The rising cost of memory and storage, driven by the massive AI build out, might make on-premises datacenters uneconomical, and drive more cloud adoption. This episode of the Tech Field Day podcast features Ned Bellavance, Jim Czuprynski, and Alastair Cooke considering whether it is better to wait out the shortages or design for their effects. The core problem is the significant increase in costs for RAM and storage components like SSDs and hard drives, which is making on-premises infrastructure upgrades financially challenging for many organizations. This surge in prices is largely driven by substantial, long-term procurement agreements made by major cloud providers and companies developing AI data centers, leading to a global supply constraint. There are differing strategies for businesses to cope with this environment, including enhancing resource efficiency, optimizing software, and potentially leveraging the secondary hardware market or extending the life of existing equipment. The conversation also delves into broader industry impacts, such as the potential for AI to self-optimize resource usage, the challenges in building new, resource-intensive data centers due to power and water concerns, and predictions for when these current market conditions might stabilize and component prices could return to more typical levels.
Cloud Strategy, The Future of Infrastructure, and Of Course AI at Cloud Field Day 25
Cloud Field Day 25 kicks off March 11–12 with two days of in-depth technical discussions, live demos, and expert insights from some of the most innovative companies in the industry. On Wednesday at 9:00 AM PT, Hammerspace kicks things off by exploring real-world use cases for global namespaces and policy-based data management—especially for AI workloads. […]
Breaking the Data Gravity Curse in the AI Factory
In the latest discussion on breaking the data gravity curse in AI environments, Alastair Cooke highlights the challenges and solutions associated with managing large data sets that inhibit the mobility of applications across different platforms in an AI-driven ecosystem. Cooke explores how organizations are innovating to overcome these obstacles, enhancing efficiency and agility in their AI operations. For comprehensive insights on AI Infrastructure Field Day 4, visit Techstrong AI.
Cisco Reimagines AI Infrastructure for the Rest of Us
Alastair Cooke examines Cisco’s revamped approach to AI infrastructure, aiming to make it more accessible and efficient for broader user groups. He discusses how Cisco’s enhancements not only cater to large enterprises but also support smaller organizations striving to implement AI solutions. For a more comprehensive analysis of AI Infrastructure Field Day 4, visit Techstrong AI.
Ultra-Reliable Wireless for Your Physical and Mobile AI Devices
Alastair Cooke discusses the increasing reliance on ultra-reliable wireless networks to support physical and mobile AI devices, which are integral for maintaining seamless operations in various sectors. He explores the critical need for robust connectivity solutions that ensure these AI technologies function efficiently without interruption. For additional insights on AI Infrastructure Field Day 4, visit Techstrong IT.
To Get Better Business Value, We Need Better AI Infrastructure
Alastair Cooke emphasizes the crucial role of robust AI infrastructure in harnessing maximum business value from AI technologies. He explores how advancements in infrastructure can directly enhance the performance and efficiency of AI applications, thereby impacting business outcomes positively. For additional insights into AI Infrastructure Field Day 4, explore further articles by Alastair Cooke on Techstrong AI.
AI Has Escaped Your Datacenter Presented by Cisco
AI has driven your datacenter designs and is now moving outwards through your whole network. This episode of the Tech Field Day podcast features Lee Peterson from Cisco discussing AI and networks with Andy Banta, Jack Poller, and Alastair Cooke. The discussion explores how AI is “escaping the data center” and becoming pervasive across the network, necessitating a dual focus on “networking for AI” and “AI for networking.” The former involves building robust, high-performance, and secure infrastructure, particularly at the edge, to support AI workloads like real-time inference. The goal is to support new applications such as robotics, fraud detection, and small language models, moving beyond traditional cloud-centric deployments to a more federated model. The latter leverages AI to manage, optimize, troubleshoot, and secure the network itself, with Cisco utilizing deep network learning models, historical data, and expertise to create AI assistants that enable intent-based networking and streamline operations. Additionally, the conversation emphasizes the critical role of advanced security, including hardware-accelerated post-quantum cryptography, to protect data in this evolving, AI-driven environment from future decryption threats.
