Mistaking Quantity for Quality in Tech and Life - Tech Field Day Podcast
@TechFieldDay @TechFieldDayPod @SFoskett @GuyCurriersFeed @DaveGraham #TFDPodcast #AIFD8 #AI #AgenticAI #AIInfrastructure #AIAgents #AIQuality #DataQuality
#tfdpodcast — Public Fediverse posts
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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.
#TFDPodcast #AIFD8 #AI #AgenticAI #AIInfrastructure #AIAgents #AIQuality #DataQuality
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I love the things I get to learn about when I produce podcasts for work. AI, cybersecurity, networking, the way everything works. 🎧
https://youtu.be/ta8HcGfYyq4👉 Part of that is the Tech Field Day Podcast, one of the podcasts I produce for my job at Tech Field Day and The Futurum Group.
🎙️ In this episode, host Tom Hollingsworth, Jack Poller, Karen Lopez, & Brett Wolmarans break down the truth behind Anthropic Mythos model.
#TFDPodcast #XFD15 #Cybersecurity #Mythos #AISecurity #ClaudeSonnet
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Security goes beyond AI. Identity and user security are hot topics at this year’s RSAC Conference.
👉 https://youtu.be/t8yJxa0xG7o?si=yq-ZUPXD5uNzdq4R▶️ On the Tech Field Day Podcast, Tom Hollingsworth, Jack Poller, and Drew Conry-Murray discuss non-AI security trends—from identity-based and non-human users to securing the browser—and how AI may add future context.
#TFDPodcast #IdentitySecurity #Cybersecurity #EnterpriseSecurity
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#AIIFD4 #TFDPodcast Tech Field Day Podcast now online: Billion-Dollar AI Headlines Obscure Real Business Value
YouTube: https://youtu.be/h1MoZ8QRG-k?si=cJe79fUNRxdagBvr
Apple Podcasts: https://podcasts.apple.com/us/podcast/93-billion-dollar-ai-headlines-obscure-real-business-value/id1232389532?i=1000747868893
Spotify Podcasts: https://open.spotify.com/episode/3RidFYKUrhvQG0CzxHP7VZ?si=SvHtPCV8SeeF6k_mm63dew
Audio Landing Page: https://creators.spotify.com/pod/profile/techfielddaypodcast/episodes/93--Billion-Dollar-AI-Headlines-Obscure-Real-Business-Value-e3ei020
Website:https://techfieldday.com/2026/billion-dollar-ai-headlines-obscure-real-business-value/
LinkedIn: https://www.linkedin.com/feed/update/urn:li:activity:7424499759974985728
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Agentic AI Spells the End of Dial Twiddlers 🧠 🌐
ICYMI: Guy Currier, Jay Cuthrell, and Alastair Cooke discuss how infrastructure abstractions, GenAI, and business-as-code are reshaping the specialist roles who are used to “twiddling the dials.”
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Agentic AI Spells the End of Dial Twiddlers 🧠 🌐
Guy Currier, Jay Cuthrell, and Alastair Cooke discuss how infrastructure abstractions, GenAI, and business-as-code are reshaping the specialist roles who are used to “twiddling the dials.”
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Listen to the #TFDPodcast on the go on all major podcast apps 🎧 ➡️ https://podcasters.spotify.com/pod/show/techfielddaypodcast
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Network Engineers are Facing an Identity Crisis 🔸 🔌 🎧
NEW ▶️ https://youtu.be/nTTHMCWiMG8?feature=shared
In this episode, Tom Hollingsworth talks with Ryan Harris, Chris Grundemann, and Nathan Nielsen about how the evolving role of Network Engineers and if the CLI is really dead.
@techfieldday @networkingnerd #tfdpodcast #nfd38 #networkengineering #networking #ai
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Was on the @TechFieldDayPod talking abt the upcoming SHARE conference. Mainframe is AI. The new @IBM z17 will show how the two can merge together. Walk into a store and they know what you need? Get on an airplane without issue?
