Kategorie: Google Cloud Platform

Supporting Viksit Bharat: Announcing our newest AI investments in India

India’s developer community, vibrant startup ecosystem, and leading enterprises are embracing AI with incredible speed. To meet this moment for India, we are investing in powerful, locally-available tools in India that can help foster a diverse ecosystem, and ensure our platform delivers the controls you need for compliance and AI sovereignty.
Today, we’re announcing a significant expansion of our local AI hardware capacity for customers in India. This increase in local compute, powered by Google’s AI Hypercomputer architecture with the latest Trillium TPUs, will help more businesses and public sector organizations train and serve their most advanced Gemini models in India. 
By unblocking new opportunities for high-performance, low-latency AI applications we can help customers meet India’s data residency and sovereignty requirements.
Enabling models and control: AI tools built for India’s context
While infrastructure is the foundation for digital sovereignty, it also requires control over the data and the models built on it. We’re committed to bringing our latest AI advancements to India faster than ever, with the controls you need.
Our new services would enable you to build, tune, and deploy models that understand India’s unique business logic and rich cultural context.

Next-generation models, here in India: Earlier this year, Google Cloud made Gemini available to regulated Indian customers by deploying Gemini 2.5 Flash with local machine-learning processing support. Now, we’re opening early testing for our latest and most advanced Gemini models to Indian customers. We’re also committing to launching the most powerful Gemini models in India with full data residency support. This is a first for Google Cloud, and a direct response to help meet the needs of our Indian customers.

More AI capabilities, available locally: We’re providing additional consumption models and pre-built AI-powered applications tailored for local context by launching a suite of new capabilities with data residency support in India:

Batch support for Gemini 2.5 Flash: Now generally available, this allows organizations to run high-volume, non-real-time AI tasks at a lower cost, all in India.

Document AI: Now in preview, we’re providing local support to help Indian businesses automate document processing.

More local context in your AI: Grounding on Google Maps is a new capability to ground model responses in real time from Google Maps, ensuring AI applications can provide accurate, location-aware answers.

A sovereign AI ecosystem: Building for India, with India
The most durable and decisive factor for long-term digital sovereignty lies in cultivating the “human element” — the skilled talent and innovation ecosystem. A sovereign AI future depends on building a strong local ecosystem.
Our strategy is to support India’s ecosystem-led approach by investing in the researchers, developers, and startups who are building for India’s specific needs.
Collaboration with IIT Madras: Google Cloud and Google DeepMind are thrilled to collaborate with IIT Madras to support the launch of Indic Arena. Run independently by the renowned AI4Bharat center at IIT Madras, this platform will allow users from all over India to anonymously evaluate and rank AI models on tasks unique to India’s rich multilingual landscape. To support this initiative, we are providing cloud credits to power this critical, community-driven resource.
“At AI4Bharat, our mission is to build AI for India’s specific needs. A critical part of this is having a neutral, standardized benchmark to understand how models are performing across our many languages,” said Mitesh Khapra, associate professor, IIT Madras. “Indic Arena will be that platform. We are delighted to have Google Cloud’s support to provide the initial compute power to bring this independent, public-facing project to life for the entire Indian AI community.”
We encourage all developers, researchers, and organizations in India to explore the Indic Arena platform and contribute to building a more inclusive AI future.
We invite the entire Indian ecosystem, from startups and universities to government bodies and enterprises, to take advantage of this new, dedicated capacity for Gemini in Vertex AI and our sovereign-ready infrastructure to build the next generation of AI that is built by Indians, for Indians.
Quelle: Google Cloud Platform

How scientists can leverage AI agents using Gemini Enterprise, Gemini Code Assist, and Gemini CLI

