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Livescience

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Quantum computing breakthrough could make 'noise' — forces that disrupt calculations — a thing of the past

Scientists have discovered a groundbreaking method to shield quantum information from 'noise' and potentially enable the construction of practical quantum computers.
Quantum computers rely on quantum entanglement, which allows for faster parallel processing. However, noise disrupts this 'coherence' and increases the error rate.
A team of physicists has found a way to preserve quantum information by encoding it in the topology of entangled photons, making it resilient to noise.
This approach could contribute to the development of quantum computers and networks that can overcome noise in any environment.

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VentureBeat

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Google’s new Ironwood chip is 24x more powerful than the world’s fastest supercomputer

Google Cloud unveiled its seventh-generation Tensor Processing Unit (TPU) called Ironwood, claiming it delivers more than 24 times the computing power of the world’s fastest supercomputer.
Ironwood is the first TPU purpose-built for inference, providing computational power for deploying trained AI models.
With scaled deployment, Ironwood delivers 42.5 exaflops, dwarfing El Capitan's 1.7 exaflops, and offers 4,614 teraflops peak compute per chip.
Each Ironwood chip features 192GB of High Bandwidth Memory (HBM) and 7.2 terabits per second memory bandwidth per chip.
Ironwood delivers twice the performance per watt compared to the previous TPU generation, enhancing power efficiency.
Google observed a 10x increase in AI compute demand over eight years, emphasizing the need for specialized architectures like Ironwood for inference.
Ironwood's focus on inference optimization signifies a shift towards deployment efficiency and reasoning capabilities in the AI landscape.
Google positions Ironwood as a foundation for advanced AI models like Gemini 2.5, emphasizing reasoning tasks over simple pattern recognition.
Google also announced Cloud WAN and software offerings for AI, aiming to enhance networking performance and machine learning runtime scaling.
Google's vertical integration in developing TPUs translates into competitive advantages in AI offerings for enterprise customers.

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Siliconangle

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Google Cloud opens its global network for enterprise wide-area network use

Google Cloud has launched Cloud WAN, a fully managed enterprise backbone designed for wide-area network architectures.
The offering provides a unified approach to site, application, and user connectivity with optimal performance and lower total cost of ownership compared to multiprotocol label switching services.
Cloud WAN leverages Google's global network, offering up to 40% faster performance compared to public internet connections and a 40% lower total cost of ownership.
The service supports high-performance, cross-region connectivity for global organizations and enables branch and campus networks to connect to the cloud with built-in security and low latency.

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Siliconangle

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Google brings the power of AI to healthcare with new partnerships

Google Cloud is expanding partnerships in the healthcare industry to leverage AI for improving patient care and reducing workload for healthcare professionals.
Partnerships include collaborations with Highmark Health, Hackensack Meridian Health Inc., and Seattle Children’s Hospital, introducing AI-powered tools like Pathway Assistant.
Highmark Health is implementing generative AI tools for its employees, with a focus on improving efficiency and access to information.
Hackensack Meridian Health is utilizing AI to streamline clinical note summarization and relieve strain on clinicians through innovative solutions.
Seattle Children’s Hospital has developed Pathway Assistant, which integrates text, images, and medical literature to aid in decision-making, improving patient outcomes.
The AI assistant can quickly develop diagnoses and research plans, reducing the time taken when compared to manual processes.
Initial pilots of the AI show promise in enhancing patient care by freeing up doctors' time and providing access to crucial medical information.
The collaboration between Google and healthcare providers aims to address the challenge of accessing complex healthcare guidelines efficiently using targeted AI solutions.
The use of AI in healthcare is rapidly evolving, offering innovative solutions that improve workflow, patient care, and access to critical information.
The partnerships signify a move towards utilizing advanced technology to empower healthcare professionals and enhance the quality of care provided to patients.

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Siliconangle

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Google boosts AI and agentic features across BigQuery and AlloyDB

Google Cloud introduces new data analytics capabilities focused on unstructured data for AI model training.
Enhancements include AI agents, autonomous data foundation, PostgreSQL-compatible AlloyDB, and Oracle DBMS support on Google Cloud.
Specialized agents in BigQuery and Looker assist in data engineering, science, and user experience tasks.
Features like conversational queries, Colab's data science agent, and Looker's AI-driven functions provide advanced analytics capabilities.
BigQuery Knowledge Engine uses large language models for metadata generation and semantic search.
BigQuery Notebook improvements streamline data science tasks with intelligent SQL cells and collaborative features.
New BigQuery AI Query Engine integrates AI models for processing unstructured data like images.
Expanded integrations include support for Apache Kafka, Apache Spark, and continuous queries for streaming data analysis.
AlloyDB gains agentic search capability, natural language support, and enhanced SQL functionality.
Google Cloud adds support for Oracle databases and introduces a Database Migration Service for SQL Server-to-PostgreSQL migrations.

