Empowering Innovation
with Solidigm

In today’s rapidly advancing tech landscape, optimizing infrastructure to handle massive data sets has become more crucial than ever. One noteworthy story emerging from NVIDIA GTC is how Intercontinental Exchange (ICE) is tackling the growing complexity of data management, AI implementation and storage optimization across its vast network of financial exchanges, data services and mortgage technologies. We sat down with Anand Pradhan, the head of the AI Center of Excellence at ICE, and Roger Corell, senior director of leadership marketing at Solidigm, to discuss how ICE is using technology to stay ahead of the curve.  

ICE, known for operating the New York Stock Exchange, processes over 700 billion transactions daily. With such massive volumes of data, building and maintaining an optimized, highly redundant infrastructure is essential. It’s not just about the network and servers — the flow of data through these systems makes storage a critical focus in ICE’s technology strategy.

Anand explained that ICE handles around 10 to 12 terabytes of data every single day with nanosecond granularity. This data, crucial for tracking financial trades, must be stored and accessed at lightning speeds. With millions of trades, real-time analysis and preventing fraud are key, which means both data retrieval and storage processes must be supercharged for efficiency.

One of the biggest challenges is the sheer volume of data and the input-output bottlenecks that arise when reading and writing to storage systems. To solve this, Anand’s team works closely with the InfraSolutions architecture team to fine-tune the storage infrastructure, ensuring that it scales easily, remains flexible and is resilient to failure. This involves rigorous testing and investment in systems that allow for fast, uninterrupted data access, while minimizing latency and maximizing performance.

But Anand’s insights extend beyond just infrastructure; he also highlighted how AI is shaping the company’s approach to data aggregation. At ICE, AI models are primarily used for processing unstructured data, such as images of real estate properties. The AI extracts valuable insights from these photos, identifying key artifacts, such as doors, kitchens or even the color of a room. With real estate photos pouring in from across the U.S., this AI-driven data processing is a massive undertaking. AI models are deployed at scale to make sense of the raw data, which is then converted into structured, usable information for the company’s real estate services.

As ICE’s AI adoption grows, so too does its need for an optimized storage solution. The storage systems of the future, Anand noted, need to accommodate millions of files — whether flat files, images or video data — and ensure they can be accessed quickly. As more and more workloads move to the AI space, fast access to large datasets and the ability to scale storage seamlessly are becoming essential. This is where storage systems that can horizontally scale, offer fast write speeds and support massive volumes of data will stand out.

Looking ahead, ICE’s evolving use of AI and machine learning is transforming its infrastructure and redefining what modern storage systems must deliver. What’s the TechArena take? With growing demands for speed, scale and real-time access, ICE’s journey offers a clear example of how AI is driving a fundamental shift across the industry. As adoption accelerates, organizations at the forefront of tech will need to rethink their approach to storage — those that do will be best positioned to gain a lasting competitive edge.  

To learn more about ICE, visit www.ice.com, or find Anand and ICE on LinkedIn.

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At GTC, all things AI took center stage, and one thing that grabbed attendees’ attention was Dell’s latest innovation for AI computing, Project Lightning. We sat down with Scott Shadley, director of leadership narrative and evangelist at Solidigm, and Rob Hunsaker, director of engineering technologies at Dell, for a conversation that offered valuable insights into how Dell’s storage solutions are evolving to meet the growing demands of the AI market.

For those following AI developments, it’s clear that the performance demands of AI workloads are shifting. Traditional file systems are no longer sufficient to handle the immense data volumes and speed requirements of modern AI applications. Enter Project Lightning, Dell’s next-generation parallel file system, designed from the ground up to be the fastest solution in its market segment.

What sets Project Lightning apart is its ability to address extreme performance needs in AI environments. As Rob explained, the project was announced last year at Dell Tech World and is specifically optimized for AI use cases. This new file system offers unmatched speed and efficiency, which is essential as AI workloads continue to grow in complexity and scale. By leveraging Dell’s own intellectual property, Project Lightning represents a significant leap forward in storage technology, making it a game-changer for industries relying on AI.

This new addition to the PowerScale family of storage solutions isn’t just about speed. It’s about ensuring that storage solutions can scale with the growing demands of AI. Dell’s approach is rooted in the idea that data is the most critical asset in any enterprise, and having the right tools to manage and store that data is key to enabling AI’s potential. As Rob highlighted, Dell is working to ensure that all of its storage products are prepared for the future, with a strong focus on making data easily accessible and manageable.

One of the highlights of the conversation was Dell’s broader vision for data storage. Rather than simply providing individual storage products, Dell’s focus is on offering complete solutions that address the full spectrum of customer needs. The Dell Data Lakehouse, for example, is a powerful tool designed to unify storage, PowerEdge and software features into a comprehensive solution. This platform is designed to support AI applications by providing a reliable and scalable data management system that can handle the vast amounts of unstructured data AI processes require.

Throughout the discussion, it became clear that Dell’s role in the AI ecosystem goes beyond just providing storage solutions — it’s about creating a seamless environment where data can be used effectively to drive innovation. As Rob pointed out, the enterprise sector is just beginning to fully embrace AI, and Dell is committed to helping them navigate that transition. By ensuring that storage products can meet the needs of AI applications, Dell is positioning itself as an essential player in the future of enterprise AI.

In an industry where storage often takes a backseat to more glamorous technologies like GPUs and inference engines, it was refreshing to hear a conversation that highlighted the importance of reliable, high-performance storage. After all, as Rob noted, if the storage fails, the data is lost, and with it, the entire AI workload.

The partnership between Dell and Solidigm, known for their high-capacity quad-level cell (QLC) drives, further demonstrates the importance of resilient, high-performance storage. The TechArena take? By working together, Dell and Solidigm are able to provide a robust storage infrastructure capable of supporting the intense demands of AI environments, ensuring that customers’ data is safe and accessible.

To learn more about Dell’s cutting-edge storage solutions and their ongoing advancements in AI, visit the Dell InfoHub (infohub.delltechnologies.com) or check out their Unstructured Data Quick Tips blog for the latest updates.

