The Deep Edge Podcast

Ray Mota

The Deep Edge Podcast discusses technologies powering a cloud-native, fully connected world: Virtual and physical compute; virtual and physical networking; orchestration; mobile/wireless, wired; Internet of things; NFV; SDN; routing and switching; optical; cable; and hyper-scalers. We deliver the skills, insights, and materials to help our subscribers master their own transformations.

  1. 1d ago

    Starbucks has recently pulled the plug on their AI inventory tool, after just 9 months in 11,000+ shops. I Ep: 72

    Starbucks has recently pulled the plug on their AI inventory tool, after just 9 months in 11,000+ shops. The bigger lesson for me is simple: AI cannot solve an operations problem it does not understand. The technology was designed to utilize computer vision and spatial intelligence to count inventories faster and more precisely. On paper it sounds powerful. But in the real world, it apparently confused products, failed to find items on shelves, and made stockout concerns worse, not better. This is not a Starbucks problem. It’s a larger lesson for enterprise AI. Many firms are trying to expand AI without even understanding the operational challenge, the workflow, the human behavior and execution environment. AI doesn’t instantly produce process discipline. It magnifies the quality, or the fragility, of the underlying operational model. Some major take-aways: Speed is not preparation. Scaling AI to thousands of locations fast might seem daring, but success in the pilot does not always translate to success in production. AI requires operational context. If the fundamental cause is supply chain consistency, replenishment timeliness, store level execution, or process variation, then counting faster is not the issue. Frontline feedback is important. The failure sites are commonly seen by employees closest to the work. That signal is ignored, delaying adjustment and increasing risk. The design of the integration is as crucial as the AI model. Enterprise AI success isn’t about claims of accuracy. It’s about workflow fit, process reform, data quality, governance, training and adoption. Enterprise AI’s biggest danger isn’t the adoption. Scaling prematurely without properly diagnosing the business and operational problem. AI is powerful, but we need to relate it to the realities of how work really gets done.” What’s your take: are corporations rushing too fast to implement AI before they properly grasp the operational difficulties they are seeking to solve? #AI #EnterpriseAI #DigitalTransformation #RetailTech #SupplyChain #Operations #TechLeadership

    7 min

  2. Apr 14

    The Economics of AI Infrastructure: From Network Cost to Capital Return I Ep: 71

    In this episode of The Deep Edge Podcast, Ray Mota breaks down one of the most important questions facing network architects, CTOs, and business leaders building next-generation AI data centers: how to make the right infrastructure investment decisions with real confidence. Ray explains why the economics of AI data centers are fundamentally different from traditional enterprise networks. In the AI era, the biggest investment is often the GPU cluster, and the network’s role is no longer just to provide connectivity. Its job is to keep high-value GPU resources fully utilized. When the network underperforms, the result is not just lower performance. It can mean lost revenue, delayed service delivery, and direct destruction of capital efficiency. The episode explores why financial modeling tools such as economic digital twins are becoming essential for planning AI infrastructure. Ray also outlines the critical questions every organization should quantify before committing capital, including the cost of GPU idle time, the CapEx-to-OpEx tradeoffs of different architectures, and the break-even point for transport decisions under varying growth scenarios. This is a practical and executive-level discussion on why AI infrastructure decisions must now be guided by modeled economics, not vendor slides.

    4 min
  3. Cisco’s AI Networking Future: Will Eatherton on Silicon One, SONiC & Next-Gen Data CentersI Ep: 70

    12/01/2025

    Cisco’s AI Networking Future: Will Eatherton on Silicon One, SONiC & Next-Gen Data CentersI Ep: 70

    In this episode of The Deep Edge Podcast, host Ray Mota, Ph.D. speaks with Will Eatherton, Cisco’s engineering leader driving the future of AI-optimized networking. They dive deep into:  • Cisco’s AI-ready data center strategy  • Silicon One evolution & optical innovation  • Adaptive routing, congestion control & GPU fabric design  • Cisco + NVIDIA partnership and what it means for AI clusters  • SONiC openness, multi-cloud integration & operational simplification  • HyperFabric, LPO/CPO optics, and the shift from training to inference at scale Video link: https://youtu.be/39X2-BIL9sE WIll's Bio: As the SVP of the Data Center, Internet & Cloud Infrastructure Engineering team, Will leads a wide-ranging group responsible for data center, web, and service provider solutions. This group encompasses cutting-edge technologies, longstanding Cisco product lines, and the recently launched Cisco 8000 series. Will initially joined Cisco in 2000 with the acquisition of Growth Networks. During his early years at Cisco, Will expanded his expertise in routing systems architecture and co-authored several patents on packet processing. In 2013, Will co-founded Skyport Systems, a cloud technology pioneer addressing industry gaps in cloud-managed secure virtualized systems. In 2018, Will returned to Cisco with the acquisition of Skyport Systems. With his return, Will has led the Cisco Networking Engineering team, bringing with him a wealth of industry knowledge and experience. Will is an active technology researcher, author, and speaker. His most recent speaking engagements include sessions on high-performance ethernet fabrics for AI infrastructure and enabling enterprise generative AI with ethernet AI networking. Will has a Master’s degree in Electrical Engineering from Washington University in St. Louis, MO, and a Bachelor’s in Electric Engineering from the Missouri University of Science and Technology.

