Exploring the Future of Enterprise AI Deployment and Innovation at AI Field Day 7

Join Tech Field Day, Techstrong, Futurum, and our panel of independent experts for AI Field Day 7, live October 29th and 30th, 2025. Watch live on Techstrong TV, LinkedIn, and the Tech Field Day website, where you can also view the full schedule.

Private Cloud is Not just Self-Service Virtualization

Private cloud is not just virtualization 4.0, self-service VM deployment doesn’t fulfil the same need as the Public Cloud. This episode of the Tech Field Day podcast features Mike Graff, Jon Hildebrand, and Alastair Cooke. Private cloud has evolved from simple virtualization to a more comprehensive, cloud-like experience, emphasizing the need for on-premises infrastructure to offer the same developer-friendly tools and APIs as public clouds. Some application repatriation is driven by cost concerns and enabled by rise of technologies like Kubernetes and OpenShift for managing containerized workloads. A unified control plane for hybrid cloud environments is vital, as is accurate cost accounting for on-premises resources. Enterprises will search for a hybrid approach where developers can deploy applications without needing to worry about the underlying infrastructure.

The Evolution of Cloud at Cloud Field Day 24

Cloud Field Day 24 is back in San Francisco on October 22nd and 23rd, bringing the brightest minds in enterprise cloud together for two days of innovation, insight, and live demos.

Your Edge Projects will Fail Without Fleet Lifecycle Management with ZEDEDA

Projects to deliver applications to edge locations will fail without comprehensive fleet lifecycle management. This episode of the Tech Field Day podcast features Sachin Vasudeva from Zededa discussing the importance of long-term edge management with Guy Currier and Alastair Cooke. There are unique challenges of managing edge deployments compared to cloud or on-premises environments. Focusing on business logic and application outputs while leveraging infrastructure providers to handle the complexities of packaging, deploying, and monitoring AI models enables diverse edge environments. Edge locations might have different hardware deployed, intermittent connectivity, requiring a balance between standardization and flexibility in managing edge devices and applications. Teams with rapid responsiveness and adaptation will better enable their business to respond to changing conditions, especially with the rapid pace of AI innovation.

Tech Field Day Experience at NetApp Insight 2025 Keynote Live Blog

Learn more about NetApp Insight 2025 during the Keynote in our delegate live blog!

Every AI Strategy Needs a Data Protection Strategy with Commvault

Every company lives in fear of a ransomware attack, whether they have suffered one or not, and this is even more critical in the era of AI. This episode of the Tech Field Day Podcast looks forward to Commvault SHIFT in November with a discussion of the importance of data protection to AI applications with Tim Zonca from Commvault, frequent delegate Gina Rosenthal, and host Stephen Foskett. AI applications are reliant on good data, and yet this same technology makes it easier for attackers to breach corporate controls. Today’s social engineering and phishing is more convincing than ever thanks to generative AI, and this has helped ransomware crews to adopt larger and more powerful attacks. Ransomware is a massive business, and it isn’t going away any time soon. At the same time, GenAI applications offer a new attack surface, as agentic AI is empowered to take action based on untrusted inputs. Not only can we not stop ransomware, but the pace and technical capabilities of these attacks keeps accelerating. There is reason for optimism, however, as data protection tools keep getting better. Today’s AI-optimized tools can effectively categorize data, burst or migrate to different locations, and roll back or recover from corruption or compromise. In the future, we will see increasing use of AI to monitor systems and data, detecting patterns and hardening the attack surface.

Moving Enterprise AI Applications From Experiments to Production with NetApp

Running enterprise applications in production is a lot different from the AI experiments many of us have been involved with so far. This episode of the Tech Field Day podcast, recorded prior to NetApp Insight 2025, features Ingo Fuchs from NetApp along with Gina Rosenthal, Glenn Dekhayser, and Stephen Foskett. AI applications often start as experiments with a limited data set, but once these are moved to production there are many critical decisions to be made. Data must be classified and cleaned, removing personal and financial data and proprietary information before it even reaches an LLM. Data also must be structured for embedding and vectorization prior to use by an LLM. And we have to ensure that data is up to date or the application will not serve the customer properly. Finally we have to consider whether it is proper and ethical to share and act on this data. Many of the challenges facing modern AI applications are similar to the historic issues faced by enterprise storage, and this is an area in which NetApp and their customers have decades of experience.

