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VAST Data Partners with Google Cloud to Enable Enterprise AI at Scale Across Hybrid Cloud Environments

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VAST Data, the AI Operating System company, today announced an expanded partnership with Google Cloud, the first fully managed service for the VAST AI Operating System (AI OS), enabling customers to deploy the AI OS and extend a unified global namespace across hybrid environments. Powered by the VAST DataSpace, enterprises can seamlessly connect clusters running in Google Cloud and on-premises locations, eliminating complex migrations and making data instantly available wherever AI runs.

Enterprises want to run AI where it performs best, but data rarely lives in one place and migrating can take months and costs millions. Fragmented storage and siloed data pipelines make it hard to feed the AI accelerators with consistent, high-throughput access and every environment change multiplies governance and compliance burdens.

VAST and Google Cloud address this challenge by making data placement a choice rather than a constraint. In this recorded demonstration, VAST showcased the power of the VAST DataSpace to connect clusters across more than 10,000 kilometers, linking one in the United States with another in Japan. This configuration delivered seamless, near real-time access to the same data in both locations while running inference workloads with vLLM, enabling intelligent workload placement so organizations can run AI models on TPUs in the US and GPUs in Japan without duplicating data or managing separate environments.

“Together with Google Cloud, VAST is building a unified data and computing environment that extends to wherever a customer wants to compute and unleashes the potential of AI by unlocking access to all data everywhere,” said Jeff Denworth, Co-Founder at VAST Data. “Delivered as a managed AI Operating System on Google Cloud, customers can go from zero to production in minutes – we’re turning hybrid complexity into a single, intelligent fabric that provides fast access to data, regardless of where it resides to accelerate time to value for agentic AI.”

“Bringing VAST AI Operating System to Google Cloud Marketplace will help customers quickly deploy, manage, and grow the data solution on Google Cloud’s trusted, global infrastructure,” said Nirav Mehta, Vice President, Compute Platform at Google Cloud. “VAST can now securely scale and support customers on their digital transformation journeys.”

Powering Google Cloud TPUs with seamless data access and near-local performance

Recent performance results also show how the VAST AI Operating System connects seamlessly to Google Cloud Tensor Processing Unit (TPU) virtual machines, integrating directly with Google Cloud’s platform for large-scale AI. In testing with Meta’s Llama-3.1-8B-Instruct model, the VAST AI Operating System delivered model load speeds comparable to some of the best options available in the cloud, while maintaining predictable performance during cold starts.

These results confirm that the VAST AI OS is not just a data platform but a performance engine designed to keep accelerators fully utilized and AI pipelines continuously in motion.

“The VAST AI OS is redefining what it means to move fast in AI, delivering model load speeds comparable to cloud-native alternatives while providing the full power of an advanced, enterprise-grade AI platform,” said Subramanian Kartik, Chief Scientist at VAST Data. “This is the kind of acceleration that turns idle accelerators into active intelligence, driving higher efficiency and faster time to insight for every AI workload.”

With VAST on Google Cloud, customers can benefit from:

  • Deploy AI in Minutes, Not Months: Organizations can run production AI workloads on Google Cloud today against existing on-premises datasets without migration planning, transfer delays, or extended compliance cycles. Using VAST DataSpace and intelligent streaming, they can present a consistent global namespace of data across on-prem and Google Cloud instantly.
  • Reduce Data-Movement Costs: Stream only the subsets that models require to avoid full replication and reduce egress – cutting footprint and redirecting budget from data movement to AI innovation with infrastructure that is future-ready for the demanding AI pipelines in genomics, structural biology, and financial services.
  • Maximize Google Cloud Innovation with Flexible Data Placement: Choose what to migrate, replicate, or cache to Google Cloud while keeping one namespace and consistent governance by applying unified access controls, audit, and retention policies everywhere to simplify compliance and reduce operational risk. Leverage VAST DataStore and VAST DataBase to unify prep, training, inference, and analytics without rewiring pipelines.
  • TPU-Ready Data Path: Feed TPU VMs over validated NFS paths with optimized model loading and metadata-aware I/O, delivering fast, consistent warm-start performance and predictable behavior during cold-starts.
  • Build on a Unified Platform: The VAST AI Operating System delivers a DataStore, DataBase, InsightEngine, AgentEngine and DataSpace that scales across on-premises and Google Cloud environments and adapts to changing business needs without architectural rewrites, enabling data scientists to use a variety of access protocols with a single solution.
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Intel Core Series 3 Extends AI-Ready Performance to Value and Edge Computing Segments

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Intel has introduced its latest Intel Core Series 3 mobile processors, aimed at expanding advanced computing capabilities to value buyers, commercial users, and essential edge deployments.

