Tech Field Day Podcast

Learn more about AI Field Day here.

The massive promises surrounding artificial intelligence are just history repeating itself.

In this episode of the Tech Field Day Podcast recorded on-site at AI Field Day 8, host Stephen Foskett is joined by Jim Czuprynski, Kate Scarcella, and Jeff Ello to debate the explosive world of AI hype.

They compare the current generative AI boom to past tech cycles like the dot-com era and early cloud computing. Together, they break down the brutal financial realities of a trillion-dollar AI infrastructure investment, dropping software precision, and the truth behind Large Language Models versus traditional machine learning.

Panelists:

Jim Czuprynski, Chief Storyteller at Zero Defect Computing

Jeff Ello, Head of AI at Purdue University

Kate Scarcella, Chair of CD Foundation

Hosts:

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Learn more about AI Infrastructure Field Day 5 here.

Think your expensive GPUs are the biggest factor in AI performance? Think again. Without a high-performance data storage strategy to keep them supplied with data, your AI infrastructure can become an expensive machine sitting idle. In this episode of the Tech Field Day Podcast, host Alastair Cooke is joined by industry experts Barton George and Ron Pagani Jr. to discuss the industry’s shift from data-intensive AI training to fast, transaction-heavy inference workloads and how data gravity is forcing organizations to rethink where they place data, caches, and compute resources. They also examine rising DRAM and SSD costs, the challenges of deploying Small Language Models (SLMs) at the edge, and the growing need for security and governance as autonomous AI agents become more common in enterprise environments.

Panelists:

Barton George, Founder of 808 Labs

Ron Pagani Jr., Founder of Open Technology Partners

Hosts:

⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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Learn more about Tech Field Day at Cisco Live US here.

Is the AI tech bubble about to burst just like the dot-com boom did?

On this episode of the Tech Field Day Podcast ahead of Cisco Live 2026, host Tom Hollingsworth and experts Sam Clements, Ed Weadon, and Rob Coote look at the real state of enterprise AI.

They discuss why tech giants are facing layoffs despite record profits, and whether companies should stick to selling hardware infrastructure instead of forcing useless AI chatbots into everything. The panel compares today's AI hype to past tech trends, looking closely at rising token costs and heavy investor pressure. Watch to find out why betting your entire business strategy on unproven AI features might be a huge mistake for your organization.

Panelists:

Sam Clements, Technical Solutions Architect

Ed Weadon, Senior Network Engineer

Rob Coote, Director, Cybersecurity and Infrastructure

Hosts:

⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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Learn more about Mobility Field Day here.

AI is changing the way we maintain and troubleshoot networks, offering suggested fixes and knowledge about issues. But we aren’t ready to trust it in fully autonomous mode yet.

In this episode of the Tech Field Day Podcast, Dan Ryan, Chris Reed, and Alan Wang join Tom Hollingsworth on-site at Mobility Field Day to discuss why fully autonomous networking still feels out of reach despite rapid advances in AI. The group explores the tension between deterministic networking protocols like OSPF and BGP and the non-deterministic nature of LLMs, noting that while AI excels at parsing data and suggesting fixes, it often lacks the business context needed to distinguish real problems from expected anomalies.

They also raise concerns about a growing skills gap, arguing that overreliance on AI for Tier 1 and Tier 2 troubleshooting could prevent junior engineers from developing the deep expertise needed to validate AI-generated recommendations. Ultimately, the delegates agree that networking still requires a human-in-the-loop approach, with AI best suited for guided troubleshooting, scripting, and low-risk operational tasks rather than fully autonomous control.