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From Tech Field Day - Networking Field Day 38 7/9-7/10:
NEW: Enterprises Shouldn't Be Outsourcing Their IT Anymore 🎧🎙️
Watch ➡️ buff.ly/aFsxzaB
Enterprise networks are complex and fully outsourcing ops doesn’t always guarantee better results.
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Data Infrastructure Is A Lot More Than Storage
The rise of AI and the importance of data to modern businesses has driven us too recognize that data matters, not storage. This episode of the Tech Field Day podcast focuses on AI data infrastructure and features Camberley Bates, Andy Banta, David Klee, and host Stephen Foskett, all of whom will be attending our AI Data Infrastructure Field Day this week. We’ve known for decades that storage solutions must provide the right access method for applications, not just performance, capacity, and reliability. Today’s enterprise storage solutions have specialized data services and interfaces to enable AI workloads, even as capacity has been driven beyond what we’ve seen in the past. Power and cooling is another critical element, since AI systems are optimized to make the most of expensive GPUs and accelerators. AI also requires extensive preparation and organization of data as well as traceability and records of metadata for compliance and reproducibility. Another question is interfaces, with modern storage turning to object stores or even vector database interfaces rather than traditional block and file. AI is driving a profound transformation of storage and data.
Infrastructure Beyond Storage
The rise of AI has fundamentally shifted the way we think about data infrastructure. Historically, storage was the primary focus, with businesses and IT professionals concerned about performance, capacity, and reliability. However, as AI becomes more integral to modern business operations, it’s clear that data infrastructure is about much more than just storage. The focus has shifted from simply storing data to managing, accessing, and utilizing it in ways that support AI workloads and other advanced applications.
One of the key realizations is that storage, in and of itself, is not the end goal. Data is what matters. Storage is merely a means to an end, a place to put data so that it can be accessed and used effectively. This shift in perspective has been driven by the increasing complexity of AI workloads, which require not just vast amounts of data but also the ability to access and process that data in real-time or near real-time. AI systems are highly dependent on the right data being available at the right time, and this has led to a rethinking of how data infrastructure is designed and implemented.
In the past, storage systems were often designed with a one-size-fits-all approach. Whether you were running a database, a data warehouse, or a simple file system, the storage system was largely the same. But AI has changed that. AI workloads are highly specialized, and they require storage systems that are equally specialized. For example, AI systems often need to access large datasets quickly, which means that traditional storage systems that rely on spinning disks or even slower SSDs may not be sufficient. Instead, AI systems are increasingly turning to high-performance storage solutions that can deliver the necessary bandwidth and low latency.
Moreover, AI workloads often require specialized data services that go beyond simple storage. These include things like data replication, data reduction, and cybersecurity features. AI systems also need to be able to classify and organize data in ways that make it easy to access and use. This is where metadata management becomes critical. AI systems need to be able to track not just the data itself but also the context in which that data was created and used. This is especially important for compliance and reproducibility, as AI systems are often used in regulated industries where traceability is a legal requirement.
Another important aspect of AI data infrastructure is the interface between the storage system and the AI system. Traditional storage systems often relied on block or file-based interfaces, but AI systems are increasingly turning to object storage or even more specialized interfaces like vector databases. These new interfaces are better suited to the needs of AI workloads, which often involve large, unstructured datasets that need to be accessed in non-linear ways.
Power and cooling are also critical considerations in AI data infrastructure. AI systems are highly resource-intensive, particularly when it comes to GPUs and other accelerators. These systems generate a lot of heat and consume a lot of power, which means that the data infrastructure supporting them needs to be optimized for energy efficiency. This has led to a shift away from traditional spinning disks, which consume a lot of power, and towards more energy-efficient storage solutions like SSDs and even tape for long-term storage.
The rise of AI has also blurred the lines between storage and memory. With the advent of technologies like CXL (Compute Express Link), the distinction between memory and storage is becoming less clear. AI systems often need to access data so quickly that traditional storage solutions are not fast enough. In these cases, data is often stored in memory, which offers much faster access times. However, memory is also more expensive and less persistent than traditional storage, which means that data infrastructure needs to be able to balance these competing demands.