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Nvidia

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NVIDIA Brings Agentic AI Reasoning to Enterprises With Google Cloud

NVIDIA is collaborating with Google Cloud to bring agentic AI to enterprises.
The collaboration provides enterprises with access to the Google Gemini family of AI models using the NVIDIA Blackwell HGX and DGX platforms and NVIDIA Confidential Computing for data safety.
Enterprises can locally harness the Gemini models, ensuring data sovereignty and compliance with regulatory requirements.
The collaboration enables enterprises to unlock the full potential of agentic AI by combining breakthrough performance and confidential computing capabilities.

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Siliconangle

348

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Google’s cloud-based AI Hypercomputer gets new workhorse with Ironwood TPU

Google Cloud is upgrading its AI Hypercomputer infrastructure stack with the new Ironwood TPU to enhance AI workloads performance, announced at Google Cloud Next 2025.
Ironwood is Google's seventh-generation TPU designed for advanced AI models, known for handling massive amounts of parallel processing efficiently.
It is the most powerful TPU accelerator ever built by Google, able to scale to a megacluster of 9,216 liquid-cooled chips connected by advanced Inter-Chip Interconnect technology.
Ironwood was created to cater to new 'thinking models' with mixture-of-experts techniques, enabling advanced reasoning with minimal data movement and latency.
With 192 GB high-bandwidth memory per chip, Ironwood provides faster processing and data transfers, enhancing performance significantly.
Google Cloud customers can choose from two initial configurations of Ironwood clusters: 256-chip or 9,216-chip cluster, with a total performance of 42.5 exaflops at peak performance.
Ironwood's enhancements include low-latency ICI network, HBM bandwidth boost, and bidirectional bandwidth improvements, offering more rapid data access for memory-intensive workloads.
Additionally, Google's infrastructure stack includes Nvidia's advanced AI accelerators, hardware improvements like higher-performance block storage, and software updates for better utilization and performance.
New software features such as Pathways runtime, Cluster Director for workload optimizations, and improved observability tools are added to boost AI infrastructure efficiency.
Expanded inference capabilities in AI Hypercomputer, including Inference Gateway in GKE and GKE Inference Recommendations tool, aim to simplify infrastructure management and offer optimized performance.

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Siliconangle

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CrowdStrike expands Google Cloud partnership to secure AI development at scale

CrowdStrike expands partnership with Google Cloud to secure AI development.
This partnership aims to deliver comprehensive security for AI innovation using CrowdStrike Falcon Cloud Security.
CrowdStrike offers deep integrations to enhance protection across the entire AI lifecycle on Google Cloud.
Key features of the expanded integrations include AI image scanning, compliance enforcement, and continuous monitoring.

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Siliconangle

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With agentic AI, Google Cloud is transforming almost every aspect of app development

Google Cloud is integrating generative artificial intelligence-powered assistance into application development to boost the capabilities of human software developers.
At Google Cloud Next 2025, they introduced a new AI-powered cloud for developers and operators to streamline software development.
The new Application Design Center provides a visual approach to designing application templates and collaborating with other developers.
Google's AI agents, Gemini Code Assist and Gemini Cloud Assist, automate various aspects of app development and infrastructure management.
Gemini Code Assist can generate code, check for issues, provide test cases, evaluate AI models, and create documentation.
Developers can interact with Gemini Code Assist via a Kanban board and connect it to third-party platforms with prebuilt tools.
Gemini Cloud Assist automates infrastructure design, deployment, monitoring, and maintenance, reducing the workload on engineering teams.
Gemini Cloud Assist Investigations helps troubleshoot and resolve issues, while the Cost Optimization dashboard aids in performance and cost optimization.
Integration capabilities have been expanded, with Gemini Cloud Assist available in various Google Cloud services for enhanced efficiency.

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VentureBeat

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Google Cloud intros AI security agents, unified security platform to consolidate ops, triage, threat intel

Google Cloud introduces AI security agents and a unified security platform to consolidate operations, triage, and threat intelligence.
The new Google Unified Security platform creates a single, searchable security data fabric across the entire attack surface.
Powered by Gemini and semi-autonomous AI, Google Unified Security offers preemptive security by providing visibility and integration of data from various sources.
Enterprises aim to anticipate and remediate threats before they materialize, utilizing Google's platform that integrates Chrome Enterprise and Google Threat Intelligence.
The platform enhances security posture through browser behavior, threat hunting, and security validation integrations, offering a holistic defense against today's complex threat landscape.
Google Cloud's collaboration with Deloitte Cyber enhances centralized data fabric, unified SOC workflows, and agentic AI automation, transforming security operations for clients.
With the introduction of new semi-autonomous Gemini security agents, Google advances in incorporating AI agents for alert triage and malware analysis to reduce manual workload and drive strategic program transformation in security operations.
The AI agents aim to reduce toil, build cyber-resilience, and transform security programs by working alongside human analysts to focus on complex issues.
Google Cloud also updates its Security Command Center with specific AI protections and a Model Armor for safeguarding AI systems against threats.
Additionally, Google Cloud introduces a data security posture management tool and a compliance manager to help enterprises discover and protect sensitive data, enforce security controls, and ensure compliance.