    42 min
  4. The Hidden Economics of Your Netflix Stream I Ep: 69

    08/25/2025

    The Hidden Economics of Your Netflix Stream I Ep: 69

    I use AI to create this podcast, let me know what you think? The ACG Research study highlights how application-driven traffic is reshaping the economics of fixed and mobile networks. While fixed networks benefit from lower unit costs ($0.06/GB vs. $0.33/GB for mobile), far higher household data consumption drives a 393% higher TCO per subscriber ($21.22 vs. $5.40). A small set of applications accounts for the vast majority of costs: 9 apps drive 92% of fixed expenses and seven drive 96% of mobile led by YouTube, Netflix, TikTok, Facebook, and Steam. Cost burdens are concentrated in the access layer for fixed networks (75% of TCO) and in the RAN for mobile (85%), underscoring structural vulnerabilities as video, gaming, and latency-sensitive applications proliferate. For CSPs, these dynamics create rising margin pressure, which are exacerbated by OTT players that capture revenue while operators absorb infrastructure costs. To respond, CSPs must adopt application-aware traffic management to optimize QoE and defer CapEx, pursue commercial or regulatory frameworks to rebalance costs with OTT providers, and deploy CSP specific TCO models to guide investment and policy strategies. Sustaining profitability in an application-centric era will depend on combining smarter traffic engineering, fairer cost sharing, and tailored economic modeling. Download report: https://www.acgcc.com/reports/the-economics-of-application-traffic-tco-benchmark/  For more information, contact Ray Mota or Peter Fetterolf.

    5 min
  5. Mplify’s Bold Rebrand & the Future of Network-as-a-Service w/Kevin Vachon | Ep68

    07/29/2025

    Mplify’s Bold Rebrand & the Future of Network-as-a-Service w/Kevin Vachon | Ep68

    Join Ray Mota, CEO of ACG Research and host of the Deep Edge Podcast, for an in-depth conversation with Kevin Vachon, of Mplify (formerly the MEF). In this episode, Kevin walks us through:  • The Story Behind the Rebrand: Why “Mplify” was chosen, how market shifts toward multi-cloud, AI, and automation drove the decision, and the legacy of LSO and network standardization.  • Building a Global NaaS Ecosystem: Strategies for fostering collaboration among service providers, vendors, hyperscalers, data-center operators, and enterprise customers—plus the engagement models that make it all work.  • Certifications & Interoperability: How trusted transparency and standardized APIs reduce risk, boost confidence, and drive real interoperability across layer-2, APIs, and beyond.  • Networks for AI vs. AI for Networks: Clarifying where Mplify plays in enabling AI-centric use cases, from on-demand GPU services to elastic bandwidth and consumption-based models.  • Inside the Global NaaS Event (GNE) 2025: What to expect at this year’s Dallas gathering—real demos, rapid-fire user stories, business-value case studies, and deep dives into next-generation NaaS capabilities. LinkedIn: https://www.linkedin.com/in/kevin-vachon-5675ab1/ Kevin's bio https://www.mplify.net/people/kevin-vachon/ Mplify Board Link https://www.mplify.net/about-mplify/officers-board-of-directors/ #mplify #acgresearch #NaaS #LSO