In addition to the technical challenges, AI data infrastructure also needs to address the growing need for traceability and compliance. As AI systems are increasingly used to make decisions that impact people’s lives, whether in healthcare, finance, or other industries, there is a growing need to be able to trace how those decisions were made. This requires not just storing the data that was used to train the AI system but also keeping detailed records of how that data was processed and used. This is where metadata management becomes critical, as it allows organizations to track the entire lifecycle of the data used in their AI systems.
In conclusion, AI is driving a profound transformation in the way we think about data infrastructure. Storage is no longer just about performance, capacity, and reliability. It’s about managing data in ways that support the unique needs of AI workloads. This includes everything from specialized data services and interfaces to energy-efficient storage solutions and advanced metadata management. As AI continues to evolve, so too will the data infrastructure that supports it, and organizations that can adapt to these changes will be well-positioned to take advantage of the opportunities that AI presents.
Apple Podcasts | Spotify | Overcast | Amazon Music | YouTube Music | Audio
Learn more about AI Data Infrastructure Field Day 1 on the Tech Field Day website. Watch the event live on LinkedIn or on Techstrong TV.
Podcast Information:
Stephen Foskett is the Organizer of the Tech Field Day Event Series, now part of The Futurum Group. Connect with Stephen on LinkedIn or on X/Twitter.
Camberley Bates is the VP and Practice Lead at The Futurum Group. You can connect with Camberley on LinkedIn and her podcast Infrastructure Matters through The Futurum Group.
Andy Banta is a consultant at MagnitionIO and a storage expert promoting simplicity and economy. You can connect with Andy on X/Twitter or on LinkedIn. Learn more about Andy on his Substack.
David Klee is the Founder at Heraflux Technologies. You can connect with David on X/Twitter or on LinkedIn. Learn more about David on his personal website or about Heraflux Technologies on their website.
Thank you for listening to this episode of the Tech Field Day Podcast. If you enjoyed the discussion, please remember to subscribe on YouTube or your favorite podcast application so you don’t miss an episode and do give us a rating and a review. This podcast was brought to you by Tech Field Day, home of IT experts from across the enterprise, now part of The Futurum Group.
#AI #AIDIFD1 #TFDPodcast #Andybanta #CamberleyB #KleeGeek #SFoskett #TechFieldDay #TechstrongTV #TheFuturuemGroup
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Just Posted: Tom Hollingsworth discusses the evolution of network engineering, highlighting its ongoing relevance despite shifts in industry interest. @networkingnerd #Networking #NFD35 #TFDPodcast
https://gestaltit.com/podcast/tom/network-engineering-is-a-dying-profession/ -
#SymLink: Open-source platforms and managed services help small businesses modernize applications affordably and efficiently. @GestaltIT @sfoskett #ADFD1 #TFDPodcast
https://gestaltit.com/podcast/stephen/open-source-helps-small-businesses-modernize-applications/ -
Just Posted: Tom Hollingsworth discusses the need for on-premises networks to adopt cloud models to efficiently manage specialized applications and AI. @networkingnerd #Networking #NFD35 #TFDPodcast
https://gestaltit.com/podcast/tom/on-premises-networks-need-to-work-like-cloud-networks/ -
#SymLink: Stephen Foskett and colleagues discuss the ubiquity and evolution of cloud computing, emphasizing its broad but sometimes inaccurately broad application. @GestaltIT @sfoskett #CFD20 #Cloud #TFDPodcast
https://gestaltit.com/podcast/stephen/everything-is-the-cloud-and-the-cloud-is-everything/ -
Just Posted: Tom Hollingsworth discusses the advantages of private 5G in enterprises, highlighting its suitability for challenging and regulated environments. @networkingnerd #ArubaAtmosphere #NFDx #TFDPodcast
https://gestaltit.com/podcast/tom/its-time-for-private-5g-in-the-enterprise/ -
#SymLink: The term "cloud native" has evolved from describing applications designed for cloud to now commonly referring to containerized applications. @GestaltIT @sfoskett #CFD20 #TFDPodcast
https://gestaltit.com/podcast/stephen/cloud-native-is-just-a-marketing-term/ -