Scientific inquiry has always been a journey of curiosity, meticulous effort, and groundbreaking discoveries. Today, that journey is being redefined, fueled by the incredible capabilities of AI. It’s moving beyond simply processing data to actively participating in every stage of discovery, and Google Cloud is at the forefront of this transformation, building the tools and platforms that make it possible. 
The sheer volume of data generated by modern research is immense, often too vast for human analysis alone. This is where AI steps in, not just as a tool, but as a collaborative force. We’re seeing powerful new models and AI agents assist with everything from identifying relevant literature and generating novel hypotheses to designing experiments, running simulations, and making sense of complex results. This collaboration doesn’t replace human intellect; it amplifies it, allowing researchers to explore more avenues, more quickly, and with greater precision. 
At Google Cloud, we’re bringing together high-performance computing (HPC) and advanced AI on a single, integrated platform. This means you can seamlessly move from running massive-scale simulations to applying sophisticated machine learning models, all in one environment. 
So, how can you leverage these capabilities to get to insights faster? The journey begins at the foundation of scientific inquiry: the hypothesis.
AI-enhanced scientific inquiry
Every great discovery starts with a powerful hypothesis. With millions of research papers published annually, identifying novel opportunities is a monumental task. To overcome this information overload, scientists can now turn to AI as a powerful research partner.
Our Deep Research agent tackles the first step: performing a comprehensive analysis of published literature to produce detailed reports on a given topic that would otherwise take months to compile. Building on that foundation, our Idea Generation agent then deploys an ensemble of AI collaborators to brainstorm, evaluate, propose, debate, and rank novel hypotheses. This powerful combination, available in Gemini Enterprise, transforms the initial phase of scientific inquiry, empowering researchers to augment their expertise and find connections they might otherwise miss.
Go from hypothesis to results, faster
Once a hypothesis is formed, the work of translating it into executable code begins. This is where AI coding assistants, such as Gemini Code Assist, excel. They automate the tedious tasks of writing analysis scripts and simulation models by generating code from natural language and providing real-time suggestions, dramatically speeding up the core development process. 
But modern research is more than just a single script; it’s a complete workflow of data, environments, and results managed from the command line. For this, Gemini CLI brings that same conversational power directly to your terminal. It acts as the ultimate workflow accelerator, allowing you to instantly synthesize research and generate hypotheses with simple commands, then seamlessly transition to experimentation by generating sophisticated analysis scripts, and debugging errors on the fly, all without ever breaking your focus. Gemini CLI can further accelerate your path to impact by transforming raw results into publication-ready text, generating the code for figures and tables, and refining your work for submission. 
This capability extends to automating the entire research environment. Beyond single commands, Gemini CLI can manage complex, multi-step processes like cloning a scientific application, installing its dependencies, and then building and testing it—all with a simple prompt, maximizing your productivity.
The new era of discovery: Your expertise, AI agents, and Google Cloud
The new era of scientific discovery is here. By embedding AI into every stage of the scientific process – from sparking the initial idea to accelerating the final analysis – Google Cloud provides a single, unified platform for discovery. This new era of AI-enhanced scientific inquiry is built on a robust, intelligent infrastructure that combines the strengths of HPC simulation and AI. This includes purpose-built solutions like our H4D VMs optimized for scientific simulations, alongside the latest A4 and A4X VMs, powered by the latest NVIDIA GPUs, and Google Cloud Managed Lustre, a parallel file system that eliminates storage bottlenecks and allows your HPC and AI workloads to create and analyze massive datasets simultaneously. We provide the power to streamline the entire process so you can focus on scientific creativity – and changing the world! 
Join the Google Cloud Advanced Computing Community to connect with other researchers, share best practices, and stay up to date on the latest advancements in AI for scientific and technical computing, or contact sales to get started today.
Quelle: Google Cloud Platform

News you can use: What we announced in AI this month

2025 is off to a racing start. From announcing strides in the new Gemini 2.0 model family to retailers accelerating with Cloud AI, we spent January investing in our partner ecosystem, open-source, and ways to make AI more useful. We’ve heard from people everywhere, from developers to CMOs, about the pressure to adapt the latest in AI with efficiency and speed – and the delicate balance of being both conservative and forward-thinking. We’re here to help. Each month, we’ll post a retrospective that recaps Google Cloud’s latest announcements in AI – and importantly, how to make the most of these innovations. 
Top announcements: Bringing AI to you 
This month, we announced agent evaluation in Vertex AI. A surprise to nobody, AI agents are top of mind for many industries looking to deploy their AI and boost productivity. But closing the gap between impressive model demos and real-world performance is crucial for successfully deploying generative AI. That’s why we announced Vertex AI’s RAG Engine, a fully managed service that helps you build and deploy RAG implementations with your data and methods. Together, these new innovations can help you build reliable, trustworthy models.
From an infrastructure perspective, we announced new updates to AI Hypercomputer. We wanted to make it easier for you to run large multi-node workloads on GPUs by launching A3 Ultra VMs and Hypercompute Cluster, our new highly scalable clustering system. This builds on multiple advancements in AI infrastructure, including Trillium, our sixth-generation TPU.