At this year’s CloudFest, we caught up with Chris Ward, senior sales account manager at Solidigm, and Guillaume Gojard, product director at OVHcloud, to dive deeper into OVHcloud’s unique infrastructure strategy, its evolving role in AI and its long-standing commitment to sustainable innovation. Amid the cloud announcements and industry buzz, OVHcloud stood out for how it’s quietly reshaping the cloud landscape — one custom-built server and water-cooled data center at a time.

At a time when cloud providers are often defined by how they manage their hyperscale partnerships, OVHcloud stands apart by owning its full value chain. The company builds its own servers at facilities in both Europe and North America, operates more than 40 data centers worldwide and manages its own global fiber network. This level of integration isn’t just about control — it enables OVHcloud to deliver a price-performance ratio that resonates, particularly in today’s AI-hungry world.

And AI is everywhere. “It’s in every mouth,” Guillaume said, capturing the sentiment that defined the expo floor this year. For OVHcloud, this isn’t about scrambling to catch up. It’s about expanding what they started years ago. The company has been offering GPU-based compute since 2017, and it recently began rolling out ready-to-use large language models (LLMs) and AI endpoints — giving developers a practical starting point to integrate generative models into their stack. OVHcloud is pairing its AI push with an upcoming data platform designed to streamline how customers manage and leverage data inside complex workflows.

But the conversation didn’t stop at AI. Another topic discussed was OVHcloud’s long-standing use of water cooling, which is now getting mainstream attention. “And for example, water cooling with one glass of water, we can cool down one server for 10 hours of use,” Guillaume explained, noting that the company’s approach uses seven times less water than the industry average. That’s not a gimmick — it’s industrial innovation rooted in sustainability. It’s also a reminder that OVHcloud isn’t jumping on trends — they’re often ahead of them.

A large part of that innovation comes through partnerships. In this case, OVHcloud’s collaboration with Solidigm has allowed the company to push high-performance storage capabilities in its high-grade servers. “Blazing fast data access on our NVMe storage capacity, which is really great, because this is what the market demands,” Guillaume explained. For demanding use cases like real-time analytics, that speed translates directly into customer value. More importantly, the partnership gives OVHcloud the flexibility to respond to shifting demands — something Guillaume said has been smooth and responsive from day one.

Looking ahead, OVHcloud’s eye is on quantum computing. OVHcloud is supporting startups and even has a quantum computer. The company is also quietly building a quantum-friendly cloud platform, positioning itself to support ecosystems that will, like AI, demand entirely new infrastructure paradigms.

The TechArena take? In an industry full of noise, OVHcloud’s approach is refreshingly holistic. From LLM toolkits to next-gen cooling to the quantum horizon, it’s not just about where things are now — it’s about where they’re headed.

At CloudFest 2025, Khilna Chandaria, operations manager at Solidigm, caught up with Charlie Hacker, sales and marketing director at M2M Direct, and TechArena to chat about the latest trends in cloud computing and the innovations that are reshaping the industry. The conversation highlighted the growing importance of AI, the rising demand for high-capacity storage and the key attributes businesses are seeking in their cloud solutions. As cloud computing continues to evolve, M2M’s consultative distribution approach is helping organizations adapt to these changes, particularly through their collaboration with Solidigm.  

The shift toward AI-driven cloud computing was one of the key topics of discussion.  

“Cloud computing is shifting to an AI-based model, both for private and public clouds,” Charlie shared. This shift is reshaping how cloud environments are used, enabling businesses to handle larger amounts of data with greater efficiency and scalability.

As cloud adoption accelerates, businesses are looking for solutions that offer flexibility, scalability and competitive pricing. “Flexibility and price, price or flexibility, either or,” Charlie explained, emphasizing the trade-offs many organizations are grappling with when choosing their cloud partners. But these aren’t the only important factors. Scalability is also essential, as businesses must be able to expand their storage and processing capabilities as their needs grow.  

Security is another major consideration in today’s cloud landscape. With more data being transferred across private and public clouds, keeping that data secure is a top priority. As businesses increasingly rely on cloud solutions to store and process sensitive information, they must prioritize robust security measures that can protect against cyber threats, ensuring both compliance and the integrity of their data.

One of the most pressing needs in cloud computing today is high-capacity data storage. As AI and other data-intensive technologies continue to advance, the demand for larger, faster storage solutions is growing at a rapid pace. “Size, size, size, size,” Charlie remarked, stressing how critical storage capacity has become in the face of AI’s massive data requirements. Solidigm’s quad-level cell (QLC) products, offering up to 122 terabytes of capacity, are meeting this demand head-on. With such large-scale storage solutions, businesses can manage and process enormous datasets efficiently, without sacrificing speed or performance.

M2M’s role in this evolving landscape is to provide not just products, but consultative services that help businesses navigate the complexities of cloud migrations and data center upgrades. “We’re like a sales arm for Solidigm, and Solidigm is a sales arm for us,” Charlie explained.  

What’s the TechArena take? Collaborations like this one between M2M and Solidigm ensure that cloud infrastructure providers can deliver the right products at the right time, supplying on-demand solutions that are essential for businesses undergoing significant infrastructure changes.

For those interested in staying updated on the latest advancements in cloud computing and AI, Charlie encouraged viewers to follow M2M on LinkedIn and visit their website (m2m-enterprise.com) for the latest product offerings and updates.

At TechArena, we’ve been closely following the transformative potential of AI in various industries, and after recently sitting down for a conversation with Solidigm’s Jeniece Wnorowski and Oracle’s Andrew De La Torre, one thing is clear: AI is revolutionizing how the telecommunications industry operates. From network management to customer service, AI is enabling telcos to optimize their operations and pave the way for the future of digital connectivity.

During our chat, Andrew explained how Oracle is at the forefront of AI-driven network automation, particularly in integrating AI with telecom infrastructure. As 5G networks continue to expand and evolve, the need for more efficient, scalable and autonomous systems becomes even more apparent.