Just Posted: Tom Hollingsworth discusses with Evan Mintzer and Jody Lemoine how AI, like past tech trends, needs strategic implementation to avoid the pitfalls of hype. @networkingnerd #CiscoLive24 #TFDPodcast #TFDx
https://gestaltit.com/podcast/tom/ai-is-the-new-blockchain/ -
#SymLink: The Tech Field Day podcast emphasized the importance of integrating DevSecOps from the start of application development to ensure robust security. @GestaltIT @sfoskett #ADFD1 #appdev #TFDPodcast
https://gestaltit.com/podcast/stephen/application-modernization-requires-good-security-practices/ -
#SymLink: Platform engineering merges with DevOps to balance innovation and control, fostering development efficiency and operational standardization. @GestaltIT @sfoskett #ITOperations #PlatformEngineering #TFDPodcast
https://gestaltit.com/podcast/stephen/platform-engineering-is-the-revenge-of-it-operations/ -
Just Posted: Tom Hollingsworth and experts discuss Wi-Fi 7's limitations in adapting to evolving user needs and technology advancements on Gestalt IT. @networkingnerd #MFD11 #TFDPodcast #WiFi7
https://gestaltit.com/podcast/tom/wi-fi-7-isnt-enough-for-future-wireless-needs/ -
#SymLink: Stephen Foskett discusses the critical role of data quality in AI success with Drew Clarke from Qlik on the Tech Field Day podcast. @GestaltIT @sfoskett #AI #QlikConnect #Sponsored #TFDPodcast
https://gestaltit.com/podcast/spotlight/stephen/data-quality-is-more-important-than-ever-in-an-ai-world-with-qlik/ -
Data Quality is More Important Than Ever in an AI World with Qlik
In our AI-dominated world, data quality is the key to building useful tools. This episode of the Tech Field Day podcast features Drew Clarke from Qlik discussing best practiced for integrating data sources with AI models with Joey D’Antoni, Gina Rosenthal, and Stephen Foskett before Qlik Connect in Orlando. Although there is a lot of hype about AI in industry, companies are realizing the risks of generative AI and large language models as well. Solid data practices in terms of data hygiene, proven data models, business intelligence, and flows can ensure that the output of an AI application is correct. The proliferation of Generative AI is also causing a rapid increase in the cost and environmental impact IT systems and this will impact the success of this technology. Good data practices can help, allowing a lighter and less expensive LLM to produce quality results. The Tech Field Day delegates will learn more about these topics at Qlik Connect in Orlando, and we will be recording and sharing content as well.
This Spotlight Podcast is Brought to You by QlikApple Podcasts | Spotify | Overcast | Amazon Music | YouTube Music | Audio
As AI technologies like generative AI and large language models continue to appear, the foundation upon which these technologies are built – data – becomes the linchpin of their success. This episode of the Tech Field Day podcast features a discussion with Drew Clarke from Qlik, alongside industry experts Joey D’Antoni, Gina Rosenthal, and Stephen Foskett. Ahead of Qlik Connect in Orlando, the panel discussed the best practices for integrating data sources with AI models, underlining the importance of data quality in an AI-dominated world.
The proliferation of AI technologies has brought with it an increased awareness of the potential risks associated with generative AI and LLMs. As companies venture into the realm of AI, the realization that not all AI is capable of delivering accurate or useful outcomes has become apparent. This acknowledgment has brought traditional data practices such as data hygiene, data quality, proven data models, business intelligence, and data flows into the spotlight. These practices ensure that the output of an AI application is correct and reliable.
One of the critical challenges is the integration of data into LLMs and small language models. We consider metadata, data security, and the implications of regulations like GDPR and the California Data Privacy Act on data integration with AI models. It is critical to consider data privacy and to avoid exposing private data as companies integrating data into their AI models.
We should also consider societal and environmental impacts of the rapid increase in the use of AI as well as the cost of inferencing. The environmental footprint of data centers, driven by the energy and water consumption required to support AI computations, is a particular area of concern. This underscores the need for good data practices that not only ensure the quality of AI outputs but also contribute to the sustainability of AI technologies.