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What’s new in partners and open-source 
This month, we invested in our relationship with our partners. We shared how Gemini-powered content creation in Partner Marketing Studio will help partners co-market faster. These features are designed to streamline marketing efforts across our entire ecosystem, empowering our partners to unlock new levels of success, efficiency, and impact. 
At the same time, we shared several important announcements in the world of open-source. We announced Mistral AI’s Mistral Large 24.11 and Codestral 25.01 models on Vertex AI. These models will help developers write code and build faster – from high-complexity tasks to reasoning tasks, like creative writing. To help you get started, we provided sample code and documentation.
And, most recently, we announced the public beta of Gen AI Toolbox for Databases in partnership with LangChain, the leading orchestration framework for developers building LLM applications. Toolbox is an open-source server that empowers application developers to connect production-grade, agent-based generative AI applications to databases. You can get started here.
Industry news: Google Cloud at the National Retail Federation (NRF) 
The National Retail Federation kicked off the year with their annual NRF conference, where Google Cloud showed how AI agents and AI-powered search are already helping retailers operate more efficiently, create personalized shopping experiences, and use AI to get the latest products and experiences to their customers. Check our new AI tools to help retailers build gen AI search and agents. 
As an example, Google Cloud worked with NVIDIA to empower retailers to boost their customer engagements in exciting new ways, deliver more hyper-personalized recommendations, and build their own AI applications and agents. Now with NVIDIA’s AI Enterprise software available on Google Cloud, retailers can handle more data and more complex AI tasks without their systems getting bogged down.
News you can use 
This month, we shared several ways to better implement fast-moving AI, from a comprehensive guide on Supervised Fine Tuning (SFT), to how developers can help their LLMs deliver more accurate, relevant, and contextually aware responses, minimizing hallucinations and building trust in AI applications by optimizing their RAG retrieval.
We also published new documentation to use open models in Vertex AI Studio. Model selection isn’t limited to Google’s Gemini anymore. Now, choose models from Anthropic, Meta, and more when writing or comparing prompts.
Hear from our leaders
We closed out the month with The Prompt, our monthly column that brings observations from the field of AI. This month, we heard from Warren Barkley, AI product leader, who shares some best practices and essential guidance to help organizations successfully move AI pilots to production. Here’s a snippet:
More than 60% of enterprises are now actively using gen AI in production, helping to boost productivity and business growth, bolster security, and improve user experiences. In the last year alone, we witnessed a staggering 36x increase in Gemini API usage and a nearly 5x increase of Imagen API usage on Vertex AI — clear evidence that our customers are making the move towards bringing gen AI to their real-world applications.
Stay tuned for monthly updates on Google Cloud’s AI announcements, news, and best practices. For a deeper dive into the latest from Google Cloud, read our weekly updates, The Overwhelmed Person’s Guide to Google Cloud.
Quelle: Google Cloud Platform