The Shift Toward Autonomous Networks

Telcos are undergoing a massive migration from traditional telecom networks to autonomous ones, utilizing the migration to 5G to fuel new capabilities that speed and simplify network management. Andrew described how the integration of AI ops is essential to unlocking the full potential of these self-healing, self-optimizing networks. While it may sound like something from a sci-fi novel, the idea of a network that can monitor, troubleshoot and repair itself with minimal human intervention is becoming a reality.

This vision of an autonomous network is not just about improving efficiency; it’s about enabling telecom companies to deliver services more nimbly and improve service reliability at a fraction of the cost. Oracle’s focus on integrating AI capabilities into every layer of the telco stack — from cloud native infrastructure to front office applications — demonstrates the company’s commitment to transforming the industry.

AI Ops: A New Framework for Telecom Transformation

So, what is AI Ops? At its root, it is a framework designed to automate telecom network functions, which is essential for handling the complexity of 5G networks while minimizing manual intervention. Andrew explained that the key to building autonomous networks is the integration of cloud-native applications, data aggregation and AI analytics. By combining these elements, Oracle helps telecom providers to make data-driven decisions that improve performance and reduce operational costs.

For example, Oracle’s AI models can analyze vast amounts of network data to identify issues before they become critical. This predictive capability allows for proactive troubleshooting and service optimization, which ultimately leads to improved service uptime. With the rise of 5G, increased use of edge computing, growth in IoT and the resultant increased demand for data, this type of automation is becoming less of a luxury, and more of a necessity.

Generative AI vs. Traditional Machine Learning: What’s in Play for Telco?

One of the most insightful moments of the conversation came when Andrew addressed the role of different types of AI technologies in telco. While generative AI is making headlines, he emphasized that AI in telco is a diverse toolkit, with applications ranging from robotic process automation to advanced machine learning techniques.  

Andrew pointed out that the telco industry is unique in its complexity, which is why specialized AI models tailored to telco use cases are so essential. AI’s ability to handle large-scale, repetitive tasks — such as network monitoring and optimization — while also supporting more advanced functions, such as natural language processing, is key to driving digital transformation.

The Human Element in AI-Driven Network Automation

Of course, the integration of AI into telco networks doesn’t come without its challenges. Andrew noted that the industry’s slow adoption of automation is partly due to deeply ingrained legacy infrastructure and attitudes. Networks are essential to national economies, and the cautious pace of change is understandable. However, Oracle is actively helping operators to navigate this transition.

Through tools such as automated test repositories and software solutions, Oracle is enabling telco providers to adopt a cloud-native mindset and deploy DevOps-style operations. The human element remains essential in this journey — operators need the right training and support to manage these new AI-driven systems effectively.

The Road Ahead: A More Connected, Autonomous World

In the grand scheme of things, AI-driven network automation is setting the stage for a future where telcos can deliver faster, more reliable and more cost-effective services. By embracing AI ops, Oracle is helping its clients build the autonomous networks of tomorrow — networks that promise to be smarter, faster and more responsive to the needs of both consumers and businesses.

At TechArena, we’re always on the lookout for stories that highlight innovation and transformation in the tech industry. We’re hot on the trail of AI Ops and its control of the IT infrastructure that will...accelerate broader application of AI. The insights shared by Andrew on Oracle's innovation demonstrate that AI Ops has survived the trough of disillusionment and is moving forward into real world deployment. The capabilities at stake will deliver a nimble edge, and provide telcos their potential edge for long term financial prosperity. We’re delighted to see it as fast and ubiquitous networks are a core of broad technology innovation.

Check out the full podcast.

To learn more about Oracle, visit their website at oracle.com.

From breakthrough 122TB SSDs to the industry’s first liquid-cooled storage, Solidigm’s Avi Shetty unpacks how storage is powering AI workloads from hyperscale to neo-cloud.

NVIDIA’s GTC is always a hotspot for innovation. This year, two industry leaders, Supermicro and Solidigm, brought their cutting-edge solutions designed for the next wave of AI workloads for CSP and Hyperscalers. From high-density storage to powerful cooling solutions, their collaboration is shaping the future of data centers. Wendell Wenjen, director of storage market development at Supermicro, and Shirish Bhargava, of Solidigm’s global field sales, sat down with TechArena to discuss how their partnership is addressing the growing demands of AI and what lies ahead for next-generation data center infrastructure.

Supermicro, known for pushing the envelope in server technology, showcased their latest systems directed at powering AI applications. Central to their presentation was the NVIDIA HGX B300 NVL16, featuring the powerful NVIDIA Blackwell UltraGPUs— Supermicro’s most advanced GPU solutions to date. These high-performance servers were designed with AI in mind, supporting the growing demand for deep learning and large-scale data processing. Supermicro also introduced a range of storage solutions optimized for AI workloads.

Another exciting announcement was the launch of a new 1U Petascale storage system, equipped with the NVIDIA Grace CPU. This dual-die, high-performance processor delivers impressive power efficiency, ideal for the ever-growing demands of AI. For those seeking even more storage efficiency, Supermicro unveiled a JBOF system powered by NVIDIA’s BlueField-3 DPU, which supports demanding storage workloads with lower power usage.  

However, it wasn’t just Supermicro’s hardware that drew attention at GTC. Solidigm, a leader in enterprise solid-state drive (SSD) solutions, brought its own innovative technology to the table. The Solidigm D5 P5336 SSD, a 122 TB powerhouse, was also on display, offering extreme storage density that is essential for AI training and large-scale data management in all form factors. This SSD is part of Solidigm’s broader portfolio designed for AI, providing the kind of performance and capacity needed to handle massive datasets with low latency.

