the June 4 Community TechTalk API-to-Agent Security: Exposing REST APIs to Gemini Enterprise via MCPConnect Gemini Enterprise agents to core data without creating security hazards. Join Google Cloud Specialist Nigel Walters on June 11 to learn how to instantly transform legacy REST APIs into secure Model Context Protocol (MCP) servers. We’ll cover how to safely register tools with Gemini while enforcing gateway-level guardrails like rate limiting and access control policies.Register for the June 11 Community TechTalk May 18 - May 22 Chinese Webinar | June 4: AI Command and ControlAs AI agents move from experimental pilots to core enterprise functions, governance has become a critical next step. Join Google Cloud on June 4th at 10:00 AM (Beijing Time) to learn how to build a secure AI management layer architecture. We'll explore how to develop governed MCP (Model Context Protocol) endpoints, manage tool access to enterprise data, and leverage robust audit logs to operationalize AI. This session also includes a practical demonstration of these governance frameworks on Google Cloud.Register here GCP Announces New Features to Benchmark and Optimize LLMs for On-Device Use CasesDeploying fine-tuned LLMs from GCP to edge devices like smartphones is complex due to fragmented hardware. Google AI Edge Portal bridges this gap, giving GCP developers the ability to test AI performance on 120+ Android devices, representing the full diversity of high, medium, and low tier smartphones on the market today. This week at I/O, we announced brand new capabilities to benchmark and debug LLM performance across these devices. Sign-up to utilize these new features in private preview today. May 11 - May 15 Build Your AI & MCP Control Tower for Universal GovernanceMaster the future of agentic security with Apigee. Join our Community TechTalk on May 21 to discover how Apigee serves as a central "Control Tower" for the Model Context Protocol (MCP). We will explore how new JSON-RPC tool authorization enables fine-grained access policies across your organization, ensuring secure and scalable AI deployments. Whether managing internal tools or external users, learn to govern your agentic ecosystem with absolute precision. This session is designed for global coverage across EMEA and AMER regions.Register for the May 21 Community TechTalk Apr 27 - May 1 Master Your Launch: The Apigee Production Go-Live ChecklistEnsure a secure launch with the Apigee production guide. Join Nicola Cardace on May 28 to explore security guardrails, including IAM roles, mTLS configurations, and encrypted KVM migrations. Scheduled at 11 AM EDT / 5 PM CEST to support EMEA and AMER teams, this TechTalk provides the technical roadmap you need to flip the switch with absolute confidence.Register for the May 28 Community TechTalk Transforming APIs into Governed Agentic Tools on the Google Cloud Agentic PlatformTurn your APIs into secure, governed agentic tools on the Google Cloud Agentic Platform. Join Specialist Christophe Lalevée on May 7 for a technical deep dive into AI productization. Scheduled at 5 PM CEST / 11 AM EDT to maximize coverage for developers across EMEA and AMER, this session explores the integration and governance frameworks required to scale enterprise-ready AI with confidence. Register for the May 7 Community TechTalk Fractional G4 VMs are Generaly Available, providing a highly efficient and cost-effective entry point for AI and graphics workloads. These new configurations, using NVIDIA virtual GPU (vGPU) technology, allow you to leverage the power of the NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs in flexible, smaller increments, so you can right-size your infrastructure to match the specific demands of your applications. By providing more granular access to advanced hardware, fractional G4 VMs let you optimize resource allocation and reduce overhead without sacrificing performance. You can now select from additional GPU slice sizes for your specific needs: 1/2 GPU: Ideal for more intensive tasks such as LLM inference, robotics sensor simulation, and high-fidelity 3D rendering. 1/4 GPU: Optimized for mainstream workloads, including mid-range creative design, video transcoding, and real-time data visualization. 