Sign in

Author: DEROBS

  • Google secures 1GW virtual power plant agreement with Voltus

    Google secures 1GW virtual power plant agreement with Voltus

    Google has signed a major agreement to establish a 1GW virtual power plant (VPP) with energy software provider Voltus. The deal marks the largest commitment to a virtual power plant initiative by a hyperscale cloud provider to date.

    Virtual power plants aggregate distributed energy resources—such as battery storage, solar installations, and demand-response capabilities—to act as a unified utility-scale power resource. By managing these distributed assets, companies can provide grid stability and support energy demand management.

    While the agreement represents a significant scale of energy management for a data center operator, further technical specifications regarding the deployment timeline or specific geographic focus of the 1GW capacity were not detailed in the initial announcement.

    Source: Data Center Dynamics
    Original article: https://www.datacenterdynamics.com/en/news/google-signs-1gw-virtual-power-plant-deal-with-voltus/

  • Microsoft outlines process to re-enable Exchange Online EWS apps

    Microsoft outlines process to re-enable Exchange Online EWS apps

    Microsoft has provided guidance for IT administrators experiencing disruptions with Exchange Web Services (EWS) applications in Exchange Online. Following the retirement of the EWS API, some organizations may find that their existing applications have stopped functioning as expected.

    According to the company, administrators have the option to re-enable the retired EWS API within their Exchange Online environment to restore connectivity for these applications. This measure is intended to assist organizations that rely on EWS-based integrations and encountered service interruptions during the transition period.

    Source: BleepingComputer
    Original article: https://www.bleepingcomputer.com/news/microsoft/microsoft-shares-how-to-fix-broken-exchange-online-ews-apps/

  • Arbol introduces insurance for data center construction moratoriums

    Arbol introduces insurance for data center construction moratoriums

    Arbol has launched a new insurance coverage product specifically designed to address the risks associated with the suspension of data center construction projects. This offering is the first of its kind, aiming to protect stakeholders against financial losses resulting from government-mandated construction moratoriums.

    As demand for data center capacity grows globally, infrastructure projects often face complex regulatory environments. The introduction of this insurance product addresses a specific risk for developers and investors whose projects may be delayed or halted due to sudden policy shifts or temporary bans on data center development in specific jurisdictions.

    By providing a mechanism to mitigate the financial impact of such government-led suspensions, the coverage seeks to offer greater predictability for long-term digital infrastructure investments.

    Source: Data Center Dynamics
    Original article: https://www.datacenterdynamics.com/en/news/arbol-launches-moratorium-risk-insurance-coverage/

  • Uber expands ChatGPT Work access to entire workforce

    Uber expands ChatGPT Work access to entire workforce

    Uber has officially expanded its deployment of ChatGPT Work, granting access to its entire global workforce of 30,000 employees. This company-wide rollout follows a more limited pilot phase, during which the organization tested the enterprise-focused AI agent.

    By integrating the platform across its staff, Uber joins a growing number of large enterprises moving toward broader adoption of generative AI tools for internal business operations. The transition from a small-scale pilot to a full-scale enterprise deployment signifies the ride-share company’s commitment to scaling the use of AI agents within its corporate infrastructure.

    Source: TechCrunch
    Original article: https://techcrunch.com/2026/10/22/uber-puts-all-30000-employees-on-chatgpt-work/

  • NVIDIA expands DGX Spark capabilities for multi-node AI development

    NVIDIA expands DGX Spark capabilities for multi-node AI development

    NVIDIA has announced an expansion of its DGX Spark platform, designed to accommodate the growing complexity of modern artificial intelligence development. Originally introduced to bring high-performance AI development capabilities directly to the desktop, the platform is now being updated to support the interconnection of multiple Spark nodes.

    The shift toward multi-node configurations addresses the evolving needs of developers who are increasingly tasked with orchestrating multiple AI models simultaneously. As these workflows involve chaining inference calls and experimenting with complex, frontier-class architectures, the hardware requirements have surged, often demanding hundreds of gigabytes of memory to process effectively.

    By enabling the linkage of up to eight NVIDIA DGX Spark nodes, the company aims to provide a more robust infrastructure for developers handling large-scale, memory-intensive AI tasks. This development was detailed by the company in anticipation of GTC Berlin, signaling a move to support more sophisticated parallelized AI workloads within localized development environments.

    Source: NVIDIA
    Original article: https://developer.nvidia.com/blog/running-frontier-class-ai-models-across-8-nvidia-dgx-spark-nodes/

  • Vector Core Compute enters partnership with SambaNova for edge AI infrastructure

    Vector Core Compute enters partnership with SambaNova for edge AI infrastructure

    Vector Core Compute has initiated a collaboration with SambaNova, marking a strategic effort to enhance computing infrastructure specifically tailored for the agentic edge. The move aims to integrate SambaNova’s specialized AI hardware technologies into Vector Core Compute’s edge-focused solutions.

    As the demand for decentralized processing grows, companies are increasingly looking to deploy sophisticated artificial intelligence models closer to the source of data. By leveraging SambaNova’s technology, Vector Core Compute seeks to improve the performance and efficiency of AI agents operating in edge environments, where latency and power constraints are critical considerations.

    Further technical details regarding the implementation of these technologies or specific timelines for product deployments have not yet been disclosed.