But what makes this collaboration truly stand out is the shared commitment to pushing the boundaries of storage capacity and efficiency. Supermicro and Solidigm’s joint focus on reducing data center footprint while maximizing storage capacity is a game-changer. By using Solidigm’s 122 TB quad-level cell (QLC) SSDs, Supermicro is able to pack three petabytes of storage into a 2U server, a dramatic leap from the previous one-petabyte systems. This compact, high-capacity solution not only optimizes data center space, but also reduces power consumption, making it a win-win for enterprises and service providers alike.

In an industry where cooling and power efficiency are critical, Supermicro’s approach to liquid cooling for high-performance GPUs stood out. Some of today’s most powerful GPUs can consume over 1,000 watts, making liquid cooling a necessity for keeping systems running at optimal temperatures. Supermicro’s comprehensive liquid cooling solution — ranging from cold plates for CPUs and GPUs to large outdoor cooling towers — ensures that even the most demanding AI systems stay cool, efficient and reliable.

So, what’s the TechArena take? This partnership between Supermicro and Solidigm is a testament to the importance of collaboration in driving innovation. Both companies have long been at the forefront of their respective fields, and their combined efforts are delivering practical, high-performance solutions to address the challenges of modern AI workloads.

For those looking to learn more, Supermicro offers an abundance of resources on their website (supermicro.com) and social media channels (X, LinkedIn and YouTube).

From 122TB QLC SSDs to rack-scale liquid cooling, Solidigm and Supermicro are redefining high-density, power-efficient AI infrastructure—scaling storage to 3PB in just 2U of rack space.

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At CloudFest 2025, OVHcloud shared insights on AI’s expanding role in cloud infrastructure, the benefits of custom-built servers, and how their global network is optimizing performance and efficiency.

In today’s rapidly evolving IT landscape, flexibility and adaptability are key to meeting the demands of businesses seeking innovative, scalable solutions. This shift in customer needs came into sharp focus at CloudFest 2025, where we sat down with Steve Gutierrez, director of sales at Solidigm, and Arun Garg, founder and CEO of Taurus Group. With a focus on open platforms and best-of-breed components, Taurus is providing businesses with the freedom to build the infrastructures they need, without being tied to a single-vendor, one-size-fits-all solution.

Taurus Group’s approach is centered around offering a diverse array of options to its partners, tapping into open compute platforms and leveraging the expertise of its sister company, Circle B, a specialized provider for the Open Compute Project Foundation (OCP). Alongside this, Taurus works closely with Cluster Vision to deliver high-performance computing solutions and open-source cluster management tools. These collaborations give Taurus the tools to provide cutting-edge, flexible infrastructure options while remaining agile enough to adapt to the unique demands of their clients.

Arun highlighted how important it is for businesses today to have the freedom to choose the best components for their needs, rather than relying on a single vendor’s ecosystem. The days of restrictive, monolithic IT systems with one-size-fits-all solutions are long gone — today’s customers are looking for more flexibility and the ability to customize their infrastructure.

Solidigm’s products, such as the recently launched 122TB storage solution, perfectly complement Taurus Group’s portfolio, offering innovative, reliable options for clients in need of scalable storage. According to Arun, customers appreciate the collaboration with Solidigm because it ensures that they can deliver the best possible solutions with the added benefit of excellent support from Solidigm’s technical and support teams.

What’s the TechArena take? The collaboration between Taurus Group and Solidigm is a great example of how true partnerships can help businesses deliver more powerful solutions to their customers. It’s clear that as companies like Taurus continue to push for openness and flexibility in the IT space, they’re creating a future where businesses are no longer constrained by traditional, single-vendor systems, but instead have access to a wide range of tools and solutions that are tailored to their needs.

For anyone looking to explore more about Taurus Group and how they can leverage the latest storage solutions, reach out directly through their website, tauruseu.com. With a clear focus on building strong, flexible partnerships, Taurus Group is poised to continue playing a key role in the future of IT infrastructure.

In a landscape often dominated by hyperscalers and familiar names, Scaleway is quietly rewriting the rules. With a clear vision and a sharp focus on what modern cloud scalers actually need, it’s stepping into a role that feels both timely and transformative. In a recent conversation between Solidigm’s Conor Doherty, field applications manager at Solidigm, and Yann-Guirec Manac’h, head of hardware R&D at Scaleway, we get a closer look at how this European cloud provider is not only keeping pace with hyperscale trends, but is also helping to shape them through focused innovation in AI infrastructure and sustainability.

Scaleway’s approach feels refreshingly grounded. It focuses on delivering a complete foundation — compute, network, storage — and binding it all together with a unified control plane that supports both traditional and AI workloads. But what really sets them apart is the dual-track strategy for AI: accessible GPU instances for smaller-scale use, and massive, tightly interconnected GPU clusters for the heavy-duty training jobs. It’s the kind of infrastructure that recognizes how AI work isn’t a one-size-fits-all operation — some tasks need 2 GPUs, while others demand thousands. Scaleway is designing for both.

Gaining a deeper understanding of Scaleway’s AI strategy starts with examining the data pipeline. As Yann-Guirec put it, AI training isn’t just compute-heavy — it’s about data complexity, scale and flow. Harvesting and curating vast datasets, handling throughput during training, managing checkpoints and doing inference all require different storage strategies. Cold storage for archival compliance, warm layers for preparation and hot storage for training — each has different hardware implications. It’s not just about speed, it’s about adaptability, and Scaleway’s infrastructure acknowledges that every phase in the AI pipeline has unique demands.

With the conversation around sustainability finally taking center stage in tech, Scaleway’s stance is more than a footnote — it’s core to their identity. Backed by the Iliad Group, the company has built and operates data centers that run on 100% renewable energy. DC5, the data center that houses a lot of their AI pods, forgoes traditional air conditioning in favor of adiabatic and free cooling methods. The result is dramatically lower power usage effectiveness without sacrificing performance. But Yann-Guirec takes it a step further, pointing out a rarely discussed metric: water usage. Scaleway is looking at water usage effectiveness as well, with a view toward responsible innovation that doesn’t overlook environmental cost.