The launch reflects a broader shift in the industry, where performance, efficiency, and AI readiness are no longer confined to premium systems but are increasingly expected across all tiers of computing.

Built on the architectural foundations of Intel’s newer Core platforms and leveraging advanced process technology, the Core Series 3 processors are designed to deliver a balanced combination of performance, battery efficiency, and scalability. The focus is on enabling reliable, everyday computing while supporting emerging workloads, including AI-driven applications.

Driving Value-Oriented Performance

Intel positions Core Series 3 as a significant upgrade path for users operating on older systems. Compared to five-year-old PCs, the new processors deliver up to 47% improvement in single-thread performance and up to 41% gains in multi-thread workloads. GPU-based AI performance also sees notable enhancements, enabling improved responsiveness in modern applications.

This performance uplift is complemented by a strong emphasis on efficiency, with reduced processor power consumption and optimisations aimed at extending battery life for mobile systems.

AI Capability Moves to the Mainstream

One of the key differentiators of the Core Series 3 platform is the introduction of hybrid AI-ready architecture within the value segment. With support for up to 40 platform TOPS, Intel is enabling a new class of systems capable of handling AI workloads at the device level.

The platform also integrates modern connectivity standards, including Thunderbolt 4, Wi-Fi 7, and Bluetooth 6, ensuring compatibility with next-generation peripherals and networks.

Expanding into Essential Edge Deployments

Beyond traditional laptops, Intel is positioning Core Series 3 as a scalable solution for edge computing environments. The processors are designed to support a wide range of applications, including robotics, smart buildings, retail systems, and industrial deployments.

By combining AI acceleration with energy efficiency, the platform aims to deliver the performance required for real-time processing while maintaining operational reliability in diverse environments.

Ecosystem and Availability

Intel expects broad adoption across the ecosystem, with more than 70 designs from OEM partners set to launch across multiple form factors. Consumer and commercial systems powered by Core Series 3 are rolling out through 2026, while edge-focused deployments are expected from Q2 onwards.

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62% OF SAUDI LEADERS ARE FAILING TO USE THEIR DATA EFFECTIVELY, NEW CLOUDERA REPORT FINDS

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Cloudera, the only company bringing AI to data anywhere, today released its latest global survey, The Data Readiness Index: Understanding the Foundations for Successful AI, examining how prepared enterprises are to support AI at scale. Surveying more than 300 IT leaders in the EMEA region, including strong insights from Saudi Arabia, the report finds that while AI adoption is growing, most organizations still lack the data foundation needed for success.

The findings highlight a sharp contrast in how effectively organizations track their data. Nearly 9 in 10 EMEA  IT leaders claim complete visibility into where all their data resides, compared to just 32% of respondents in Saudi Arabia. Furthermore, 62% of Saudi respondents cite data access restrictions as a major roadblock to effective data use.

This gap highlights an emerging ‘AI readiness illusion’: the belief that organizations are prepared to scale AI even as critical data challenges remain unresolved.

“Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments,” said Sergio Gago, Chief Technology Officer at Cloudera. “AI is only as effective as the data that fuels it. Without seamless access to all their data, organizations limit the accuracy, trust, and business value that AI can deliver. You can’t do AI without data.”

AI Adoption is High, but ROI Remains Elusive

While AI is now deeply embedded across the enterprise, achieving consistent returns on investment remains difficult due to a sharp geographical divide in implementation hurdles. Across EMEA, the struggle is largely centered on the inputs, with data quality issues (18%) and cost overruns (16%) cited as the primary causes of lackluster ROI. However, Saudi Arabia presents a different challenge focused on execution. In the Kingdom, weak integration into workflows is the overwhelming barrier at 29%, nearly doubling the concern over data quality, which sits at 15%.

These regional nuances are further tangled by significant infrastructure limitations. Around 65% of respondents in KSA report that performance constraints have hindered operational initiatives, highlighting the immense difficulty of scaling AI across fragmented environments.

Bridging The Data Gap

At the core of these challenges is a significant disconnect between data optimism and operational reality.