Passkeys are the Future

Passwords create friction and therefore users find ways around them. New technology such as secure enclaves and PKI allow us to create better solutions like passkeys. In this episode of the Tech Field Day Podcast. Alan Shimel and Kate Scarcella join Tom Hollingsworth to discuss the problems with traditional passwords and how passkeys overcome them. They also talk about why it has taken so long to adopt passkeys and what barriers remain to full implementation. The wrap up with a look at what might lay ahead on the horizon for the future of user security.

The Latest in Cybersecurity Innovation at Security Field Day 14

The world should be more secure, and Tech Field Day is helping make it that way with the latest edition of Security Field Day. The event features two full days of presentations from leading security companies, innovative startups, and expert delegates, all focused on keeping people and software safe in an ever-evolving threat landscape. Tune […]

Unified Flash Memory and Reduced HBM are Reshaping AI Training and Inference with Phison

AI will need less HBM (high bandwidth memory) because flash memory unification is changing training and inference. This episode of the Tech Field Day podcast features Sebastien Jean from Phison, Max Mortillaro, Brian Martin, and Alastair Cooke. Training, fine-tuning, and inference with Large Language Models traditionally use GPUs with high bandwidth memory to hold entire data models and data sets. Phison’s aiDaptiv+ framework offers the ability to trade lower cost of infrastructure against training speed or allow larger data sets (context) for inference. This approach enables users to balance cost, compute, and memory needs, making larger models accessible without requiring top-of-the-line GPUs, and giving smaller companies more access to generative AI.

Software is Automating Your AI Data Centre Infrastructure

Hardware always matters, especially in AI and now software is automating your AI data centre infrastructure. This episode of the Tech Field Day podcast features Gina Rosenthal, Barton George, Andy Banta, and Alastair Cooke. Generative AI brought new hardware into enterprise data centres; GPUs, TPUs, NPUs, XPUs all offload AI processing from CPUs for more performance and efficiency. Feeding these accelerators requires fast networks and fast storage, common topics for AI Infrastructure Field Day events. In parallel, sophisticated software to automate the deployment and operation of this new hardware is vital to return value fast and optimize the value from the hardware investment. Automation platforms are moving up towards delivering multiple AI applications on shared XPU infrastructure, where AI inference delivers the business value.

Pushing the Boundaries of AI Performance, Scale, and Innovation at AI Infrastructure Field Day 3

Tech Field Day is heading back in Santa Clara, California on September 10th and 11th for AI Infrastructure Field Day 3. You can watch live on the Tech Field Day website, LinkedIn Page, or Techstrong TV to see how the boundaries of performance, scalability, and innovation are being pushed by our presenting companies. The event […]

Agentic AI Spells the End of Dial Twiddlers

If you haven’t already, start working with Generative AI now and make sure to control your ongoing costs. This episode of the Tech Field Day podcast features Russ Fellows, Mitch Lewis, and Brian Martin, all from Signal65, and is hosted by Alastair Cooke. Generative AI is delivering value to businesses of all sizes, but significant evolution in models and technologies remains before maturity is achieved. Experimentation is essential to understand the value of new technologies, starting with cloud resources or small-scale on-premises servers. Business value is derived from the inference stage, where AI tools generate actionable information for users. Generative AI is like a knowledgeable and well-intentioned intern; someone more senior must ensure AI is given good instructions and check their work. In production, grounding and guard rails are vital to keep your AI an asset, not a liability.

Networks Need Agentic AI with HPE Juniper Networking

Agentic AI is reshaping the IT landscape and networking is no exception. Building upon the previous research into machine learning means we have a head start on harnessing that power. In this episode of the Tech Field Day podcast, brought to you by HPE Juniper Networking, Tom Hollingsworth is joined by Keith Parsons and Sunalini Sankhavaram. They talk about how agentic AI is driving new methods for operating networks and helping humans concentrate on real problems instead of menial tasks. They also discuss how agentic AI can power self-driving networks where configuration and provisioning are done automatically or with a minimum of effort to ensure resiliency and enhance user expectations.