What’s perhaps most fascinating is how Scaleway sees the future of AI training workloads. Today’s language models may be grounded in web-scale text, but tomorrow’s models — multimodal, agentic and domain-specific — will need exponentially more data across formats, such as images, audio and video. That means even more demand on both GPU throughput and the bandwidth feeding those GPUs. Scaleway is building toward this future now, with GPU pod systems capable of pushing hundreds of gigabits per second and storage systems built to scale with that need.

While big names in AI infrastructure often dominate the narrative, conversations like this remind us that serious innovation is happening beyond the usual suspects.  

So, what’s the TechArena take? Scaleway isn’t trying to be everything to everyone – but for teams building sophisticated AI pipelines, in Europe and beyond, it’s quickly becoming a name to watch.

To dive deeper, visit scaleway.com.

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At the NVIDIA GTC conference, where the latest advancements in AI and high-performance computing (HPC) are on display, Scott Shadley, director of leadership narrative and evangelist of Solidigm, sat down with Carrie Wang, sales marketing at Giga Computing, and TechArena, to discuss the rapidly evolving landscape of enterprise technology and AI infrastructure. Our conversation shed light on the critical role data centers and efficient computing play in addressing the growing demand for AI-driven workloads.

Giga Computing is making significant strides in the AI and HPC arenas. Carrie spoke about the company’s journey, noting how GIGABYTE’s server business began with a small team back in 2000, ultimately evolving into a leader in the AI infrastructure sector. Today, Giga Computing, a wholly owned subsidiary of GIGABYTE, is shaping the future of high-performance AI, cloud and HPC solutions for businesses worldwide.

As AI adoption surges across industries, the need for power-efficient and scalable infrastructure has never been more critical. Carrie highlighted that AI inferencing, the process of applying trained models to real-world data, is becoming more power efficient, but the growing demands of AI workloads mean that data-intensive processes are increasingly requiring better storage, networking and compute solutions.

One of the standout solutions Giga Computing is showcasing this year is the GIGABYTE G893 GPU server platform. With support for NVIDIA HGX™B200 and NVIDIA HGX™ B300 NVL16, this platform is specifically designed to handle the most demanding AI and HPC workloads. Paired with NVIDIA BlueField®-3SuperNICs, the G893 delivers outstanding performance while minimizing energy consumption – a key concern as data centers grapple with rising power demands. Additionally, Giga Computing’s innovative cooling solutions, including the GIGABYTEG4L3 platform, ensure that these powerful systems run efficiently even under heavy loads. At the conference, Giga Computing presented a comprehensive solution for data centers, featuring a direct liquid cooling (DLC) rack system that combines multiple racks for a fully integrated solution.

The conversation also touched on how Giga Computing is addressing the challenges faced by the industry. With AI workloads continuing to surge, the demand for power-hungry data centers is driving up rental rates, with increases of up to 6.5% compared to the first half of 2023. In this environment, businesses must carefully select the right components to maximize performance while keeping power consumption in check. It’s a delicate balancing act, and Giga Computing’s solutions are designed to help customers optimize their infrastructure to address these challenges.

Another topic discussed was the rise of agentic AI — systems capable of making decisions autonomously based on real-time data. Carrie emphasized that agentic AI relies heavily on inferencing, and Solidigm’s NVMe solid state drives (SSDs) play a critical role in supporting these models. With Solidigm’s cutting-edge storage solutions, customers can efficiently handle large-scale datasets in their data centers, minimizing delays and ensuring low costs and power consumption.

So, what’s the TechArena take? As AI, HPC, and cloud workloads continue to evolve, it’s clear that collaboration between companies like Solidigm and Giga Computing is key to driving the next wave of innovation. By working together to deliver integrated solutions that prioritize performance, power efficiency, and scalability, these companies are setting the stage for the future of AI infrastructure.

Watch the full video here.

For those looking to learn more about Giga Computing and their groundbreaking solutions, you can visit their website, gigabyte.com/Enterprise, or follow them on LinkedIn and Twitter to keep up to date on their latest offerings and innovations.

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Solidigm's Roger Corell chats with ICE's Anand Pradhan to explore how AI, storage, and system design fuel 700B+ daily trades — and what AI inference means for the future of storage at scale.

At the forefront of IT infrastructure advancements, ASBIS has been making significant strides in providing high-performance solutions, particularly in the transition from traditional hard drives to solid-state drives (SSDs). This shift, driven by the growing demand for speed, reliability and energy efficiency, has seen ASBIS collaborate closely with Solidigm, a leader in the SSD industry, to deliver cutting-edge storage solutions. Eduards Lazdins, business development manager at ASBIS, shared insights into the company’s approach during a recent discussion with Steve Gutierrez, director of sales at Solidigm, and TechArena

ASBIS, a value-added distributor and solution provider, has an expansive footprint that spans 28 countries, with over 20,000 active customers across 60 nations. Its reach is impressive, but it’s the company’s ability to address the unique needs of diverse markets that really stands out.  

ABSIS serves a mix of established and emerging markets facing an array of opportunities and challenges for IT infrastructure development. While Western Europe leads in cloud adoption and AI-driven workloads, regions like Central and Eastern Europe, the Caucasus and parts of the Middle East and Africa are catching up rapidly. The challenge is striking the right balance between affordability and performance. This is where ASBIS excels — by offering high-performance solutions at scalable price points, making cutting-edge technology accessible to a wide range of customers.

ASBIS’ approach to staying ahead in the competitive IT landscape involves constantly expanding its product portfolio and geographical reach. The company is not just a traditional distributor — it operates its own server assembly line in the European Union, with the capacity to produce thousands of servers per month. This vertical integration, combined with strong partnerships with leading brands, such as Solidigm, enables ASBIS to deliver tailored solutions that meet the specific needs of its diverse customer base.

A key focus of ASBIS’ strategy has been the transition to SSDs, and it has leveraged its collaboration with Solidigm to accelerate this shift. SSDs provide significant advantages over traditional hard drives, such as faster speeds, improved reliability and lower power consumption. As businesses increasingly turn to SSDs for their storage needs, ASBIS is helping customers adopt this next-generation technology with specialized services, including pre-sales consultancy, robotic solutions, technical support and custom solutions.

