Solidigm – a Bigger, Faster, and More Efficient Storage for AI

Solidigm’s AI Field Day presentation highlighted the critical role of large-scale, high-efficiency storage solutions like NAND flash memory in meeting the evolving demands of AI, as covered by tech analyst Ben Young. The company, born from the union of Intel’s NAND SSD business and SK Hynix, demonstrates expertise in delivering high-density QLC SSDs, such as the D5-P5336 model, which significantly outperforms traditional HDDs in capacity and speed while reducing energy consumption. Solidigm’s storage innovations, offering up to 61.44TB per slim drive, not only future-proof AI infrastructure but also promise to drive advancements across various industries by improving training times and real-time decision-making capabilities.

Solidigm SSDs for the AI Era – Small Size, Big Value

Solidigm’s presentation at AI Field Day focused on their ambition to deliver industry-leading storage solutions that address the escalating storage and energy consumption needs of AI workloads, as Sulagna Saha reports for Gestalt IT. Positioning itself as a provider of affordable, high-capacity SSDs, Solidigm’s D5-P5336 model stands out with its 61TB capacity within a compact 2.5” form factor, presenting a pathway to significantly lower TCO and energy costs for massive AI deployments. The company’s innovative storage solutions, coupled with Cloud Storage Acceleration Layer (CSAL) technology, promise to streamline data flow to GPUs, enhancing model training and inferencing performance across varied AI workflows.

Intel Xeon CPUs – How Efficiency Makes It a Top Contender for AI Inference

In the AI arms race, Intel’s latest 5th generation Xeon processors have emerged as a powerful and efficient alternative to GPUs for certain AI workloads, according to Ben Young’s AI Field Day article. With a 36% performance boost in specialized AI tasks enabled by Advanced Matrix Extensions (AMX), these CPUs accelerate deep learning particularly for AI inference, offering a cost-effective option for applications with lighter and less frequent processing needs. Intel’s dedication is clear as they bolster their CPUs’ AI capabilities and facilitate developers with tools like the OpenVINO toolkit, positioning Xeon CPUs as a feasible choice for an array of AI workloads, balancing the scale with GPUs based on the specific requirements of the task. Read more in this Gestalt IT article by Ben Young, sponsored by Intel.

Building a Future-Proof AI Foundation With VMware Private AI

VMware’s presentation on Private AI at AI Field Day emphasized their forward-looking approach in creating a scalable and secure foundation for enterprises investing in artificial intelligence. Their platform addresses the challenges of AI deployment and management, optimizing compute resources and providing robust data processing capabilities. With VMware’s Private AI, businesses are empowered to harness the full potential of AI applications while ensuring compliance and protecting sensitive data. Read more in this Gestalt IT article by Sulagna Saha!

Solidigm and Why Storage Is Critical to the Success of AI

At AI Field Day, experts from Solidigm and Supermicro illuminated the critical role of high-performance storage in ensuring the success of Generative AI, which demands instant, uninterrupted access to massive datasets. Efficient storage solutions are paramount to prevent downtime, which can lead to significant loss in both productivity and financial terms. Their discussion underlined the importance of structuring and cataloging data for future use, emphasizing that optimized storage systems with high IOPS (Input/Output Operations Per Second) are essential for Generative AI’s accelerating growth and the reliable generation of actionable insights. Read more in this article by Jeff Powers for Gestalt IT, sponsored by Solidigm.

Hammerspace Global Data Environment – a Shared Space for All the Data

Hammerspace’s presentation at AI Field Day showcased its Global Data Environment, which streamlines data orchestration for AI model training by providing global real-time visibility and access to distributed datasets. The company’s innovative approach decouples file system metadata from the underlying storage, enabling a universal access layer across geographies and cloud platforms. By facilitating a shared metadata control plane, Hammerspace ensures seamless user experience and efficient data management for complex enterprise AI workflows. Read more in this Gestalt IT article by Sulagna Saha.