1/8 GPU: Great for lightweight applications such as remote desktops, productivity tools, and entry-level streaming services. Transitioning AI from a sandbox prototype to an enterprise-grade system is a major hurdle. A monolithic script won't suffice for widespread deployment. To achieve true scale and reliability with Gemini, organizations must adopt service-oriented micro-agent architectures, establish Zero-Trust security, and implement rigorous EvalOps. Master the "Agentic Maturity Ladder" to ensure your AI & Agentic solutions are robust, secure, and ready for the real world. Watch the deep dive and read the developer blog to learn more. ML Development in VS Code with Google Cloud Power: Workbench Extension Now AvailableData scientists and developers can now combine the local productivity of VS Code with the scalable infrastructure of Google Cloud. The new Google Cloud Workbench Notebooks extension allows you to connect to and run notebooks on managed cloud environments directly within your local IDE. This integration streamlines the ML lifecycle by eliminating context switching and providing high-performance compute for complex workloads in a familiar interface. As part of our commitment to the developer ecosystem, the extension is fully open-sourced to support community-driven innovation. Install from Marketplace: GoogleCloudTools.workbench-notebooks Contribute on GitHub: colab-enterprise-vscode Apr 20 - Apr 24 Announcing the 2026 Google Cloud Partners of the YearGoogle Cloud is honored to celebrate the winners of the 2026 Partner of the Year awards! These awards recognize an exceptional group of partners across AI, Security, Infrastructure, and more, who have demonstrated a commitment to customer success. From global system integrators to specialized startups, these winners are leveraging the power of Google Cloud to solve complex challenges and drive digital transformation worldwide. Join us in congratulating these organizations for their innovation, collaboration, and impactful results over the past year.See the 2026 Partner Award winners Apr 13 - Apr 17 We're excited to announce the Public Preview of Datastream’s metadata integration with Knowledge Catalog. This is the first step in our vision to provide a centralized, "single pane of glass" for all Datastream assets. The enhancement automatically synchronizes Streams, Connection Profiles, and Private Connections, eliminating data silos. It enhances discoverability, allowing you to search for Datastream assets using the same interface as BigQuery tables. Centralized governance is also provided, making your real-time data estate more transparent and easier to manage. Upgrading Apigee OPDK to 4.53 with OS your infrastructure using Google’s official, sequential upgrade path. Our Technical expert, Rakesh Talanki outlines how to upgrade Apigee OPDK to v4.53 while migrating to a supported OS (RHEL 8.x/9.x). This guide covers the "build-out" methodology, including multi-data center syncing, to ensure a stable, zero-downtime transitionRead the guide Cloud Run Worker Pools and CREMA: Powering Serverless AI at ScaleGoogle Cloud has announced the General Availability of Cloud Run worker pools, a new resource type designed specifically for pull-based, non-HTTP workloads. Unlike traditional Cloud Run services that scale based on request traffic, worker pools provide an "always-on" environment for background tasks like processing message queues or running large-scale AI inference. To support this, Google Cloud also open-sourced the Cloud Run External Metrics Autoscaler (CREMA). Built on KEDA, CREMA enables queue-aware autoscaling for worker pools, allowing them to dynamically scale based on external signals like Pub/Sub backlog or Kafka lag. Apigee Model Context Protocol (MCP) now Generally AvailableExpose enterprise APIs as MCP tools for agentic AI applications with the General Availability of MCP in Apigee. This update allows developers to transform APIs into AI-ready tools using OpenAPI Specifications, removing the need for local MCP servers or additional infrastructure. With managed endpoints and semantic search in API hub, you can now provide AI agents with secure, governed access to enterprise data at scale.Explore the MCP overview Apr 6 - Apr 10 Community TechTalk: Powering Retail Agents with ADK, UCP & Apigee XMove beyond basic chatbots to secure, transactional AI experiences. Join our Community TechTalk on April 16 to learn how Apigee X and Gemini build a "Trust Layer" for AI shopping assistants using UCP standards. We’ll demonstrate how to block prompt injections with Model Armor and implement cost governance via token limits to secure the path from discovery to purchase.Register for the TechTalk Implement multimodal capabilities in your AI agentsExplore three new reference architectures for building sophisticated multi-agent AI systems that can process and analyze multimodal data. To analyze disparate multimodal data and produce a high-confidence classification, see Classify multimodal data. To create a fluid conversational AI that processes audio and