One example of ASBIS’ impact is its work with cloud service providers and data centers. By integrating Solidigm’s SSDs into their infrastructure, ASBIS has helped optimize storage solutions, significantly reducing latency and improving workload efficiency. For industries handling vast amounts of data, these improvements in speed and reliability are essential. ASBIS’ solutions have not only enhanced performance, but also minimized power consumption, a critical factor for organizations aiming to reduce operational costs and carbon footprints.

What’s the TechArena take? In a world where technology is rapidly advancing, ASBIS’ commitment to providing innovative, high-performance solutions is a prime example of how the right partnerships and a focus on customer needs can drive real-world results. Looking ahead, ASBIS is well-positioned to continue leading the charge in IT infrastructure solutions, offering both the expertise and technology to meet the evolving needs of its customers.  

To learn more about their product offers and solutions, visit ASBIS.com, or follow them on  LinkedIn and X for the latest updates.

At CloudFest 2025, Supermicro showcased their innovations that are driving the future of AI, cloud infrastructure and storage solutions. As AI technology continues to evolve, Supermicro’s ability to deliver cutting-edge hardware solutions has become a game-changer, and their booth at CloudFest served as a testament to that progress. Solidigm’s Hayley Corell spoke with Thomas Jorgensen, senior director in the Technology Enabling Group at Supermicro,to dive deeper into how Supermicro is powering AI advancements and meeting the growing demands of modern infrastructure.

Thomas highlighted the rapid growth in AI, noting that the demand for powerful AI infrastructure is being driven by large-scale model training and, increasingly, AI inferencing. But what's crucial for this advancement? A center element of that answer is storage. Supermicro understands that AI models require fast, reliable storage to keep GPUs from idling, ensuring that the entire infrastructure is working in concert to deliver results as quickly as possible. As Thomas bluntly put it, “AI doesn't work without storage,” and Supermicro is delivering solutions to meet this growing demand.

Over the past few years, AI’s exponential growth has shifted the way companies are approaching infrastructure. As Supermicro and the rest of the industry ride the wave from training centric infrastructure demand to a demand curve that also reflects inference, new kinds of infrastructure for a wider range of environments is required. As AI continues to be specifically integrated into edge environments, Supermicro is positioning itself at the forefront, enabling AI at the edge with small, fanless servers that process inferencing directly where data is generated. This localized approach reduces latency, and it also improves the speed at which data is processed, ensuring AI workloads perform seamlessly.

A key part of Supermicro’s success lies in its commitment to delivering high-performance, low-latency infrastructure. Thomas discussed how AI clusters require not only powerful GPUs, but also fast network communication and efficient storage systems. The infrastructure design has evolved significantly to meet the demands of AI, particularly with the rise of high-density petascale storage solutions. Supermicro’s focus on providing multi-tiered storage setups ensures that data is delivered at optimal speeds for any given AI workload, enabling seamless performance across AI applications.

The collaboration between Solidigm and Supermicro has been crucial in driving these advancements, particularly in the realm of high-speed storage. Solidigm’s cutting-edge storage solutions, such as their high-capacity SSDs, perfectly complement Supermicro’s AI infrastructure. By combining Solidigm’s innovative storage technology with Supermicro’s powerful hardware, they deliver the performance and reliability required to handle the intense data demands of AI workloads.

This collaboration helps ensure that AI models can access and process data quickly, making it an essential part of AI-driven infrastructure.

Supermicro's petascale storage is capable of integrating up to 122 terabyte SSDs. This massive capacity allows AI workloads to scale up and manage vast amounts of data with ease.

So, what’s the TechArena take? For on-prem AI deployments, tapping large volumes of data locally for AI integration across business functions is becoming increasingly critical, especially as many businesses shift away from the cloud due to rising costs and data privacy concerns. Supermicro’s petascale storage delivers the speed and bandwidth needed to support the growing demands of AI models, ensuring that organizations can keep up with both the scale and complexity of modern AI workloads right from their own data centers. Solidigm’s leading 122 TB drives are a perfect match for these large scale deployments.

For those looking to learn more, Supermicro offers an abundance of resources on their website (supermicro.com) and social media channels (X, LinkedIn and YouTube).

From eight-way GPU racks to liquid cooling breakthroughs, Giga Computing and Solidigm explore what it takes to support AI, HPC, and cloud workloads in a power-constrained world.

Scaleway’s Yann-Guirec Manac'h shares how the company is simplifying complex AI pipelines, maximizing SSD performance, and driving sustainable innovation in European cloud infrastructure.