Credible Content From the Community is More Important than Ever

There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities. In the first episode of Tech Field Podcast, recorded on-site at AI Field Day, Stephen Foskett chats with Frederic Van Haren, Gina Rosenthal and Colleen Coll about confronting inauthentic content.

Keeping GPUs Fed Around the Clock, With Solidigm

As discussed at AI Field Day, Solidigm’s storage system addresses the diverse and intense demands of AI workloads, ensuring GPUs remain constantly fed with data. Recognizing the variety in I/O patterns and the substantial data processing required for machine learning, Solidigm’s SSDs offer superior performance for sequential and random read/write activities, consuming less power and space in datacenters. Additionally, their Cloud Storage Acceleration Layer (CSAL) software enhances the durability and efficiency of SSDs by optimizing write patterns, making it an open-source boon for those seeking to streamline AI-based operations. Read more in this Gestalt IT article by Sulagna Saha.

No-Code Machine Learning With Qlik AutoML

At AI Field Day, Qlik launched AutoML, a revolutionary no-code machine learning capability within Qlik Cloud, empowering enterprises to harness predictive analytics without the barriers of cost or lack of expertise. This innovative feature allows organizations to effortlessly integrate algorithmic prediction into their workflows, enabling data-driven decision-making across various departments from sales to finance. AutoML stands out as a tool that simplifies machine learning, offering a straightforward approach where users can develop models and analyze future trends with just a few clicks, transforming complex data science into actionable insights. Read more in this article by Sulagna Saha from Gestalt IT.

Exploring Data in the AI Era With Solidigm – New Data Insights Series

The TechArena has launched a Data Insights Series, joining forces with Solidigm, where they will explore the intricate landscape of data in the AI era. Hosted by Allyson Klein with Jeniece Wronowski and Ace Stryker from Solidigm, the series will delve into the objectives of understanding and leveraging data, underscoring the central role of SSD innovation in crafting modern data pipelines. This initiative aims to shed light on the transformative influence of storage solutions in AI advancements, positioning SSDs as a cornerstone technology in data-centric environments.

Nature Fresh Farms – Optimizing Indoor Farming Practices With AI and Intel

At AI Field Day, Nature Fresh Farms, a leader in greenhouse farming in North America, revealed how the strategic use of Intel AI solutions revolutionized their farming practices towards precision agriculture. Keith Bradley highlighted the transition from traditional to high-tech farming, with on-premises Intel-based infrastructure enabling real-time data analytics for improved yield, resource efficiency, and operational control. Emphasizing sustainability and the growing importance of AI in agriculture, Bradley shared how Nature Fresh Farms harnesses predictive AI models on the farm, leveraging technology to optimize every aspect from irrigation to packaging and contributing to a marked increase in yield per square meter annually. Read more in this Gestalt IT article by Sulagna Saha.

Next-Generation AI With VAST Data: Beyond Storage and Compute

This LinkedIn article by Gina Rosenthal discusses the VAST Data solution for AI data presented at AI Field Day. VAST Data pioneers AI and deep learning infrastructure with its integrated VAST Data Platform, as presented in partnership with NVIDIA and Supermicro that further solidify VAST’s role in streamlining AI adoption and digital transformation.

Don’t Let Storage Be Your AI Training Kryptonite

In the rapidly advancing field of AI, efficiently managing checkpoints during model training is crucial, and Solidigm’s QLC drives offer a solution that mitigates the risk of slow storage becoming a bottleneck. Their high-performance drives support the significant read/write operations required for frequent checkpointing, enabling data scientists to maintain efficient workflows and reduce training costs. Solidigm’s dense storage enclosures optimize data centre space while providing the necessary infrastructure for high-capacity AI datasets, proving that fast storage is the unsung hero in the race towards AI innovation. Read more in this article by Ben Young, reacting to AI Field Day.