video streams in real time, see Enable live bidirectional multimodal streaming. To consolidate fragmented multimodal data into a searchable knowledge graph, see Multimodal GraphRAG resource orchestration. Automate SecOps workflows with an agentic AI systemTo accelerate incident response and reduce manual toil for your security team, you need a system that can automate remediation playbooks. Our new reference architecture helps you build an AI agent that orchestrates complex triage and investigation workflows across disparate security tools, such as SIEM, CSPM, and EDR, from a single interface. See the full guide to orchestrate security operations workflows. Mar 30 - Apr 3 ASEAN Webinar | April 30: Mastering Agentic Governance at Scale with GCPAs AI agents move from experimental pilots to core enterprise functions, governance is the critical next step. Join Google Cloud experts Shilpi Puri & Wely Lau for a webinar on April 30th at 11:00 AM SGT to learn how to architect a secure AI Management layer. We’ll explore developing governed MCP endpoints, managing tool access to enterprise data, and operationalizing AI with robust audit logs. The session includes a live demo of these frameworks in action on Google Cloud.RSVP here. Mar 23 - Mar 27 Turn your API sprawl into an agent-ready catalogAs organizations scale, APIs often become scattered across multiple gateways, creating "blind spots" that hinder AI adoption. To solve this, we’ve introduced two new capabilities for Apigee API hub: a new integration with API Gateway to automatically centralize API metadata into a single control plane, and a specification boost add-on (now in public preview). This add-on uses AI to enhance your API documentation with the precise examples and error codes that AI agents need to function reliably.Read the full blog post to get started. Webinar | April 16: AI Command & ControlAs AI agents move from experimental pilots to core enterprise functions, governance is the critical next step. Join Google Cloud expert Satyam Maloo for a webinar on April 16th at 11:00 AM IST to learn how to architect a secure AI Management layer. We’ll explore developing governed MCP endpoints, managing tool access to enterprise data, and operationalizing AI with robust audit logs. The session includes a live demo of these frameworks in action on Google Cloud.RSVP here. Modernizing and Decoupling Event Ingestion with ApigeeIn modern cloud-native architectures, decoupling producers from consumers is critical for building resilient systems. While Google Cloud Pub/Sub provides a scalable backbone, exposing it directly to external clients can introduce security and management overhead. This new guide explores how to leverage Apigee as an intelligent HTTP ingestion point. Learn how to handle security, mediation, and traffic control before messages reach your internal bus using the PublishMessage policy or Pub/Sub API.Read the full guide. Mar 16 - Mar 20 Gemini-powered Assistant in BigQuery Studio Gets Context-Aware UpgradesThe Gemini-powered assistant in BigQuery Studio has been transformed into a fully context-aware analytics partner, supporting your entire data lifecycle. The new capabilities include intelligent resource discovery, which uses Dataplex Universal Catalog search to find resources across projects and deep dive into metadata using natural language. You can now automate tasks, such as scheduling production-grade queries directly through the chat interface, and instantly troubleshoot long-running or failed jobs with root cause analysis and cost control auditing.Explore the full range of what the assistant can do. Mar 9 - Mar 13 Want to use Gemini to develop code and don't know where to start?This article includes a couple of examples of developing code with Gemini prompts; it identified changes that were needed to be made to get the code working. The article also refers to other examples that are available on github. Mar 2 - Mar 6 Introducing Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model. Built for high-volume developer workloads at scale, 3.1 Flash-Lite delivers high quality for its price and model tier. Gemini 3.1 Flash-Lite can tackle tasks at scale, like high-volume translation and content moderation, where cost is a priority. And it can also handle more complex workloads where more in-depth reasoning is needed, like generating user interfaces and dashboards, creating simulations or following instructions. Starting today, 3.1 Flash-Lite is rolling out in preview to enterprises via Vertex AI and developers via the Gemini API in Google AI Studio. TechTalk: Implementing Device Authorization Grant (RFC 8628) for ApigeeLearn how