What’s new with Google Cloud – 2024

Week of Dec 16 – Dec 20Windows Server 2025 is now available on Google Compute Engine. We are excited to announce the general availability of Windows Server 2025 on Google Compute Engine. You can now run Windows Server 2025 Data Center, and Windows Server 2025 Data Center Core editions as well as Windows SQL Server 2022 on Windows Server 2025 with pay-as-you-go licenses. Customers that don’t already have a Microsoft Enterprise Agreement can use the Google Compute Engine’s provided image to take advantage of Google Cloud’s relationships with Microsoft for pay-as-you-go licenses that scale with your workload and offers premium support.Google Agentspace is here: unlock enterprise expertise for employees with agents that bring together Gemini’s advanced reasoning, Google-quality search, and enterprise data, regardless of where it’s hosted. Google Agentspace makes your employees highly productive by helping them accomplish complex tasks that require planning, research, content generation, and actions – all with a single prompt.Week of Dec 9 – Dec 13Best of N: Generating High-Quality Grounded Answers with Multiple Drafts. We are excited to announce that Check Grounding API has released a new helpfulness score feature. Building on top of our existing groundedness score, we now enable users to implement Best of N to improve RAG response quality without requiring extensive model retraining!A3 Ultra VMs powered by NVIDIA H200 Tensor Core GPUs and Hypercompute Clusters are in preview. A3 Ultra VMs offer a significant leap in performance over previous generations. Coupled with Hypercompute Cluster, which the infrastructure and workload provisioning, and ongoing operations of AI supercomputers up to tens of thousands of accelerators is seamless. This delivers a easy to manage, secure and high-performance cloud experience for AI workloads. Learn more about the offering!Week of Nov 25 – Nov 29The Cyber Threat Intelligence Program Design Playbook, Now Available. Mandiant Academy published a new on-demand course, Cyber Threat Intelligence (CTI) Program Design Playbook. Comprised of three 2-hour courses, this learning track explains Mandiant’s approach to design and build, efficiently operate, and enhance a CTI program. This is the inaugural track from the Academy’s updated approach to on-demand learning with succinct, operations-oriented lessons designed to provide the world’s cybersecurity professionals the answers and resources they need to succeed.Week of Nov 11 – Nov 15Subsea cable connectivity is coming to Tuvalu for the first time with the addition of the Tuvalu Vaka cable. Building on the Bulikula subsea cable system announced last year, this new network infrastructure is a collaboration among several partners including Australia, Japan, New Zealand, Taiwan, Tuvalu, Tuvalu Telecommunications Corporation and the United States, and will help reduce the digital divide in the Pacific.Week of Nov 4-8We are excited to announce the reCAPTCHA Password Leak Detection Container App, a new tool that makes it easier than ever to protect your users from account takeovers. This container app simplifies the integration of reCAPTCHA’s powerful password leak detection, allowing you to instantly detect compromised credentials and proactively prompt users to change their password before their account is compromised. With pre-built libraries and a streamlined process, you can significantly reduce integration time and enhance your website’s security with ease.Week of Oct 21-25We’re excited to announce GA support for scanning: Rocky Linux, Alma, SUSE (SLES), Red Hat (UBI), Chainguard, Wolfi & Google Distroless. These operating systems are now supported in both Artifact Registry scanning, as well as On Demand Scanning. When the Container Scanning API is enabled, any container with these new operating systems or distroless images will automatically be scanned for vulnerabilities when pushed to Artifact Registry. We’ve also upgraded our On Demand scan to include; NPM, Python, Ruby, Rust, .Net & PHP language packages. See all supported package types.Term Extension Now Available for Compute Engine Committed Use Discounts: You can now extend the term length of your Compute Engine resource-based Committed Use Discounts (“CUDs”) beyond the preset 1-year and 3-year options. CUDs offer significant cost savings for predictable workloads. You can now choose a CUDs term length beyond the original commitment end date that perfectly aligns with your workload needs, from one year and one day up to 6 years. Learn moreWeek of Oct 14-18Announcing Google Cloud Marketplace private offer enhancements that enable additional payment flexibility for enterprises, including when transacting generative AI models.Week of Oct 7-11We are excited to announce the launch of new Google Cloud Cortex Framework data integration and analytics solution content for BigQuery and Looker with Oracle EBS data. To learn more read our announcement blog.Google Cloud is partnering with leading AI and cybersecurity startups to accelerate their growth and innovation, through the ISV Startup Springboard program, announced this week at the Google Cloud Startup Summit. Learn more and register interest.Privileged Access Manager (PAM) is now Generally Available. The GA release offers new capabilities in addition to recently released public preview and includes features such as Pub/Sub integration for custom alerting and monitoring, alerts on IAM grant modifications outside of PAM, and integration with VPC Service Controls to tackle data exfiltration. Learn more.Week of Sept 23-27We are excited to announce that registration is open for the App Dev & Infrastructure Summit on October 30 (AMER) and October 31 (EMEA). Google Technology Fellows – our luminary technical leaders – and industry experts will share strategies and learnings on how to improve efficiency, reduce costs, and speed up AI innovation for your cloud and application infrastructure at this global digital event. Register here.Week of Sept 16-20Starting this week, Google Cloud customers with eligible support plans can access assistance for the Cluster Toolkit through the Cloud Console. Cluster Toolkit, formerly known as Cloud HPC Toolkit, is open-source software offered by Google Cloud which simplifies the process for you to deploy HPC, AI and ML workloads on Google Cloud. The Cloud Support team will handle filed cases, ensuring that users receive timely and effective support for their Cluster Toolkit implementations. Select ‘Cluster Toolkit’ as the sub-category under ‘Compute Engine’ when creating a support ticket in your Cloud Console to get in touch about any Cluster Toolkit issues.Backup and DR service is excited to announce the public preview of backup vaults and simplified VM backup offering. Backup vaults provide secure backups for cyber resilience through immutable and indelible backups for VMs and databases, delivering security against accidental or malicious data deletion. Simplified Compute Engine VM backup with a fully-managed experience, directly integrated into the cloud console makes backing