The report highlights that 95% of KSA respondents are highly confident in their data, but only 32% of that data is currently fully governed. While this outpaces the broader EMEA region, where only 26% of data is governed despite 91% confidence, it highlights a critical execution gap that organizations are now racing to fill.

The Kingdom is uniquely positioned to bridge this divide with 100% of Saudi respondents ready to adopt new governance frameworks, and 79% being extremely willing to transform their operations. This regional commitment suggests that Saudi Arabia’s proactive approach will likely outpace its peers in the race toward AI and digital maturity.

Strategic Alignment and the Accountability Gap

While leadership in both the EMEA and KSA regions understands the necessity of data infrastructure, the execution and accountability frameworks are worlds apart. More than 90% of EMEA respondents report a well-defined data strategy tied directly to business objectives, while only over half  (53%) of Saudi Arabian respondents feel the same level of alignment.

Accountability and internal culture further widen this divide. In EMEA, 69% of leaders hold the CIO or CTO chiefly responsible for data readiness, whereas in Saudi Arabia, only 35% place ultimate responsibility on this role, indicating a more emerging ownership structure.

Beyond accountability and alignment, respondents in Saudi Arabia face a unique internal hurdle: 50% struggle with insufficient data literacy, while nearly a third (32%) cite a lack of executive sponsorship.

Data Readiness Will Define the Next Phase of Enterprise AI

As enterprise AI shifts from experimentation to execution, data readiness is emerging as the defining factor separating leaders from laggards.

Organizations able to fully access and govern all their data, wherever it resides, are far better equipped to deliver trusted, scalable AI. Notably, every respondent in the report indicated their organization is willing to adapt existing frameworks to support true data readiness.

As enterprises confront the limits of the AI readiness illusion, the path forward is clear: unlocking AI’s full value will require more than ambition; it will demand genuine data readiness. Those that close this gap will be best positioned to drive lasting impact and lead the next era of intelligent business.

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OPTRO LAUNCHES AI-POWERED GRC CAPABILITIES FOR THE MODERN ENTERPRISE WITH AI GOVERNANCE, CYBER RISK, AND CONTINUOUS CONTROL MONITORING

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Optro, the leading AI-powered GRC platform empowering enterprises to transform risk into opportunity, has announced several product capabilities to boost the effectiveness of customers’ risk management programs and enable them to innovate with AI confidently and responsibly. These capabilities follow shortly after the company changed its name to reflect what its AI-powered GRC platform enables: a single, coherent view across infosec, compliance, risk, and audit.

“Cyber risk now moves at machine speed, and legacy GRC tools can no longer keep up,” said Happy Wang, Chief Product and Technology Officer at Optro. “By leveraging AI to predict cyber risk, surface real-time insights, and accelerate mitigation, we help organizations shift from reactive reporting to proactive risk defense—building a true system of action that is ready for the AI era.”

Optro’s latest Risk Intelligence report found that AI governance program maturity is advancing, but unevenly. AI adoption continues to outpace AI governance, with 85 percent of organizations reporting they have integrated AI into their core operations or deployed it across multiple functions, while only a quarter report comprehensive visibility into employee AI use. At the same time, only 34 percent of organizations report their AI governance program is strategic and continuously improving. As these challenges become increasingly prevalent across industries, Optro has released the following product capabilities to help customers turn clarity into action:

  • Unified AI Governance: Serves as the essential orchestration layer for AI governance. By bridging the gap between policies & frameworks, your AI tech stack, and human oversight, this capability enables a unified, automated approach. We ensure that AI risks are visible, compliance is streamlined, and governance policies are enforceable across your entire organization.
  • Cyber Risk: Vulnerability Risk Monitoring: Provides a clear narrative of how a specific vulnerability affects an organization’s security posture and bottom line. This AI-powered functionality enables customers to understand the true business impact of a vulnerability. Included with IT and Cyber Risk Management (formerly IT Risk Management), it’s a paradigm shift in how organizations defend their digital perimeter.
  • Continuous Control Monitoring: With AI-driven recommendations for the controls best suited for automation, and a library of ready-to-use monitor templates, teams can bypass manual setup to start monitoring controls immediately. This capability helps customers reduce manual effort, improve consistency, and gain more timely visibility into control performance. By automating evidence collection and surfacing potential issues earlier, teams can address gaps more efficiently and move toward a more continuous approach to assurance.
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