A Look at Mainframe Innovation at Tech Field Day Extra at SHARE Cleveland 25

Tech Field Day Extra at SHARE Cleveland on August 19 promises a deep dive into mainframe innovation, and viewers are encouraged to subscribe to the Tech Field Day YouTube channel and follow the LinkedIn page for ongoing Field Day coverage.

Early Adoption of Generative AI Helps Control Costs with Signal65

If you haven’t already, start working with Generative AI now and make sure to control your ongoing costs. This episode of the Tech Field Day podcast features Russ Fellows, Mitch Lewis, and Brian Martin, all from Signal65, and is hosted by Alastair Cooke. Generative AI is delivering value to businesses of all sizes, but significant evolution in models and technologies remains before maturity is achieved. Experimentation is essential to understand the value of new technologies, starting with cloud resources or small-scale on-premises servers. Business value is derived from the inference stage, where AI tools generate actionable information for users. Generative AI is like a knowledgeable and well-intentioned intern; someone more senior must ensure AI is given good instructions and check their work. In production, grounding and guard rails are vital to keep your AI an asset, not a liability.

Network Engineers are Facing an Identity Crisis

Network engineers are the firefighters and knowledge bases of enterprise IT, however the role of a network engineer is rapidly evolving. With the rise of automation, orchestration, and AI, the familiar image of an engineer hunched over a command-line interface (CLI) is giving way, leading many to question the future of their profession. In this episode, Tom Hollingsworth is joined by Ryan Harris, Chris Grundemann, and Nathan Nielsen as they discuss how the perception of their role has shifted, the continuous need for learning and adaptation, and whether the CLI is truly dead.

The conversation explores the challenges and opportunities presented by these technological advancements, highlighting how network engineers are embracing new tools like chatbots and GUIs for enhanced visualization. While some aspects of the job, like manual CLI work, may be diminishing, the core principles of understanding network functionality remain core to the role of the network engineer. The panel talks about identity crisis in a field where continuous learning is essential, contrasting it with professions like doctors and lawyers who deal with slower-changing fundamentals. They discuss the value of specialization versus being a generalist, the concept of the “pitchfork engineer,” and ultimately, how redefining their identity as lifelong learners can help network engineers thrive in this ever-changing landscape.

The DoJ Just Devalued Juniper Mist

The proposed remedies for the HPE acquisition of Juniper Networks did a real disservice to Juniper Mist. The confusion around what’s going on with the proposed Juniper AIOps for Mist auction have professionals asking a lot of questions. In this episode, recorded on the eve of the close of the acquisition, Tom Hollingsworth sits down with Sam Clements, Jake Snyder, and Ed Weadon to make sense of it all. There are discussions about what exactly is included in the auction and what benefit will come from the license to use Juniper AIOps for Mist. Also discussed is who might be a good bidder for the solution and how long it will take for them to get any real value from it.

Enterprises Shouldn’t Be Outsourcing Their IT Anymore

Enterprise networks are complicated but outsourcing all of the operations team doesn’t lead to better outcomes. It’s important to remember that enterprise covers a wide range of network definitions. In this episode, Ed Weadon, Chris Grundemann, and Jody Lemoine join Tom Hollingsworth as they discuss how businesses see the network and IT in general as a cost center instead of value generation. They also talk about the various sizes of networks and why each of them has issues with the most popular outsourcing methods. They also discuss the human factor and why not all managed providers can give you the same level of service.

MLO is a Lie

One of the most anticipated features of Wi-Fi 7 isn’t ready for the public. Worse yet, it may never deliver on the promise of fast, reliable wireless connectivity. In this episode, Tom Hollingsworth is joined by Allyn Crowe, Peter Mackenzie, and Chris Reed as they discuss the way that multi-link operation (MLO) has been included in the specification for Wi-Fi 7 yet not quite implemented. They highlight the technical difficulties of deploying such a complicated protocol and how vendors are trying to squeeze every drop of performance out of their hardware. They wrap up with advice on whether or not to plan your next deployment around a technology that isn’t quite ready yet.