of VMs as easy as 1-2-3. The solution also enables backup admins to empower application developers to self-protect their VMs while retaining centralized governance and oversight. Read the full blog to learn more and try out the new features.Week of Sept 2-6We’re excited to share that Topaz will be extended to Taiwan. Announced in 2022, the transpacific subsea cable system was the first to connect Canada and Japan. Now, with the extension of Topaz to Taiwan, we’ll provide the region with increased reliability and resilience for network operators, for Google, and for users.Week of Aug 26-30We are excited to announce the general availability of Instant snapshots for Google Compute Engine Persistent Disks, which provide near-instantaneous, high-frequency, point-in-time checkpoints of a disk that can be rapidly restored as needed. Read the full blog to try it out.In response to customer and partner requests for pollen data in Japan, we are excited to announce that data for Japanese Cedar and Cypress trees-the 2 main sources of pollen allergens in Japan-have been added to our Pollen API from Google Maps Platform.Week of Aug 19-23We are excited to announce we’re adding support for NVIDIA L4 GPUs to Cloud Run, in preview. Developers love Cloud Run for its simplicity, fast autoscaling, scale-to-zero capabilities, and pay-per-use pricing. Those same benefits come into play for real-time inference apps serving open gen AI models. Check out this launch blog. Also watch demos from this launch event webinar Run AI on Cloud run.We are excited to announce that Google Cloud Functions is now Cloud Run functions — event-driven programming in one unified serverless platform. This goes beyond a simple name change. We’ve unified the Cloud Functions infrastructure with Cloud Run, and developers of Cloud Functions (2nd gen) get immediate access to all new Cloud Run features, including NVIDIA GPUs. Read the launch blog and watch demos from this launch event webinar Run AI on Cloud run.Week of Aug 5-9Google’s Workforce Identity federation now enables Microsoft Entra ID users to access Google BigQuery from Microsoft Power BI with Single-Sign-On. No users or groups need to be provisioned in Google Cloud as Workforce identity Federation leverages a syncless federation capability using attribute based access control to authorize access to Google BigQuery using Microsoft Entra user attributes such as user group membership. You can refer to our documentation to learn more.We are excited to announce the preview of SQL support in Bigtable to bring Google’s pioneering NoSQL database to a broader developer audience. Bigtable leverages GoogleSQL ─the same SQL dialect used by BigQuery─ making it easier to use Bigtable as low-latency analytics serving layer in combination with BigQuery’s newly announced continuous queries but does so with extensions to support its signature data model so you can use SQL without giving up on all the flexibility that comes with a NoSQL database. It also simplifies migrations from open source databases such as Apache Cassandra. With over 100 new functions from JSON processing capabilities, kNN for GenAI and HLL for real-time analytics, SQL opens the door to many new possibilities with Bigtable. Learn more in our detailed blog post.We are excited to announce the public preview of BigQuery continuous queries, a groundbreaking new feature that empowers users to run continuously processing SQL statements that can process, analyze, and transform data as new events arrive in BigQuery, ensuring insights are always up to date. Native integration with the Google Cloud ecosystem unlocks the ability of Vertex AI and Gemini to perform machine learning inference on incoming data in real time. As well as streaming replication of continuous query results to Pub/Sub topics, Bigtable instances, or other BigQuery tables. Read the full blog and try it out!AlloyDB’s AutoPilot capabilities- Automatic memory management, Adaptive AutoVacuum, Automatic storage tiering ,Automatic data columnarization and query rewrite- makes management super efficient and easy. AlloyDB eliminates the drudgery of maintaining a PostgreSQL database by using, behind the scenes , advanced self-tuning machine learning algorithm. In this blog we will look into a real world example of AlloyDB Adaptive AutoVacuum in work and how AlloyDB Cluster Storage Space is ReleasedGoogle Cloud Identity Platform, our consumer identity solution, now supports Passkeys. With Passkeys, developers can authenticate their app’s end users securely, protecting them from account takeover attacks like phishing and leaked credentials. To join the private preview, contact your Google account team.Week of July 15-19Google Cloud is excited to launch the Modern SecOps Masterclass, now available on Coursera. This course equips security professionals with cutting-edge skills to modernize their Security Operations Centers (SOCs) using our Autonomic Security Operations framework and Continuous Detection, Continuous Response (CD/CR) methodology. Read the full blog and enroll now.Learn how to potentially achieve a strong consistency in Cloud Bigtable for your next big data solution. Bigtable offers high throughput at low latency. It is ideal for storing large amounts of data in a key-value store while supporting high read and write throughput at low latency for fast access. Bigtable provides eventual consistency as well as strong consistency. This blog talks about achieving strong data consistency in a multi-cluster Bigtable instance. Read the full blog.Week of June 24-28Introducing Google Cloud Marketplace Channel Private Offers, enabling customers, ISV partners, and channel partners to efficiently transact private offers via reseller-initiated sales of third-party solutions listed on the Google Cloud Marketplace. This differentiated program also empowers channel partners to manage the customer relationship from billing, collections to revenue recognition. Read the full blog.A blog on benchmark study (collaborated with Yahoo) by comparing the cost and performance of Apache Flink and Google Cloud Dataflow for two specific streaming data processing use cases. The goal of the study was to determine the most cost-effective platform for these use cases by establishing a fair comparison methodology and controlling variables such as throughput and workload. The results indicate that, with some optimization on Dataflow can perform on-par with Apache Flink. Read the full blog.A Blog on Secure Gateways: Mutual TLS for Ingress Gateway Secure Gateways: Mutual TLS for Ingress Gateway,” discusses the implementation of mutual TLS (mTLS) for enhanced security in ingress gateways. It explains how mTLS ensures both client and server authentication through certificates, going beyond the traditional server-only verification. The article explores the setup process and the benefits of using mTLS, emphasizing its role in establishing secure communication channels in modern cloud architectures. Read the full blog.A Blog on Wildcard certificates with Ingress Gateway “Wildcard certificates with Ingress Gateway” provides a guide