Panelists:

Chris Reed, Principal Consultant

Alan Wang, Networking Analyst

Dan Ryan, Principal Solution Architect at Connection

Hosts:

⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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AI networking is quickly becoming a critical part of the enterprise. You need make the right choice about which hardware you want to use but you aren’t necessarily locked into a single choice. In this episode of the Tech Field Day podcast, brought to you by Cisco, Tom Hollingsworth is joined by Scott Robohn and Richard Licon of Cisco as they discuss rapidly evolving landscape of AI networking, emphasizing that organizations no longer have to settle for a “one-size-fits-all” approach. They explore the shift from purely software-driven innovation back to high-performance hardware, where custom silicon like Cisco Silicon One and merchant silicon are becoming central to infrastructure. The conversation highlights how the transition from AI model training to real-time inferencing in 2026 demands more flexible and programmable hardware pipelines. By leveraging tools like P4 programming, network engineers can now adjust their infrastructure mid-cycle to optimize traffic patterns and ensure consistent job completion times as workload needs shift.

The discussion also highlights Cisco’s strategic partnership with NVIDIA, offering customers a choice between distinct networking ecosystems based on their specific goals. For those requiring strict adherence to NVIDIA’s validated designs and the Secure AI Factory, the Cisco Nexus 9100 with Spectrum-X silicon provides a certified, high-performance path. Conversely, organizations seeking maximum flexibility and custom tuning for diverse workloads can opt for Cisco Silicon One. Ultimately, the experts agree that while the technical requirements of AI networking are increasingly complex, the availability of diverse silicon options and consistent operating systems like NX-OS or SONiC allows enterprises to build future-proof, composable infrastructure that can adapt to the unpredictable pace of AI development.

Panelists:

Richard Licon, Principal Technical Marketing Engineer at Cisco

⁠Scott Robohn⁠, Founder and CEO, Solutional

Hosts:

⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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Learn More about AI Field Day 8 here.

Now that AI has enabled us to have an unlimited amount of content, generated on demand and instantly, we find ourselves questioning the quality of the output.

This episode of the Tech Field Day podcast, recorded prior to AI Field Day by delegates Barbara Roos, Guy Currier, Dave Graham, and Stephen Foskett, considers this common trade-off.

Large Language Models are fundamentally personal and responsive, delivering an answer that is statistically matched to your query. This can lead users astray, as a chatbot confidently answers every question regardless of insight.

These systems are best when paired with human domain expertise and fed quality data, but they are often starved of context.

Panelists:

Guy Currier, Research Director and Analyst at The Futurum Group

Barbara Roos, Founder and Principal Consultant at Trailhead Communications

Dave Graham, Head of Marketing at MLCommons

Hosts:

⁠⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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Learn more about Mobility Field Day 14 here.

AI is everywhere in networking right now, but the reality doesn’t always match the marketing. In this episode of the Tech Field Day Podcast ahead of Mobility Field Day, Tom Hollingsworth is joined by Jennifer Huber and Megan Sorensen to break down what “AI-driven networks” actually mean in practice, where vendors are positioning AI across wireless, automation, and operations, and where those claims start to fall apart.

They discuss into what AI is genuinely good at today, from site surveys to optimization and operations, while calling out its limits, especially around troubleshooting unknown issues and working with poor data. The key takeaway is simple: AI is only as good as the data behind it. Instead of buying into the hype, this conversation focuses on where AI is delivering real value now and how to approach it with realistic expectations.

Megan Sorensen, Networking Engineer

Jennifer Huber, Founder of Huber Works B.V.

Hosts:

⁠⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

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Learn more about Security Field Day 15 here.

Is Mythos the future of cybersecurity, or just the latest AI hype cycle? In this episode of the Tech Field Day Podcast leading into Security Field Day, host Tom Hollingsworth is joined by Jack Poller, Karen Lopez, and Brett Wolmarans to break down the truth behind Anthropic Mythos model. The panel digs into whether Mythos is truly a breakthrough in vulnerability scanning or simply overhyped, comparing its capabilities to tools like Claude Sonnet.

From exploit chaining and real-world vulnerabilities to the growing role of AI in development and security workflows, the discussion highlights both the promise and limitations of AI-driven security tools. The episode also explores how organizations should approach AI adoption, emphasizing practical strategies, developer awareness, and the importance of not relying on any single tool.