    Source: Data Center Dynamics
    Original article: https://www.datacenterdynamics.com/en/analysis/a-new-neocloud-for-the-agentic-edge/

  • Hugging Face releases OlmoEarth v1.3 for geospatial embedding tasks

    Hugging Face releases OlmoEarth v1.3 for geospatial embedding tasks

    Hugging Face has announced the release of OlmoEarth v1.3, a model designed to provide state-of-the-art embeddings specifically for geospatial applications. Developed in collaboration with the Allen Institute for AI (AI2), the release aims to improve how machines process and represent data related to the Earth’s surface and planetary-scale information.

    Embeddings are a fundamental component in modern machine learning, allowing complex data—such as satellite imagery or environmental datasets—to be represented as numerical vectors that models can interpret for analysis and pattern recognition. By offering specialized embeddings for geospatial data, OlmoEarth v1.3 is intended to assist researchers and developers in tasks that require high-precision analysis of terrestrial information.

    The release is part of an ongoing effort to provide open-access tools for the artificial intelligence community, focusing on specialized domains where standard, general-purpose models may require additional tuning or specific architectures to achieve optimal performance. As with previous releases under the Olmo project, this version emphasizes openness and utility for downstream applications in climate monitoring, environmental science, and geographical data processing.

    Further technical details, including integration documentation and performance benchmarks for the v1.3 iteration, are available through the official Hugging Face repository.

    Source: Hugging Face
    Original article: https://huggingface.co/blog/allenai/olmoearth-v1-3

  • HPE expands private cloud AI portfolio with support for mixed Nvidia hardware and new CPU rack

    HPE expands private cloud AI portfolio with support for mixed Nvidia hardware and new CPU rack

    Hewlett Packard Enterprise (HPE) has announced updates to its Private Cloud AI solution, aimed at providing greater flexibility for enterprise deployments. The company is expanding the platform to support mixed Nvidia hardware clusters, allowing organizations to integrate diverse hardware configurations within their AI environments.

    In addition to the expanded hardware compatibility, HPE has launched the Vera CPU rack. This new addition is designed to further support the infrastructure requirements of modern AI workloads, specifically addressing the scaling needs of agentic AI applications.

    These developments reflect an effort to optimize private cloud infrastructure for the varying demands of AI model training and deployment. By enabling mixed-cluster support, HPE aims to provide a more adaptable architecture for companies managing complex, high-performance computing requirements.

    Source: Data Center Dynamics
    Original article: https://www.datacenterdynamics.com/en/news/hpe-expands-private-cloud-ai-solution-to-support-mixed-nvidia-hardware-clusters-launches-vera-cpu-rack/

  • IBM infrastructure revenue rebounds following second quarter decline

    IBM infrastructure revenue rebounds following second quarter decline

    IBM has seen its infrastructure revenue return to growth following a reported decline during the second quarter. The rebound marks a shift in the segment’s performance as the company navigates ongoing demand in the technology sector.

    Reflecting on the factors driving this recovery, IBM CEO Arvind Krishna highlighted the influence of sovereign AI—the trend of nations and organizations seeking to build and control their own artificial intelligence capabilities—as a significant “tailwind” for the company’s infrastructure business.

    The company continues to emphasize its focus on aligning its infrastructure offerings with the specific needs of clients investing in local AI deployment and data sovereignty.

    Source: Data Center Dynamics
    Original article: https://www.datacenterdynamics.com/en/news/ibm-infrastructure-revenue-bounces-back-after-q2-drop/

  • Rescale implements AI-driven triage to automate engineering test failures

    Rescale implements AI-driven triage to automate engineering test failures

    Rescale, a digital engineering platform provider, has announced the successful deployment of an automated AI triage agent designed to manage its internal software testing cycles. The system, built using the AI-Driven Development Lifecycle (AI-DLC) framework on AWS, identifies and routes failures in nightly end-to-end test suites, significantly reducing the manual operational burden on engineering teams.

    Automating complex engineering workflows

    Prior to the implementation, Rescale’s engineering teams faced repetitive, manual tasks to classify test failures before deployment. The new agent, integrated into the company’s existing Argo Workflows CI/CD pipeline on Amazon Elastic Kubernetes Service (Amazon EKS), automates this process by querying logs and historical data. When a failure occurs, the agent utilizes Claude Opus 4.8 via Amazon Bedrock to categorize the issue—whether it is a code bug, infrastructure failure, environment error, or a flaky test—and generates a structured remediation report.

    Building with the AI-DLC framework

    The development of the triage agent was conducted over a five-day workshop utilizing the AI-DLC methodology. This approach emphasizes collaborative “mob sessions” where humans define requirements, validate architectural decisions, and oversee AI-generated code. By adopting this structure, Rescale moved from initial problem definition to a staging deployment in five days, with a production release achieved within several weeks.

    Key technical components of the solution include the use of the Strands SDK for agent orchestration, Amazon CloudWatch for log retrieval through the Model Context Protocol (MCP), and a dedicated knowledge base for tracking historical failure patterns.

    Operational impact and adoption

    Since its deployment, the triage agent has demonstrated a steady improvement in accuracy, with the classification agreement between the AI and human triage rising to 68%. The company reports a 20% reduction in time blocking production deployments related to test failure analysis, allowing engineers to dedicate more time to architectural tasks and product development.

    Following the success of the triage project, Rescale is now extending the use of AI-DLC across other engineering initiatives, including its simulation-domain product development. The company is also evaluating the creation of an internal AI-DLC Center of Excellence to standardize these practices across its broader organization, marking a shift toward an AI-first approach to complex software engineering.

    Source: aws.amazon.com
    Original article: https://aws.amazon.com/blogs/machine-learning/how-rescale-built-an-ai-triage-agent-with-strands-agents-and-ai-dlc/