on how to use wildcard certificates to secure multiple services behind a single Istio Ingress Gateway. This simplifies certificate management and improves the user experience by allowing seamless connections across different services within the same domain. The article demonstrates the configuration process step-by-step and explains how wildcard certificates are matched to incoming requests. Read the full blogWeek of June 17-21Learn how to leverage BigQuery vector search to analyze your logs and asset metadata stored in BigQuery. Using vector search, you can find semantically similar logs which can be helpful in several use cases such as outlier detection, triage and investigation. This how-to blog walks you through the setup from processing logs, generating vector embeddings, to analyzing vector search results. It includes sample SQL queries which can be adapted for your own logs and use case. Read the full blog.Nuvem, first announced last year, is a transatlantic subsea cable system that will connect Portugal, Bermuda, and the United States. We are now working with the Regional Government of Azores to enable extending the system to the Azores as well. Named after the Portuguese word for “cloud,” Nuvem will improve network resiliency across the Atlantic, helping meet growing demand for digital services and further establishing its landing locations as digital hubs.Week of June 10-14General Availability of A3 Mega, a new instance type in the A3 VM family. A3 Mega is powered by the NVIDIA H100 Tensor Core GPU, delivers a 2.4x improvement in large scale training performance over multiple A3 instances.2x the GPU-to-GPU networking bandwidth over A3 Instances.Enhanced GPUDirect-TCPXO networking offloads GPUDirect memory access from the CPU, providing direct access through through the NIC (Network Interface Card) to GPU memory, based on Titanium TOPs, which improves performance of multi-node distributed training workloads.Simplify your Network: The Cloud Networking Product Management and Engineering team will be traveling across US cities in June/July and Sept. Learn how Cross-Cloud Network can transform your infrastructure. The workshop will address Cross-Cloud Networking for hybrid and multicloud enterprises with distributed applications, internet-facing content and applications, security, and AI-assisted network operations with Gemini Cloud Assist. Join us at one of the following Google office locations and meet the experts who will share the latest innovations, use cases, and demos. Register here.Learn how you can leverage the cloud deployment archetypes (zonal, regional, multi-regional, global, hybrid, & multicloud) to architect cloud topologies that meet your workload’s requirements for reliability, cost, performance, & operational simplicity. Read the full blog.Week of May 20-24Maximize performance and optimize spend with Compute Engine’s latest General Purpose VMs, N4 and C4. N4’s flexible configurations and price-performance gains help optimize costs, while C4 provides top-tier performance for demanding applications. With N4 and C4, you get tailored solutions for all your general-purpose workloads, so you can lower the total cost of running your business without compromising on performance or workload-specific requirements. Learn more here.Week of Apr 22 – April 26Simplify your connectivity to Google by using a Verified Peering Provider to connect to Google, instead of using Direct Peering. Verified Peering Providers handle all of the complex connectivity allowing you to focus on your core business. Learn more here.Week of Apr 15- Apr 19New training in AI, data analytics and cybersecurity, designed to expand onramps to tech careers through colleges and employers. Learn more.Week of Apr 1- Apr 5Security Command Center (SCC) Enterprise is now generally available (GA). It is the industry’s first cloud risk management solution that converges cloud security and enterprise security operations into a single platform, supercharged by Mandiant expertise and AI. Learn more in our announcement blog.Identify common container runtime attacks, analyzes suspicious code, and use natural language processing to pinpoint malicious scripts with GKE threat detection, powered by Security Command Center. Now in public preview.Get a fully managed compliance service that automatically delivers end-to-end coverage for GKE, scanning for issues against the most important benchmarks with GKE compliance, now in public preview. Near-real-time insights are available in a centralized dashboard, with compliance reports automatically produced for you.Streamline your GCE backup strategy! With tag-based backups in Google Backup and DR, protection is automated – new VMs with the right tags are protected immediately, saving you time and increasing reliability. Read more on the blog here. Differential privacy enforcement with privacy budgeting is now available in BigQuery data clean rooms so organizations can prevent data from being reidentified when it is shared.Week of Mar 18- Mar 22Google Kubernetes Engine (GKE) and NVIDIA NeMo framework are used to train large language models (LLMs). Due to the increasing demand for efficient and scalable training of LLMs, the need for GPUs at a large scale with high speed networking is rapidly growing. GKE offers a comprehensive set of features that make it suitable for enterprise-level training and inference. This blog post shows how generative AI models can be adapted to your use cases by demonstrating how to train models on Google Kubernetes Engine (GKE) using the NVIDIA NeMo framework.Cloud Run now supports volume mounts! Mount a Cloud Storage bucket or NFS file share as a volume to easily serve static assets, access app configuration data, or access an AI/ML model. Learn more in our blog post.Week of Mar 11- Mar 15Datastream adds support for SQL Server sources, now in preview. With existing support for MySQL, PostgreSQL, and Oracle, support for SQL Server sources extends the reach of Datastream and empowers you to replicate data from a range of relational sources to several Google Cloud services, such as BigQuery, Cloud Storage, AlloyDB, and Spanner. Read more in the blog here.Week of Feb 5- Feb 9Check out this new blog and learn more about the Integrated Commerce Network (ICN) delivered by Kin + Carta and built on Google Cloud. The ICN features 3 of our premier digital commerce partners for an integrated end-to-end solution including Bloomreach, commercetools and Quantum Metric.Week of Jan 29- Feb 2IDC finds 318% ROI from migrating to Google Cloud IaaS: Check out the latest IDC research study to learn how organizations worldwide are benefitting by adopting Google Cloud Infrastructure as a Service.Week of Jan 15-19Check out the latest generative AI training available from Google Cloud : Take a look at our top ten trainings in Duet AI to help boost your productivity in 2024.Week of Jan 1-5The year in Google Cloud: Top news of 2023: A look back at the biggest stories of 2023 from Google Cloud, covering generative AI, DevOps, containers, data and databases, security, and more.
Quelle: Google Cloud Platform