As AI continues to evolve, this conversation offers a grounded look at what actually matters for securing modern environments.

Panelists:

Jack Poller, Principal Analyst at Paradigm Technica

Karen Lopez, Senior Project Manager and Architect, InfoAdvisors

Brett Wolmarans, Staff Solutions Engineer at KONG

Hosts:

⁠⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Follow ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more information on upcoming and current event coverage ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠visit our website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Learn more about ⁠Networking Field Day 40 here⁠.

AI networking is driving innovation in the market like no other time in history. But the likelihood of all these advances filtering down into the enterprise is very slim. In this episode of the Tech Field Day Podcast, host Tom Hollingsworth and a panel of IT experts debate whether high-performance AI networking will ever truly penetrate the traditional enterprise. The discussion centers on the premise that the specialized, low-latency fabrics and ultra-high-speed Ethernet modules (like 800GbE) may be overkill for the average organization. While Ethernet continues to evolve to meet these demands, they question if the typical enterprise workload, primarily driven by human users rather than GPU clusters, actually requires the “trickery” of distributed flows and SmartNICs.

The conversation shifts toward the practicalities of adoption, highlighting that while the technology exists, its integration into the enterprise is often limited by physical constraints like power, cooling, and the lack of a killer app. However, the guests suggest that AI networking might arrive in smaller, rack-optimized pods or self-contained black boxes as companies begin to train private models on their own sovereign data. Ultimately, the experts advise that while engineering teams must become literate in high-performance computing, organizations should be wary of over-provisioning for a future they may not yet need, lest their expensive high-speed infrastructure ends up collecting dust.

Panelists:

Jeff Ello, Head of AI at Purdue University

Mike Witte, World Wide Technologies

Vincent Celindro, Director of Strategic Sales & Technology at Quantum Foundry

Hosts:

⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Follow ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more information on upcoming and current event coverage ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠visit our website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Learn more about IBM Watsonx here.

Keeping your AI applications waiting for data is not a technical problem; AI agents can help deliver the right data. This episode of the Tech Field Day podcast features Stephanie Valarezo from IBM, who discusses Agentic data enablement with Karen Lopez, Jim Czuprynski, and Alastair Cooke. Organizations face many critical challenges in providing high-quality, secure, and well-governed data at scale for AI, especially agentic AI applications.

Beyond simply possessing data, the challenges include managing vast, disparate data sources across hybrid environments, ensuring rapid access, and building trust through robust data governance. IBM's Watsonx is presented as a comprehensive data foundation with pillars in AI, Data, and Governance, offering composable products for data integration, quality, cataloging, and the creation of automated data products. Autonomous agents for repetitive data tasks will allow data professionals to concentrate on higher-value activities such as architecture, policy design, and security. Ultimately, enabling organizations to build scalable, automated, and well-governed data ecosystems for their AI initiatives.

IBM Representative: Stephanie Valarezo, Program Director, Product at IBM

Panelists:

Karen Lopez, Senior Project Manager and Architect, InfoAdvisors

Jim Czuprynski, Chief Storyteller at Zero Defect Computing

Hosts:

⁠⁠⁠⁠⁠⁠Tom Hollingsworth⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead for Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Alastair Cooke⁠⁠⁠⁠⁠⁠⁠⁠, Event Lead at Tech Field Day

⁠⁠⁠⁠⁠⁠⁠Stephen Foskett⁠⁠⁠⁠⁠⁠⁠⁠, President and Organizer of ⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠

Follow the Tech Field Day Podcast ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and use the Hashtag #TFDPodcast to join the discussion. Listen to more episodes ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on the podcast page of the website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

Follow ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Tech Field Day⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ for more information on upcoming and current event coverage ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on X/Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on Bluesky⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠on LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠, or ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠visit our website⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.