Deploying AI Cost-Effectively at Scale With Kamiwaza

At AI Field Day, Kamiwaza introduced their open-source stack, designed to enable GenAI to scale elastically, addressing the common hurdles of infrastructure cost and operational scale faced by enterprises. With a vision to empower businesses to achieve a trillion inferences a day and ignite the 5th industrial revolution, Kamiwaza’s stack facilitates AI deployment across various environments, from cloud to edge, guaranteeing security and manageability of dispersed data. The stack’s compatibility with Intel CPUs ensures that enterprises can harness efficient AI inferencing power with minimal energy consumption, making sophisticated AI accessible and sustainable for organizations of all sizes. Read more in this Gestalt IT article by Sulagna Saha.

Compute Requirements in the AI Era With Intel’s Lisa Spelman

In this TechArena interview, Allyson Klein explores with Intel’s Lisa Spelman the evolving compute demands as enterprises gear up for the AI revolution and strive for widespread AI integration. They delve into the current state of AI adoption across industries while highlighting the critical role of software, tools, and standards in scaling AI solutions effectively. This insightful discussion underscores the thriving synergy between hardware advancements and software ecosystems necessary to power the next generation of AI applications.

At AI Field Day, Qlik Shows AI-Based Analysis Added to Its Platform

At AI Field Day, Qlik unveiled a wizard-based AI feature that simplifies the process of leveraging on-premises data for insightful analytics, integrating smoothly with Qlik’s cloud services. This enhancement to their analytics platform aims to democratize AI’s benefits, making advanced data analysis accessible to a broader range of users with varying expertise. Qlik’s initiative reflects a commitment to user-friendly, AI-powered analytics, facilitating deeper insights while streamlining the experience for its customers. Read more in this analyst note for The Futurum Group by Alastair Cooke.

Why Storage Matters for AI: Solidigm Shares POV at AI Field Day

During AI Field Day, Solidigm’s Ace Stryker and Alan Bumgarner illustrated the pivotal role of SSDs in AI applications, showcasing how they cater to the high data demands of models and workflows with increased efficiency. They highlighted the superiority of SSDs over HDDs in terms of performance and Total Cost of Ownership, emphasizing the tangible benefits from greater data density to reduced physical infrastructure needs. The presentation honed in on the importance of storage in AI, linking Solidigm’s advanced SSD solutions with scalable and power-efficient AI server operations, resonating with sustainability goals and operational cost reduction.

Google Cloud, the Preferred Platform for Building Competitive AI Models

At AI Field Day, Google Cloud’s Brandon Royal showcased the giant’s comprehensive strategy for meeting today’s burgeoning AI demands, leveraging one of the industry’s most extensive digital infrastructures. Emphasizing the significance of AI infrastructure in conjunction with generative AI (GenAI), Google Cloud highlighted their commitment to innovation, asserting their platform as the superhighway for AI-forward companies. With Google Cloud providing robust compute power off its own infrastructure, businesses can harness AI’s opportunities without the traditionally high entry barriers of infrastructure costs and expertise. Read more in this article by Sulagna Saha for Gestalt IT.

Deciding When to Use Intel Xeon CPUs for AI Inference

At AI Field Day, Intel offered insights into strategic decision-making for AI inference, highlighting scenarios where Intel Xeon CPUs outshine traditional GPU solutions on both on-premises and cloud servers. By evaluating the specific requirements of AI inference workloads, Intel guides users to make informed choices that enhance value while optimizing their existing server infrastructure. This approach emphasizes efficiency and practicality in deploying AI capabilities, ensuring that organizations can navigate the complex landscape of hardware selection for their AI initiatives. Read more in this Futurum Research Analyst Note by Alastair Cooke.

Hammerspace Shows Storage Acceleration for AI Training

At AI Field Day, Hammerspace showcased its innovative storage acceleration solution, demonstrating how Hyperscale NAS can be leveraged to enhance the performance of current scale-out NAS systems, particularly in training large language models (LLM) efficiently. This storage boost not only improves speed but also optimizes resource allocation during the intensive LLM training process. Hammerspace’s advancement offers organizations the opportunity to amplify their AI training capabilities without the need to overhaul their existing storage infrastructure. Read more in this Futurum Research Analyst Note by Alastair Cooke.