The Year in Google Cloud – 2024

If you’re a regular reader of this blog, you know that 2024 was a busy year for Google Cloud. From AI to Zero Trust, and everything in between, here’s a chronological recap of our top blogs of 2024, according to readership. You’ll probably see some favorites on this list, and discover a few that you missed the first time around. 
January
We started the new year strong, removing data transfer fees for anyone moving data off of our platform. Translation: Anyone doing cool things on Google Cloud (like using generative AI to analyze their microservices deployment) is doing it because they want to, not because they have to. And in business news, we shared how to make the most out of your data and AI in the coming year. 

Cloud switching just got easier: Removing data transfer fees when moving off Google Cloud

Figuring out microservices running on your GKE cluster with help from Duet AI

Transform: Five ways your data can thrive with generative AI in 2024

February
From local GPUs, to model libraries, to distributed system design, the second month of 2024 was the first of many to come where AI topics dominated the charts. Our Transform team explored gen AI’s impact on various industries.

No GPU? No problem. localllm lets you develop gen AI apps on local CPUs

Google Cloud expands access to Gemini models for Vertex AI customers

Coming of age in the fifth epoch of distributed computing, accelerated by machine learning

Your RAGs powered by Google Search technology, part 1

Transform: Putting AI to work: Where gen AI is impacting industries in 2024

March
If it wasn’t already obvious, this month’s top-read blogs showed that our core audience is developers pushing the boundaries of innovation. Business leaders, meanwhile, read about best practices for securely deploying AI on Google Cloud. 

Domain-specific AI apps: A three-step design pattern for specializing LLMs

Announcing Anthropic’s Claude 3 models in Google Cloud Vertex AI

Transform: To securely build AI on Google Cloud, follow these best practices

April
Watch out, here comes Google Cloud Next, where we made a record 218 announcements; the top three are listed here. Readers were also keen to hear about how Citadel Securities built out a research platform on Google Cloud. 

Introducing Google Axion Processors, our new Arm-based CPUs

Powering Google Cloud with Gemini

BigQuery is now your single, unified AI-ready data platform

Transform: How Citadel Securities is reimagining quantitative research on the cloud

May
We don’t always get it right, but when there’s a problem, we’re committed to providing you with accurate, timely information with which to make your own assessments. We’re also committed to making you, and customers like McLaren Racing, go really, really fast when developing new AI-based applications.  

Sharing details on a recent incident impacting one of our customers

RSA ’24: Introducing Google Threat Intelligence: Actionable threat intelligence at Google scale

Announcing Trillium, the sixth generation of Google Cloud TPU

Improving connectivity and accelerating economic growth across Africa with new investments

Transform: AI at the track: How McLaren Racing leverages terabytes of data each race for a winning edge

June
Whether you wanted to modernize your databases, deliver higher system reliability, create really cool AI-powered apps, or learn how legendary companies tackle data management, the Google Cloud blog was your go-to source midway through the year. 

Accelerating cloud transformation with Google Cloud and Oracle

Free to be SRE, with this systems engineering syllabus

Announcing Anthropic’s Claude 3.5 Sonnet on Vertex AI, providing more choice for enterprises

Google Cloud expands grounding capabilities on Vertex AI

Transform: We are Legend: How Goldman Sachs’ open-source data platform democratizes information

July
We talk a lot about “meeting customers where they are.” Sometimes that means a disaster zone, a remote research station, or a truck cruising down the highway. Over on Transform, you read about the history of our custom Axion and TPU chips. 

Bringing cloud and AI capabilities to the tactical edge: Google Distributed Cloud air-gapped appliance is generally available

VMware Cloud Foundation on Google Cloud VMware Engine: 20% lower price and up to 40% in migration incentives

Transform: Why Google keeps building custom silicon: The story behind Axion

Transform: TPU transformation: A look back at 10 years of our AI-specialized chips

August
Just when you thought you knew how to run AI inference, your available graph database options, or the name of Google Cloud’s event-driven programming service, we went and changed things up. We like to keep you on your toes And business readers got a first look at AI agents — more to come on this. 