Data is a key product in an AI world, and we must treat data with the same care and consideration as we do in conventional applications. This involves curating, managing, and continuously improving data to ensure its quality and relevance. Data engineers and business analysts play a key role in enhancing productivity and effectiveness of AI capabilities.
This discussion is a reminder of the critical importance of data quality in the age of AI. As companies navigate the complexities of integrating AI into their operations, the foundational principles of data hygiene, data quality, and proven data models remain as relevant as ever. We look forward to discussing these themes at Qlik Connect in June, and invite our audience to attend the event!
Visit the Qlik Connect official website for more information and registration.
Podcast Information:
Stephen Foskett is the Organizer of the Tech Field Day Event Series, now part of The Futurum Group. Connect with Stephen on LinkedIn or on X/Twitter.
Gina Rosenthal, Founder and CEO of Digital Sunshine Solutions. You can connect with Gina on LinkedIn and listen to her podcast, The Tech Aunties Podcast. Learn more on her website.
Joey D’Antoni is a Principal Consultant at Denny Cherry & Associates Consulting. You can connect with Joey on LinkedIn, on Mastodon, and on X/Twitter or read more about him and his work on his website.
Drew Clarke is the General Manager & EVP of the Data Business Unit at Qlik. You can connect with Drew on LinkedIn and learn more about Qlik by visiting their website.
Thank you for listening to this episode of the Tech Field Day Podcast. If you enjoyed the discussion, please remember to subscribe on YouTube, Apple Podcasts, Spotify, or your favorite podcast application so you don’t miss an episode. Please do give us a rating and a review, it helps with discoverability. This podcast was brought to you by Tech Field Day, home of IT experts from across the enterprise, now part of The Futurum Group. For upcoming events and more episodes, head to the Tech Field Day website.
#AI #QlikConnect #Sponsored #TFDPodcast #GestaltIT #GMinks #JDAnton #Qlik #SFoskett #TechFieldDay #TechFieldDayPod
https://wp.me/p4YpUP-mfJ
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Just Posted: Tom Hollingsworth and guests discuss AI's potential in IT as a supplement to human expertise, highlighting its current limitations and the necessity for thoughtful integration into workflows. @networkingnerd #AI #NFD34 #TFDPodcast
https://gestaltit.com/podcast/tom/ai-is-smarter-than-your-average-network-engineer/ -
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.
#ColleenColl #Digi_Sunshine #FredericVHaren #SFoskett #TechFieldDay #TechFieldDayPod #AIFD4 #TFDPodcast Coverage
https://gestaltit.com/podcast/stephen/content-made-with-ai-is-obscuring-real-information/ -
There is a hazardous amount of AI-generated and SEO-oriented content being generated, and the solution is real stories from real communities #ColleenColl #Digi_Sunshine #FredericVHaren #SFoskett #TechFieldDay #TechFieldDayPod #AIFD4 #TFDPodcast Coverage https://gestaltit.com/podcast/stephen/content-made-with-ai-is-obscuring-real-information/
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#SymLink: Stephen Foskett highlights the critical role of authentic community content in addressing the challenges posed by AI-generated and SEO-focused articles in the tech media landscape. @GestaltIT @sfoskett #AIFD4 #TFDPodcast
https://gestaltit.com/podcast/stephen/content-made-with-ai-is-obscuring-real-information/ -
The Tech Field Day Podcast returns! The name may change but the content and format are still the same. Read on to learn more about the history of the podcast and focus going forward with our new episodes.
#GestaltIT #NetworkingNerd #SFoskett #TechFieldDay #TFDPodcast Coverage
https://gestaltit.com/podcast/tom/reintroducing-the-tech-field-day-podcast/ -
The Tech Field Day Podcast returns! The name may change but the content and format are still the same #GestaltIT #NetworkingNerd #SFoskett #TechFieldDay #TFDPodcast Coverage https://gestaltit.com/podcast/tom/reintroducing-the-tech-field-day-podcast/