1. What are some of the key challenges your customers face related to generating, storing and processing high volumes of data?
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• Cost and Unpredictable Spending: The cost associated with traditional data warehousing solutions, especially in cloud environments, has become unpredictable and is leading to budgets spiraling out of control.
• Data Movement: Moving data between disparate systems is inefficient, introduces vulnerabilities, security risks, and increases operational complexity.  
• Increased Energy Consumption: Running compute-intensive workloads on legacy hardware and software architectures leads to excessive energy consumption and a large environmental footprint. This restricts an organization’s ability to innovate sustainably and impacts the overall operational burden associated with large, complex data workloads.
• Data Preparation: Preparing data for AI and machine learning is a time-consuming and resource-intensive process, with a lot of that complexity having to do with data pipeline.  
• Operational Burden: Maintaining and managing complex data environments and pipelines poses a significant operational burden on enterprise teams who may already be constrained for time and resources.
• Data Sprawl: Enterprises with data spread across many different systems struggle with inefficient data ecosystems and sprawl.
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2. How are you helping to address these challenges with the products and services you provide?
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• Unified Data Platform: Ocient’s data platform consolidates various analytics capabilities into a single, efficient system, built for sustainable data performance with compute-intensive workloads.
• Compute-Adjacent Storage Architecture (CASA): Ocient's innovative architecture brings compute directly to the storage layer, minimizing data movement and maximizing processing efficiency.
• SSD-Based Infrastructure: With hardware partners like Solidigm, Ocient leverages an all-NVMe SSD architecture for high performance and efficiency.
• In-Database Machine Learning (OcientML): Ocient’s in-database machine learning capabilities enabling customers to train and deploy models directly on their data.
• Customer Solutions and Workload Services: Ocient offers comprehensive customer support, including pre-purchase workload analysis and post-purchase optimization, ensuring successful deployments and sustained customer success.
• Built for Efficiency: Ocient enables organizations to reduce the total cost of ownership, operational burden, and environmental footprint of their analytics and AI use cases.
• Streamlined & Consolidated Analytics Stack: Ocient helps organizations consolidate and streamline their analytics stack, eliminating the need for disparate ETL, real-time streaming, and orchestration solutions in many implementations.
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3. How has the shift to high-density SSDs impacted your ability to handle massive-scale workloads, particularly in industries like telecommunications, geospatial analytics, and financial services?
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• High-density SSDs, like those delivered by Solidigm, are foundational to Ocient's architecture and our CASA-based approach to large, complex, costly data workloads.  
• With an architecture underpinned by SSDs, Ocient is able to deliver extremely fast data access and processing, which is essential for the following industry verticals:
  • Telcos (e.g. data retention and disclosure; internet connected records),
  • AdTechs (e.g. real-time bidding and reporting)
  • Public Sector organizations (e.g. geospatial analytics; network operations and security, search and analysis)
• The speed and efficiency of SSDs enable Ocient to deliver real-time analytics and data processing capabilities that would be nearly impossible with traditional hard disk drives.
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4. Can you elaborate on the role of high-capacity SSDs in enabling energy efficiency and sustainability within your data centers?
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• With hardware-aware software and innovations delivered via Ocient’s Hyperscale Data Warehouse, Ocient can reduce the cost, energy, and system footprint for data and AI workloads by up to 90% 
• Using SSDs with massively better IOPS than HDDs means that you can use fewer drives to handle real-time data and therefore cut the carbon footprint.
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5. What opportunities do these advanced storage solutions unlock for your clients in terms of real-time analytics, data accessibility, and scalability?
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• Cost Reduction: Cost efficiencies delivered via the hardware and software layer translate to an overall efficient system capable of delivering powerful data performance at a significant cost reduction.  
• Scalability: Ocient's platform is designed for sustainable growth and data performance, which allows customers to handle massive-scale workloads while also being future-proof for future workloads.
• Faster Machine Learning: The ability to run machine learning directly on the data within Ocient's platform accelerates the deployment of AI models.
• Reduced Complexity: Consolidating data environments and simplifying data pipelines reduces operational complexity and frees up resources for innovation.

At GTC 2025, Arm’s Chloe Ma explains how AI is shifting from compute to full-system optimization — and why storage, inference, and the edge are becoming central to tomorrow’s intelligent infrastructure.

With NVIDIA CEO Jensen Huang’s headline-grabbing reference to GTC as the “Super Bowl of AI,” expectations for this year’s conference were sky-high — and key players delivered. Among the standout innovations was Alluxio’s contribution to transforming how data is managed and accelerated in AI workloads. Scott Shadley, Director of Leadership Narrative and Evangelist at Solidigm, joined Bin Fan, Founding Engineer and VP of Technology of Alluxio, to discuss how their team has been pushing the envelope in AI data acceleration and efficient storage management, and quickly establishing a tangible impact on how AI models are trained and deployed across industries.  

At the heart of Alluxio’s innovation is its ability to decouple storage and compute. Traditionally, data storage has been tightly coupled with compute resources, limiting the scalability and speed of AI workloads. But with Alluxio’s technology, data scientists and AI modelers no longer need to worry about the complexities of storage management. Instead, Alluxio introduces an abstraction layer between applications and storage, making data access seamless and efficient.

One of the most compelling aspects of Alluxio is its ability to accelerate data access. By positioning Alluxio close to GPU applications, the technology significantly reduces the time it takes to access large datasets, especially in geographically dispersed environments. This is particularly important for AI workloads that require massive amounts of data across different regions or clouds. With Alluxio’s caching layer, repeated data access is minimized, ensuring that applications are running at peak performance without the usual latency or overhead.

But Alluxio isn’t just about speeding things up – it also brings simplicity and flexibility to the table. By abstracting storage into a unified structure, their solution enables organizations to seamlessly manage their data across multiple on-prem and cloud deployments without the hassle of manual configuration or inconsistent access. Whether it's scaling up GPUs in one region or shifting workloads to another, Alluxio’s virtualization and abstraction layers provide a seamless experience for both data engineers and end users.

To meet these varied and demanding workloads, Alluxio has partnered with Solidigm to provide reliable, high-capacity storage solutions. While Alluxio serves as the software layer for managing data storage, Solidigm brings its experience as a leading supplier of SSDs to offer the ideal hardware for Alluxio’s caching layer. Together, this collaboration ensures that AI workloads are running on the fastest, most reliable infrastructure possible. The ability to store and retrieve data efficiently is essential in today’s fast-paced AI landscape, and Alluxio’s integration with Solidigm hardware delivers that performance without compromise. (Learn more about data storage optimized for the AI era.)

Alluxio is doing more than just keeping up with the growing demand for AI infrastructure — it’s leading the way in making data management simpler, faster, and more efficient. As AI continues to evolve, technologies like Alluxio will be at the forefront, empowering organizations to harness the full potential of their data.

For anyone curious about diving deeper into Alluxio’s capabilities, the company’s website, alluxio.io, and social media channels, including YouTube, offer a wealth of resources. Watch the full video here.

Peak AIO’s Roger Cummings joins Solidigm’s Scott Shadley at NVIDIA GTC to talk AI infrastructure shifts, single-node innovation, and making data placement as intelligent as the AI it powers.

