NetApp buys DataPelago to boost AI data processing

itbrief.asia Jul 20, 2026

NetApp buys DataPelago to boost AI data processing

Curated by Shubham · TechCapsules · Jul 20, 2026

AI-summarised brief · reviewed before publication

NetApp has acquired DataPelago, an AI data infrastructure company, to integrate its data-processing technology into NetApp’s storage business. Based in California, DataPelago develops software that processes data at the storage layer rather than moving it to separate computing systems. NetApp states this approach can reduce infrastructure costs by up to 80% and deliver performance up to 10 times faster for AI and analytics workloads compared to conventional methods. The deal incorporates DataPelago’s Nucleus engine, which utilizes CPUs and GPUs to address the time and cost challenges of preparing data for enterprise AI projects. CEO George Kurian noted that as AI models advance, enterprises require equally intelligent data infrastructure. This acquisition aims to help customers harness their data assets more effectively by simplifying data preparation, governance, and access across hybrid cloud and on-premises environments, thereby addressing a critical bottleneck in AI deployment.

💡 Why It Matters

· The acquisition shifts the industry focus from merely acquiring powerful AI chips to optimizing the underlying data infrastructure that feeds them.
· By processing data where it resides, NetApp directly tackles the hidden costs and latency that often stall enterprise AI initiatives.

AI Capsules Cloud Computing

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Robotics Company Agility Opens 60,000 Square-Foot Facility Silicon Valley Daily

Agility Robotics has inaugurated a 60,000‑square‑foot Fremont, California facility to serve as its Silicon Valley hub for Physical AI development. The new center will house engineering teams that train, test, and enhance the AI systems powering the company’s humanoid robot, Digit, enabling it to acquire new skills and perform more complex tasks in customer settings. The site complements Agility’s existing RoboFab plant in Salem, Oregon, and will employ nearly 200 professionals in AI/ML software engineering and field operations. The expansion supports the company’s goal of scaling Digit deployments and preparing for a public listing through a merger with Churchill Capital Corp XI.

💡 By positioning its AI development hub in Silicon Valley, Agility taps a premier talent pool, accelerating innovation that could set new standards for safety and productivity in enterprise robotics.

aljazeera.com · Jul 21

Can AI systems make moral decisions in war?

Artificial intelligence is increasingly shaping modern warfare, with autonomous drones and AI‑driven command systems now deployed in Ukraine, Gaza, and the US‑Israel conflict against Iran. Palantir’s Maven Smart System identified and struck over 1,000 targets on the first day of the US‑Israel war on Iran, including an Iranian primary school that killed more than 150 people, mostly children. The Pentagon’s investigation into the strike remains stalled, with senators demanding answers and Bloomberg reporting the error stemmed from outdated satellite data. As military budgets grow, the U.S. pushes toward an “AI‑first” fighting force, compressing the OODA loop to accelerate decision‑making.

💡 The use of AI in targeting raises urgent questions about accountability and the moral weight of automated decisions in conflict zones.

firstpost.com · Jul 21

Kevin O’Leary dismisses AI data centre water concerns, says modern facilities are…

Kevin O’Leary, the Canadian entrepreneur known from “Shark Tank,” told Glenn Beck’s radio show that modern AI data centres no longer consume excessive water. He said newer cooling technologies have reduced usage to levels comparable with a golf course, countering criticism that AI infrastructure strains water supplies in drought‑prone regions. O’Leary cited his own projects in Utah and Canada, noting the Utah phase will deliver 1.4 gigawatts of computing power while using water similar to a golf course. He argued that concerns stem from older facilities built more than a decade ago and do not reflect current designs. The comments arrive as AI firms pour billions into new hardware amid mounting scrutiny of power‑hungry data centres and regulatory pressure intensifies worldwide.

💡 By reframing water use, O’Leary aims to defuse a key environmental hurdle that could stall AI expansion in water‑scarce jurisdictions.

openpr.com · Jul 21

CrunchJ Launches Marketing Reporting Platform with AI Visibility and Conversion Attribution

CrunchJunkie, a Hamburg‑based SaaS firm, unveiled a new marketing reporting platform that merges automated performance dashboards with AI‑visibility tracking. The tool aggregates data from Google Ads, Meta, GA4, Microsoft Ads and other sources into an interface, generates AI‑written executive summaries in a brand’s tone, and schedules white‑label PDF reports, reducing report creation from a full day to roughly ten minutes. It also monitors how eight major AI assistants—including ChatGPT, Gemini, Claude and Perplexity—describe a brand, measuring visibility, sentiment, share of voice and cited sources. By linking this AI visibility to Google Analytics traffic and conversions, the platform quantifies the impact of AI mentions. Plans start at €12 per month and include a GEO audit and a Signals inbox for alerts.

💡 Marketers can finally prove that AI‑driven brand mentions translate into sales, turning speculative visibility into a measurable ROI driver.

nextplatform.com · Jul 21

GenAI Hardware Investments Are Way Ahead Of Model And Platform Revenues

Recent analysis shows that investment in generative AI (GenAI) hardware far outpaces revenue from AI models and platforms. Gartner’s data estimates model spending at $1.4 billion in 2023, rising to $5.7 billion in 2024, but growth slows sharply thereafter, with projected 2026 revenues of $28.3 billion—well below the annualized revenue run rates reported by OpenAI and Anthropic. The disparity highlights a widening gap between capital‑intensive infrastructure spending and the cash flow generated by AI services. Open‑weight models from Chinese firms such as Alibaba Qwen and DeepSeek are gaining traction, potentially diverting customers from higher‑priced closed‑weight offerings. Meanwhile, U.S. and European firms face mounting hardware costs that may outstrip the earnings from their proprietary models, raising concerns about the sustainability of current investment levels.

💡 The hardware‑revenue mismatch threatens to strain cash‑flow for leading AI developers, forcing them to reassess growth strategies amid rising competition from cheaper open‑weight alternatives.

therobotreport.com · Jul 21

Generative Bionics unveils humanoid robot with full-body tactile sensing

Generative Bionics introduced its Gene.01 humanoid at AMD Advancing AI 2026, marking the robot’s U.S. debut. Developed in six months, the platform integrates full‑body tactile skin that senses touch, temperature, proximity and force with a physics‑native AI that treats the robot’s body, mechanics and intelligence as a single system. CEO Daniele Pucci described Gene.01 as a scalable, human‑aware platform that can be customized at the AI, design and end‑effector levels for specific industrial tasks. The first commercial configuration partners with shipbuilder Fincantieri to perform welding in shipyards. Gene.01’s model and digital twin are open‑sourced on PyPI, conda‑forge and ROS, enabling developers to integrate the robot instantly into existing AI and simulation pipelines. Its rapid build underscores fast tactile‑robotic progress today.

💡 By open‑sourcing a touch‑sensitive humanoid, Generative Bionics lowers the barrier for factories to deploy collaborative robots that can learn tasks through force feedback, accelerating adoption of safe human‑robot teamwork.