to authorize "headless" devices like Smart TVs or AI agents that lack keyboards and browsers. Join our Community TechTalk on March 19 (5PM CET / 12PM EDT) to go under the hood of Apigee X/Hybrid. We’ll cover the real-world mechanics of state management, polling, and human-in-the-loop security patterns for devices and autonomous agents. Register for the TechTalk Feb 23 - Feb 27 Pro-level image generation gets faster and more accessible with Nano Banana 2Nano Banana 2 is our state-of-the-art image generation and editing model. It delivers Pro-level image generation and editing at the speed you expect from Flash — making the quality, reasoning, and world knowledge you loved about Nano Banana Pro more accessible. Learn more about the model here. The Intelligent Path to Compliance: Transforming Regulatory QC with Google CloudReducing "Refuse to File" (RTF) risks and submission cycle times is critical for life sciences leaders. Google Cloud’s Regulatory Submission Semantic QC Auditor leverages Gemini and RAG architecture to transform Quality Control from a manual burden into an active, intelligent workflow. By automating semantic cross-referencing, narrative coherence checks, and dynamic guidance-based auditing, this solution ensures rigorous accuracy and auditability. Operating within a secure GxP-ready environment, it empowers teams to detect subtle inconsistencies and generate remediation plans without sacrificing data privacy. Learn more. Stop typing, start interacting! The Gemini Live Agent Challenge is here. Build immersive agents that can help you see, hear, and speak using Gemini and Google Cloud. Compete for your share of $80,000+ in prizes and a trip to Google Cloud Next '26!Submissions are open from February 16, 2026 to March 16, 2026. Learn more and register at .devpost.com Feb 9 - Feb 13 Introducing Gemini 3.1 Pro on Google Cloud. 3.1 Pro is a noticeably smarter, more capable baseline for complex problem-solving. We’re shipping 3.1 Pro at scale, building upon our goal to help you transform your business for the agentic future. Learn more about the model’s capabilities here. Gemini 3.1 Pro is available starting today in preview in Vertex AI and Gemini Enterprise. Developers can access the model in preview via the Gemini API in Google AI Studio, Android Studio, Google Antigravity, and Gemini CLI. Automate Storage Compatibility with GKE Dynamic Default Storage ClassesManaging storage across mixed-generation VM clusters in GKE just got easier. With the new Dynamic Default Storage Class, Google Kubernetes Engine automatically selects between Persistent Disk (PD) and Hyperdisk based on a node's specific hardware compatibility. This abstraction eliminates the need for complex scheduling rules and manual pairing, ensuring your volumes "just work" regardless of the underlying infrastructure. By defining both variants in a single class, you reduce operational overhead while maintaining peak performance and cost-efficiency across your entire cluster.Explore automated disk type selection Community TechTalk: AI-Powered Apigee Development with strofa.ioJoin the Apigee community on February 26 for a deep dive into strofa.io. Guest speaker Denis Kalitviansky will demonstrate how this new AI-powered tool automates and orchestrates Apigee development, from local emulators to large-scale hybrid environments. Discover how to scale your API management and streamline team collaboration using the latest in AI-driven automation. Register now to reserve your spot. Jan 26 - Jan 30 Simplify API Governance with Native OpenAPI v3 SupportEliminate integration debt and accelerate deployment velocity with the General Availability of OpenAPI v3 (OASv3) support for API Gateway and Cloud Endpoints. You no longer need to downgrade modern specifications to OASv2. Instead, you can now define API contracts and enforce critical policies—including telemetry, quotas, and security—using native Google-specific extensions directly within your OASv3 files. This update ensures your APIs are secure by design while remaining fully compatible with the modern developer ecosystem and Google Cloud’s AI services.Get started with OpenAPI v3 on API Gateway and Cloud Endpoints. Accelerate API Testing with the New Open Source API TesterStart validating your APIs with API Tester, a simple, YAML-based Test Driven Development (TDD) framework. Designed for the Apigee community, this tool allows you to write human-readable tests, run them instantly via a web client or CLI, and perform deep unit testing on Apigee proxies. With native support for JSONPath assertions and Apigee shared flows, you can verify everything from payload data to internal