Billion-Dollar AI Headlines Obscure Real Business Value
The big headlines that we’re seeing around the massive funding of large AI companies are a distraction from the reality that AI is being built and used in business applications. This episode of the Tech Field Day podcast features Frederic Van Haren, Chris Grundemann, Brian Martin, and Alastair Cooke reflecting after AI Infrastructure Field Day in Santa Clara. Popular news often covers the creation of large, general purpose AI models, yet the real-world application of AI through inference is where most companies see a return on their investment. Similarly, the common understanding of “AI” is as a single topic, without a more granular view that differentiates between rules-based systems, traditional machine learning, and emergent generative models like Large Language Models (LLMs). Specialized AI models will be vital for cost-effective applications with enhanced efficiency and the integration of diverse AI capabilities into agentic architectures. Advanced security protocols and regulatory frameworks are vital to mitigate novel vulnerabilities, organizations must adapt to an extraordinarily rapid pace of technological evolution. AI has already had a profound impact on software development, potentially enabling widespread custom application creation.
AI Needs Resource Efficiency
As we build out AI infrastructure and applications we need resource efficiency, continuously buying more horsepower cannot go on forever. This episode of the Tech Field Day podcast features Pete Welcher, Gina Rosenthal, Andy Banta, and Alastair Cooke hoping for a more efficient AI future. Large language models are trained using massive farms of GPUs and massive amounts of Internet data, so we expect to use large farms of GPUs and unstructured data to run those LLMs. Those large farms have led to scarcity of GPUs, and now RAM price increases that are impeding businesses building their own large AI infrastructure. Task-specific AIs, that use more efficient, task-specific models should be the future of Agentic AI and AI embedded in applications. More efficient and targeted AI may be the only way to get business value from the investment, especially in resource constrained edge environments. Does every AI problem need a twenty billion parameter model? More mature use of LLMs and AI will focus on reducing the cost of delivering inference to applications, your staff, and your customers.
Cutting-Edge AI Networking and Storage Kick Off 2026 at AI Infrastructure Field Day 4
We’re kicking off 2026 with one of our most popular events, AI Infrastructure Field Day 4, running from January 28th through January 30th. The event will stream live on LinkedIn, Techstrong TV, the Tech Field Day website, and for the first time ever, on our YouTube channel, offering a front-row view of the latest in […]
Managing Edge AI and Computer Vision at Scale
Alastair Cooke discusses the complexities and strategies for effectively managing Edge AI and computer vision technologies when deployed at scale. He emphasizes the importance of integrating these advanced technologies to handle real-time data processing and decision-making across diverse industries. For additional insights on Zededa’s special Tech Field Day event, visit Techstrong IT.
ResOps: The Convergence of Security and Operations
Alastair Cooke explores the emerging trend of ResOps, highlighting its role in integrating security practices with operational procedures to enhance enterprise efficiency and security posture. This approach advocates for cohesive teamwork and streamlined processes between traditionally separate IT departments. For additional insights from Commvault SHIFT, watch Techstrong IT.
Modern Data Mobility is Challenging the Laws of Physics with Hammerspace
Modern data mobility is challenging the laws of physics; the speed of light is a fundamental limit for moving signals. This episode of the Tech Field Day podcast features Kurt Kuckein from Hammerspace discussing data movement and management with Jim Jones, Jack Poller, Andy Banta, and Alastair Cooke. The challenge is that the distributed nature of data, spread across the globe, creates significant obstacles for AI, particularly regarding the speed of light and power consumption. We delve into overcoming these limitations through technologies that facilitate data access and movement, touching on concepts such as efficient storage solutions (Open Flash Platform), the importance of centralized data management, and the agility required for evolving AI workloads. While the underlying principles of data management are not new, the scale and complexity of AI necessitate innovative approaches to ensure data can be accessed and utilized effectively, regardless of its physical location.