Run your AI inference applications on Cloud Run with NVIDIA GPUs

GenOps: learning from the world of microservices and traditional DevOps

Real-time in no time: Introducing BigQuery continuous queries for up-to-the-minute insights

Introducing Spanner Graph: Graph databases reimagined

Cloud Functions is now Cloud Run functions — event-driven programming in one unified serverless platform

Transform: So much more than gen AI: Meet all the other AI making AI agents possible

September
You’ve been generating (and storing) business data for years. Now, we’re making it easier for you to make sense of, and actually use, that data. Speaking of using data, the Transform team compiled a jaw-dropping list of the real-world ways customers are using gen AI in their organizations. 

Chat with your business data – Conversational Analytics comes to Gemini in Looker

Find key insights faster with a new contribution analysis model in BigQuery ML

Transform: 185 real-world gen AI use cases from the world’s leading organizations

October
According to this month’s most-read blog, 75% of you rely on AI for at least one daily professional responsibility, including code writing, information summarization, and code explanation, and experience “moderate” to “extreme” productivity gains. So it was no big surprise that business leaders wanted to read about how to develop an AI strategy. 

Highlights from the 10th DORA report

Gemini models are coming to GitHub Copilot

Revolutionizing SQL with pipe syntax, now available in BigQuery and Cloud Logging

BigQuery tables for Apache Iceberg: optimized storage for the open lakehouse

Transform: How to build an effective AI strategy

November
Not content to hold the existing record for most nodes in a Kubernetes cluster (15,000), we went ahead and more than quadrupled it, to the delight of AI unicorns. But whether you work for an AI unicorn, or just a plain old zebra, all Google Cloud users needs to start using multi-factor authentication next year, as well as learn how to avoid comman AI pitfalls. 

65,000 nodes and counting: Google Kubernetes Engine is ready for trillion-parameter AI models

Mandatory MFA is coming to Google Cloud. Here’s what you need to know

Transform: Unlocking gen AI success: Five pitfalls every executive should know

December
We’re closing out the year on an AI highnote, with the availability of amazing new image and video generation models, as well as the new Trillium TPU, which Google used to train Gemini 2.0, our most capable AI model… yet. Be on the lookout for how these technologies — and many others — will reshape your industry and how you work in the coming year. 

Veo and Imagen 3: Announcing new video and image generation models on Vertex AI

Announcing the general availability of Trillium, our sixth-generation TPU

Introducing Google Agentspace: Bringing AI agents and AI-powered search to enterprises

Transform: AI’s impact on industries in 2025

To all our loyal readers and customers, thanks for an amazing 2024, and here’s to an even more exciting and productive 2025!
Quelle: Google Cloud Platform

AI Playground: Where learning and innovation converge in the heart of London

AI is rapidly transforming industries and redefining the future of work. However, many organizations face a significant hurdle: bridging the knowledge gap and acquiring the necessary skills to effectively harness the power of AI. 
Recognizing this challenge, Google Cloud is set to launch the AI Playground in Shoreditch, Central London, in the first quarter of 2025. This innovative space will serve as a dynamic hub for businesses and individuals to demystify AI, explore its potential, and develop practical expertise.
More than a showcase — dive deep into AI
Google’s powerful Gemini model family — now in its supercharged second generation — takes center stage at the AI Playground, featuring several interactive demos that put its multimodal and agentic capabilities on display. Among the capabilities guests can experience and experiment with first hand are Gemini’s ability to analyze complex data, generate creative formats, and power innovative solutions.
The AI Playground is much more than a technology showcase. 
We’ve built the space to serve as an immersive learning environment where visitors can actively engage with AI, participate in hands-on workshops and hackathons, and connect with Google Cloud AI experts. This unique approach fosters a deeper understanding of AI concepts and encourages experimentation with cutting-edge tools and techniques.

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Addressing the AI skills gap
The AI Playground directly addresses the growing need for AI skills development in today’s rapidly evolving technological landscape, providing a dedicated space for:

Hands-on experimentation: Gain practical experience with cutting-edge AI tools and techniques, moving beyond theoretical knowledge to real-world application.

Skills development: Build on-demand AI skills through interactive workshops and hackathons led by Google Cloud experts, equipping individuals and teams with the expertise needed to thrive in the AI era.

Community building: Connect with fellow AI enthusiasts, share knowledge, and facilitate collaboration, creating a vibrant ecosystem for learning and innovation.

Real-world inspiration: Explore AI applications across diverse industries and discover new possibilities for your organization, sparking creativity and driving the development of novel AI solutions.

Empowering the future of AI
By providing accessible learning opportunities and fostering a thriving AI community, the AI Playground empowers individuals and businesses to embrace the transformative power of AI and contribute to shaping a better future. It’s a place where curiosity meets innovation, learning is hands-on, and  the potential of AI is unlocked. Mark your calendars for Q1 2025 and prepare to embark on your AI journey at Google Cloud’s AI Playground.
Quelle: Google Cloud Platform