variables like proxy.basepath without leaving your terminal.Explore the API Tester guide and start testing your proxies today. Secure Sensitive Data with Kubernetes Secrets in Apigee hybridEnhance security in Apigee hybrid by accessing Kubernetes Secrets directly within your API proxies. This hybrid-exclusive feature keeps sensitive credentials within your cluster boundary and prevents replication to the management plane. It supports strict separation of duties: operators manage secrets via kubectl, while developers reference them as secure flow variables—ideal for high-compliance and GitOps workflows.Implement Kubernetes Secrets in your hybrid proxies. See the Console in a Whole New Light: Dark Mode is Now Generally Available in Google CloudElevate your cloud management workflow with Dark Mode, now generally available in the Google Cloud console. We have delivered a modern, cohesive, and accessible experience reimagined for maximum comfort and productivity—especially during extended working hours and low-light environments. Dark Mode can be enabled automatically based on your operating system's preference, or manually through the Settings -> Appearance menu.Switch to Dark Mode today to enjoy a modern, comfortable, and productive environment! Apigee X Networking: PSC or VPC Peering?Deciding how to connect Apigee X? Watch this video to compare Private Service Connect and VPC Peering. We break down northbound and southbound routing, IP consumption, and how to reach targets on-prem or in the cloud. Learn to simplify your architecture and avoid common networking "gotchas" for a smoother deployment.Watch the video. Jan 19 - Jan 23 Bridge the Gap: Excel-to-API Conversion in Apigee PortalsGive your customers more ways to connect! This new article by Tyler Ayers explores how to extend the Apigee Integrated Portal to support direct Excel file uploads. By leveraging SheetJS and custom portal scripts, you can enable users to upload spreadsheets, preview data, and submit it directly to your APIs, all without writing a single line of integration code themselves. It’s a powerful way to simplify onboarding for those who aren't yet API-ready.Learn how to build it. Elevate your applications with Firestore’s new advanced query engineWe have fundamentally reimagined Firestore with pipeline operations for Enterprise edition. Experience a powerful new engine featuring over a hundred new query features, index-less queries, new index types, and observability tooling to improve query performance. Seamlessly migrate using built-in tools and leverage Firestore’s existing differentiated serverless foundation, virtually unlimited scale, and industry-leading SLA. Join a community of 600K developers to craft expressive applications that maximize the benefits of rich queryability, real-time listen queries, robust offline caching, and cutting-edge AI-assistive coding integrations.Learn more about Firestore pipeline operations.
Perplexity is launching "Teammates," always-on agents that work through ongoing projects on their own virtual machines. The feature requires the Max plan at $200 per month, well above similar offerings from OpenAI or Anthropic. The market for always-on agents is getting crowded. The article Perplexity now has its own always-on AI agent appeared first on The Decoder.
Extend Claude Code to remote sessions on Amazon Bedrock AgentCore with security controls
Run Claude Code as a remote agent on Amazon Bedrock AgentCore. Each coding task runs in its own isolated session in your AWS account, every model call goes through Amazon Bedrock, and the result comes back as a GitHub pull request you review and merge.
Anthropic IPO Valuation Expectations Hit After AI Rout
Prospective investors in Anthropic's IPO are facing a weekend of uncertainty after a punishing post-election selloff in AI stocks prompted a rethink of the company’s expected valuation. Tom Mackenzie explains. (Source: Bloomberg)
Frontier Radar #5: If AGI is so close, why is everyone leaving? The neolabs and their bets
OpenAI is talking about the AGI era, and Nvidia CEO Jensen Huang says AGI has arrived. At the same time, co-creators of today's models are leaving OpenAI, Google DeepMind, and Meta to start their own labs, raising billions with no product to show. Why? They're betting that the current recipe alone won't be enough. We've sorted 45 neolabs by their research bets, mapped the limitations of today's AI they're trying to overcome, looked at what's already visible from their work, and explain why Nvidia always wins. The article Frontier Radar #5: If AGI is so close, why is everyone leaving? The neolabs and their bets appeared first on The Decoder.