Tech Field Day Takeaways for 2025: Making AI Less Manic
2025 was the year of AI Mania. Everyone wants you to know where they stand with AI in their product. Tech Field Day has a different approach. In this special year end episode, Tom Hollingsworth, Stephen Foskett, and Alastair Cooke look back at the discussions and deep dives into AI and how Tech Field Day grounded them all in practical real terms. Our event leads discuss the boring reality of AI tools and how AI has a dual nature that must be understood to get real value. They also debate the changing landscape of security where AI is concerned, including the importance of data sovereignty. They wrap up with a focus on the fundamentals and how Tech Field Day continues to make those important for the community at large.
Generative AI Coding Tools Make Enterprise Applications Worse
AI is writing a large proportion of modern software and Generative AI coding tools make enterprise applications worse. This episode of the Tech Field Day podcast looks at AI generated applications with Calvin Hendryx-Parker, Jim Czuprynski, Jay Cuthrell, and Alastair Cooke. Satya Nadella says that up to 30% of the code Microsoft writes is AI generated, AWS is at about 25% AI generated code. We ponder whether there is a link between this AI generated code and the quality of the Windows 11 codebase, possibly even the recent AWS outage? Calvin has hands-on experience with a range of AI coding tools, finding he uses different AI tools for specialist tasks in his development projects. The easy task for AI coding is translating existing applications from one platform version to another, or rewriting existing application code in new languages. Both these tasks are onerous for human developers and ideal for an AI assistant. The unanswered question is whether generative AI tools can handle creating new functionality in enterprise applications, can AI fulfill the role of the senior developer or software architect?
Qlik Answers: Simplifying Data Analysis with Qlik’s AI Assistant
In this video, Jim Czuprynski and Alastair Cooke share their reactions to Qlik Answers after trying out the product as part of a Tech Field Day project. Qlik Answers, an AI-powered chat assistant, simplifies data querying by effortlessly importing complex documents and providing accurate, transparent answers. Its logging and attribution features enhance trust, while its potential to support structured data makes it accessible to non-technical users.
What Does It Mean To Bring the Cloud Experience Home?
Alastair Cooke’s article explores the concept of replicating the cloud experience within on-premises infrastructure, focusing on how businesses can achieve the agility and flexibility of cloud services directly from their own data centers. He discusses the various strategies, technologies, and challenges involved in transitioning to a hybrid model that supports seamless operation between cloud and on-prem environments. For further details from Broadcom’s VMware presentation at KubeCon, watch for coverage by Alastair Cooke on Techstrong IT.
The Attack Surface of Cloud-Based Generative AI Applications is Evolving
Alastair Cooke discusses the expanding attack surface of cloud-based generative AI applications, highlighting how their evolving nature introduces new security challenges. He emphasizes the importance of adapting cybersecurity strategies to safeguard against potential vulnerabilities inherent in these innovative technologies. For additional commentary on the Fortinet presentation at Cloud Field Day 24, check out Security Boulevard!
Commvault Launches AI Powered Cloud Unity Platform – YouTube
Tom Hollingsworth recently explored the launch of Commvault’s latest innovation, the AI-powered Cloud Unity platform, in a new YouTube video. This platform is designed to enhance data management capabilities by integrating artificial intelligence to streamline cloud operations. For more insights from Commvault SHIFT 2025, follow us on social media, and catch new episodes of the Tech Field Day Rundown every Wednesday on YouTube.
The Cloud Scout Model Delivers Reliability As An Embedded Capability
Alastair Cooke’s recent article discusses how the Cloud Scout Model is ingeniously designed to integrate reliability as a core functionality. This model focuses on proactive problem-solving and maintenance, enhancing cloud infrastructure performance and minimizing downtime. For further insights from the SOUTHWORKS presentation at KubeCon, check out the coverage on Techstrong’s DevOps site.