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VentureBeat

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Google’s new Agent Development Kit lets enterprises rapidly prototype and deploy AI agents without recoding

Google has announced the launch of its Agent Development Kit (ADK) to simplify the creation of AI agents.
ADK allows users to build an AI agent in under 100 lines of code and supports the Model Context Protocol (MCP).
Google also introduced Agent Engine, a managed runtime dashboard for production usage.
Google's ADK and other agentic AI offerings put the company in competition with other agent providers like OpenAI and Amazon.

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VentureBeat

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Google Cloud Next ’25: New AI chips and agent ecosystem challenge Microsoft and Amazon

Google Cloud is intensifying its focus on artificial intelligence with new technologies like Ironwood TPU and Cloud WAN.
Ironwood is Google's seventh-gen TPU delivering high computing power tailored for AI models.
Google emphasizes an AI-optimized platform for real-world problem-solving.
Ironwood pods focus on efficiency for running complex AI models after training.
Google opens its global network infrastructure through Cloud WAN for enterprise customers.
Google expands the Gemini model family with Gemini 2.5 Flash, featuring 'thinking capabilities.'
Updates to generative media capabilities include models for image, video, audio, and text-to-music.
Google introduces a multi-agent ecosystem with tools like ADK and the A2A protocol for communication between AI systems.
Google enhances Workspace productivity suite with AI integration, aiding in data analysis and document creation.
The focus on interoperability and specialized agents sets Google apart in the cloud AI space.

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Sap

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How SAP and Google Cloud Are Advancing Enterprise AI Through Open Agent Collaboration, Model Choice, and Multimodal Intelligence

SAP and Google Cloud are collaborating to advance enterprise AI through the Agent2Agent (A2A) interoperability protocol, expanding Google Gemini models in SAP's generative AI hub, and leveraging Google's video and speech intelligence for multimodal retrieval-augmented generation.
The A2A protocol enables AI agents to interact, share context, and work together seamlessly across different platforms, enhancing automation and collaboration in enterprise workflows.
SAP is contributing to the A2A protocol to support cross-platform collaboration and accelerate business outcomes by enabling AI agents to coordinate actions without manual system switching.
In addition to agent interoperability, SAP is expanding access to Google models in the generative AI hub on SAP Business Technology Platform, offering customers high-performance models for AI-driven solutions within a secure environment.
SAP is unlocking multimodal understanding with Google Video Intelligence, integrating text, images, audio, and video to enhance knowledge retrieval and interaction with training and support materials.
The collaboration between SAP and Google Cloud emphasizes a vision for AI that is open, flexible, and deeply rooted in business context, aiming to help customers innovate confidently with enterprise AI solutions.
The joint efforts focus on agent collaboration, model choice, and multimodal intelligence to drive the next wave of enterprise AI, emphasizing the importance of seamless interoperability and meaningful insights from diverse data modalities.
By aligning on shared principles of openness, flexibility, and practical application of AI, SAP and Google Cloud are shaping the future of enterprise AI to deliver value and innovation to businesses.
The collaboration reflects a shared commitment to delivering enterprise-ready AI solutions that are agile, powerful, and tailored to meet the evolving needs of businesses within a secure and efficient ecosystem.
The integration of Google's AI capabilities into business contexts by SAP showcases a strategic alignment towards leveraging advanced technologies to unlock the value of unstructured content and enhance knowledge delivery in enterprises.

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Tech Radar

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AMD's Ryzen AI Max 395+ processor will power a new GMKtec mini-PC supposedly launching in May - and I'm curious to see its gaming performance

GMKtec's upcoming mini-PC, EVO-X2, is set to launch in May, powered by AMD's Ryzen AI Max 395+ processor.
The pre-order price in China suggests a $2,000 price point for US consumers, featuring 128GB RAM and 2TB storage.
The processor's Radeon 8060S iGPU offers impressive gaming performance, rivaling some desktop GPUs in intensive games like Cyberpunk 2077.
The APU boasts 16 cores, 32 threads, and a powerful 40-core Radeon 8060S GPU, hinting at a potential shift towards integrated graphics dominance.
Despite the promising performance, final details on cooling, power consumption, and dimensions are yet to be confirmed for the mini-PC system.
Ryzen AI Max+ chip systems could face inflation and tariffs challenges, impacting the final pricing and availability in the US market.
Concerns also loom over the uncertain PC gaming landscape, with implications on hardware availability and pricing due to tariffs.
Nvidia's RTX 5000 series GPUs are also grappling with issues like driver problems, limited availability, and inflation pressures.
The current GPU market struggles also affect handheld gaming PCs, potentially delaying any Ryzen AI Max+ APU integration in such devices.
AMD's response to CPU issues and innovative upgrades, alongside frustration with GPU market prices, further complicate the PC gaming landscape.

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Digitaltrends

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Microsoft could soon let Copilot see your entire screen, but that’s not a bad thing

Microsoft is testing Copilot Vision, a new feature on Copilot for PC which allows the app to see everything on your screen.
With Copilot Vision, you can share browser windows, your entire desktop, or even a game to get real-time feedback from Copilot.
The Copilot app will soon be able to help you find files on your PC using natural language queries.
Copilot Vision and enhanced file search are being rolled out to Windows Insiders in the United States.

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