Ramp data shows AI spending stalling just as Anthropic nears its IPO
AI usage keeps climbing, but spending has stalled. Price cuts and smarter cost controls among the biggest spenders could challenge investor assumptions about AI hypergrowth.
Anthropic IPO Valuation Under Pressure After Tech Rout
The selloff in tech stocks could hurt Anthropic. Potential buyers are discussing a valuation range of $1.2 trillion to $1.3 trillion for the company, which could go public before Thanksgiving. Mandeep Singh of Bloomberg Intelligence has more. (Source: Bloomberg)
Anthropic’s IPO Valuation Raises A Question: Is AI Worth Its Cost?
Investor scrutiny of Anthropic’s IPO raises a broader question: can AI’s productivity gains justify its enormous costs and translate into better lives for ordinary people?
METR finds Anthropic may have crossed its own AI acceleration warning threshold back in July
Nonprofit METR spent eleven weeks auditing Anthropic's internal research data and concluded that the pace of model development has roughly doubled, with about 80 percent of the speedup driven by AI-assisted research. Anthropic redacted the most informative evidence, though, which means the public has to rely on METR's judgment "much more than would be ideal." There are also skeptical voices inside the company. The article METR finds Anthropic may have crossed its own AI acceleration warning threshold back in July appeared first on The Decoder.
Thinking Machines' Inkling 2 Small claims top spot among western open-weight models
Thinking Machines, the startup from former OpenAI CTO Mira Murati, is releasing Inkling 2 Small, a mixture-of-experts model with 594 billion parameters. The company claims it's the strongest western open-weight model. Better agentic performance comes at a price, though, with token usage rising sharply. The article Thinking Machines' Inkling 2 Small claims top spot among western open-weight models appeared first on The Decoder.
Kubernetes, mark II? Why Google’s giving away gVisor, a code sandbox used by Anthropic and OpenAI
Google wants to emulate one of its biggest ever open-source success stories, donating three core AI agent infrastructure projects to The post Kubernetes, mark II? Why Google’s giving away gVisor, a code sandbox used by Anthropic and OpenAI appeared first on The New Stack.
Anthropic's $1.5 trillion IPO hits resistance as investors balk at valuation
Anthropic's IPO is in trouble as investors push back on the $1.5 trillion valuation and the tech market sells off. The article Anthropic's $1.5 trillion IPO hits resistance as investors balk at valuation appeared first on The Decoder.
Anthropic adds bank account access to Claude so users can track their spending
Anthropic is introducing a new feature in Claude called Personal Finance, which allows users to connect their bank and card accounts and ask questions about their finances. The article Anthropic adds bank account access to Claude so users can track their spending appeared first on The Decoder.
HSBC’s Max Kettner: The AI Trade Hasn’t Fundamentally Changed
Wall Street’s biggest trading desks spent weeks arguing that the stock-market rally would resume once the election was over. On Thursday, that call backfired spectacularly.Max Kettner, HSBC’s Chief Multi-Asset Strategist, argues that the sharp selloff in AI and US equities does not yet point to a fundamental break in the trade. He explains why positioning and forced selling may be driving the volatility, and how he is thinking about AI valuations — including why he’d be comfortable with an Anthropic IPO valuation below $1 trillion. (Source: Bloomberg)
Max Kettner, chief multi-asset strategist at HSBC Bank, discusses the global stocks rout as uncertainty around the AI trade mounts. Market stabilization could hinge on the Anthropic IPO, Kettner tells Bloomberg Television. "Let's see in the next two weeks if that goes through, that will give us some sort of relief," he says. (Source: Bloomberg)