At NVIDIA GTC 2025, Cloudflare shared an exciting vision for the future of AI, automation, and developer tools. During a conversation with Scott Shadley, Director of Leadership Narrative and Evangelist at Solidigm, Aly Cabral, Cloudflare VP of Developer GTM, explained how they are becoming a critical player in the rapidly evolving tech landscape. As industries shift and change, Cloudflare’s focus is clear: empowering developers to navigate these transformations with the right tools and ample support.

One of the main topics of discussion was agentic AI, and how to define the loosely used term that’s been all the rage for next-gen AI predictions. Simply put, agentic AI goes beyond traditional automation by enabling systems to make decisions and manage more complex, dynamic tasks autonomously. While automation improves efficiency, agentic AI adds intelligent oversight, making it easier to both monitor and manage automated systems. Aly emphasized that automation alone isn’t sufficient — it’s about creating systems that are not only efficient, but also transparent and easy to troubleshoot. Cloudflare’s Workflows product addresses this by giving developers visibility into complex systems, helping them quickly identify and resolve issues in multi-step processes. This capability is becoming even more essential as automation plays a larger role in development.

In addition to automation, CodeGen tools are emerging as valuable resources for developers. These AI-powered tools simplify the coding process, allowing developers to generate code faster and with less effort. However, as Aly pointed out, the real challenge lies not in creating applications, but in managing and maintaining them over time. Cloudflare’s platform is built to support developers throughout the entire lifecycle of an application — from creation to long-term management — ensuring that systems remain scalable, secure, and efficient as they evolve.

Looking forward, Cloudflare is doubling down on AI and developer tools. As Aly mentioned, the company is preparing for Developer Week in April, where they’ll unveil new launches and innovations aimed at improving the developer experience. With new features and tools focused on simplifying the development process and harnessing the power of AI, Cloudflare is working to ensure developers have everything they need to create smarter, more scalable applications.

So, what’s the TechArena take? Cloudflare’s approach to partnerships sets them apart. Rather than locking customers into proprietary ecosystems, Cloudflare prides itself on being a connector, offering a globally distributed network and an open ecosystem that integrates well with a wide variety of third-party services – without an aggressive egress tax. This flexibility allows developers to use the best tools for their needs without being restricted to a specific platform. It’s this open approach that makes Cloudflare an ideal partner for companies like Solidigm, who offer unique solutions that complement Cloudflare’s services.

Watch the full video here. Learn more about Solidigm’s data storage solutions for the AI era here.

For those interested in staying connected with Cloudflare’s latest developments, the company maintains an active Discord community, YouTube channel, and X presence, providing ample opportunities for engagement and learning. Or visit their website.

I recently had the opportunity to sit down with Jeniece Wnorowski of Solidigm, and George Crump, Chief Marketing Officer at Verge.io, to discuss how Verge.io is taking a fresh approach to IT solutions.

The Verge.io solution is game-changing for enterprises looking to optimize their IT infrastructure. Instead of relying on the traditional method of integrating different components through a GUI (Graphical User Interface), Verge.io has gone a step further by combining all aspects of IT infrastructure—networking, storage, and virtualization—into a single, unified code base. This results in a seamless user experience coupled with a dramatic improvement in performance - all while lowering hardware requirements.

By integrating these components, Verge.io improves efficiency and increases hardware flexibility. George shared that Verge.io supports hardware up to seven years old, making it highly adaptable for organizations with legacy systems. This innovation stems from Verge.io’s founding story — Greg Campbell, Verge.io’s CTO, was initially frustrated by the amount of time he spent managing infrastructure while developing a search engine to compete with Google and Amazon – so he decided to build his own solution. Today, this approach has resulted in a product that runs on less than 300,000 lines of code, ensuring fewer bugs and greater reliability compared to traditional solutions that often operate on millions of lines of code.  

The solution also addresses one of the most pressing concerns for IT professionals today—cost predictability. Verge.io’s simple licensing model charges per server rather than by core or capacity. This straightforward pricing model appeals to a wide range of IT professionals. By supporting multi-tenancy, Verge.io makes it easier to manage resources across various clients, delivering efficiency and flexibility in a shared environment.

As AI continues to shape the future of IT infrastructure, Verge.io’s platform is designed to be AI-ready. George highlighted the growing importance of AI in enterprise workloads, particularly as organizations explore the use of private AI models. Verge.io is addressing the challenge by ensuring its platform can easily integrate GPUs for AI workloads.

One of the key factors that sets Verge.io apart from others in the market is its approach to migration. As George pointed out, migration is essential when transitioning to a new infrastructure. He also shared that Verge.io’s approach ensures minimal downtime, enabling businesses to shift their data and settings with greater efficiency. This streamlined migration process is key to Verge.io’s ability to deliver a seamless experience for their customers, no matter the scale.

In addition to seamless migration, Verge.io focuses heavily on reliability through its integrated platform. George pointed out that the system continuously monitors the environment, ensuring operations run smoothly even during network disruptions. For example, he described how Verge.io's platform maintained data integrity during network failures when traditional infrastructure would have struggled to do the same.

For enterprises considering storage solutions, Verge.io is leveraging Solidigm’s storage technology to optimize performance and lifespan. George shared how the platform supports various classes of SSDs, including QLC and TLC drives, and integrates them seamlessly into the infrastructure to meet workload demands. This approach ensures that organizations can optimize performance while managing their storage needs efficiently.

So, what’s the TechArena take? Verge.io’s unified infrastructure solution is reshaping the way organizations manage their IT environments. With a focus on cost predictability, AI-readiness, and seamless migration, Verge.io presents a compelling option for businesses that are looking to simplify their infrastructure and improve efficiency.

Listen to our full discussion here.

In this Data Insights episode, Andrew De La Torre discusses how Oracle is leveraging AIOps to enable automation and optimize operations, transforming the future of telecom.

During GTC, Solidigm’s Scott Shadley and Dell’s Rob Hunsaker, director of engineering technologists, discussed how Dell is tackling the challenges of AI data infrastructure with cutting-edge solutions.