    19 min
  6. Managing Cloud Costs with Matt Biringer of North Cloud | Ep67

    07/29/2025

    Managing Cloud Costs with Matt Biringer of North Cloud | Ep67

    Join host Ray Mota as he sits down with Matt Biringer, Co-Founder of North Cloud, to explore the evolving world of public cloud finance. In this episode, we dive into:  • Why cloud cost management matters – The shift from upfront data-center purchasing to utility-based billing and its impact on budgets.  • The rise of FinOps – How finance, engineering, and product teams can collaborate around cloud spend—and the cultural and political barriers they face.  • Visibility & automation – From 50-page invoices to real-time dashboards, and the AI-driven tools that right-size resources, alert on anomalies, and allocate costs automatically.  • Agent North: Cloud FinOps AI – A sneak peek at North Cloud’s upcoming “Agent North,” which ingests your billing telemetry and technical docs to answer finance and engineering questions in natural language.  • Security & governance – Balancing automation with safeguards, air-gaps, and scenario planning to keep your financial automation platform secure. About Matt Biringer Matt Biringer is the co-founder and CEO of North.Cloud, the AI-powered platform that helps companies cut cloud waste and control costs, without the spreadsheets. Before launching North in 2023 (literally from his garage), Matt spent 12 years selling datacenter technology, leading growth at Pure Storage, CDI, and SHI. When he’s not scaling North, you’ll find him chasing his kids, training jiu-jitsu, lifting weights, or perfecting a new recipe. He also angel invests in early-stage startups, backing companies like NodeECO, Light, Data Herald, and Pipedream Labs. Find Matt online:  LinkedIn https://www.linkedin.com/in/mattbiringer/ Twitter https://x.com/biringer_ About North.Cloud North.Cloud is an AI-powered cloud optimization platform tackling the rising costs and inefficiencies of modern cloud infrastructure. By eliminating manual FinOps processes and rigid cost models, North delivers real-time, automated savings across AWS and GCP. Its dynamic platform helps companies reduce waste, improve efficiency, and gain transparency over their cloud spend. To learn more,  visit North.Cloud https://www.north.cloud/

    34 min
  7. Stand with Dawit: Demand Fair Trial and Release for Ethiopia’s Visionary ISP Founder and US Citizen! Ep66

    05/01/2025

    Stand with Dawit: Demand Fair Trial and Release for Ethiopia’s Visionary ISP Founder and US Citizen! Ep66

    Call to Action to our Community!!! Join me in standing up for justice and digital inclusion—help secure a fair trial and release for Dawit, the visionary entrepreneur detained in Ethiopia. Share his story, sign the petition, and urge your representatives to act. Today I’m spotlighting a colleague whose story demands our attention. Dawit, an American citizen and former Cisco leader, left a lucrative career in the U.S. to found Ethiopia’s first private ISP—bringing high-speed internet to 400,000 homes and empowering 110 direct employees (and hundreds more contractors). Since December 2024, Dawit has been held without bail in a maximum-security prison on financial charges that stem from an incomplete audit—and despite an appeal still pending, he remains denied basic rights and medical care.  Company assets are frozen, threatening not only his livelihood but the connectivity of thousands of Ethiopian citizens. When one of us faces injustice, we all do. The global tech community stands for innovation, progress, and fair treatment under the law. Here’s how you can help:  1. Raise awareness—share this post and use #FreeDawitBirhanu  2. Sign the petition for his release: https://chng.it/dJGpsJ99Xn  3. Contact your elected officials to advocate for U.S. diplomatic intervention  4. Engage industry associations to apply collective pressure Let’s unite our voices and ensure Dawit receives the fair trial he deserves—and that his vital work to bridge the digital divide can continue. Video Link: https://youtu.be/4ZV3GA-c-Uo

    48 min
  8. AI Hype vs Reality: Strategic Blind Spots, Big Bets & Leadership Lessons with Jamie Dobson | Ep65

    04/30/2025

    AI Hype vs Reality: Strategic Blind Spots, Big Bets & Leadership Lessons with Jamie Dobson | Ep65

    In this episode of The Deep Edge Podcast, ACG Research CEO Ray Mota sits down with Jamie Dobson—author of Visionaries, Rebels, and Machines and founder of Container Solutions—for a powerful, no-nonsense conversation on the hype, reality, and economic implications of AI. Together, they unpack how AI is reshaping corporate decision-making, exposing organizational blind spots, and challenging traditional innovation models. From Amara’s Law to strategic missteps, Jamie offers insight into why some enterprises move too fast with AI while others dangerously underestimate its long-term impact. With sharp analogies, war stories from the dot-com era, and lessons from the invention of the cloud, the discussion gives leaders a practical lens to approach AI—with no-regret moves, controlled experimentation, and an honest look at workforce readiness. This episode is a must-listen for business and tech leaders navigating AI’s promise—and its peril. ABOUT JAMIE DOBSON Jamie Dobson is the founder of Container Solutions, and has been helping companies, across industries, move to cloud native ways of working for over ten years. Container Solutions develops a strategy, a clear plan and step by step implementation helping companies achieve a smooth digital transformation. With services including Internal Developer Platform Enablement, Cloud Modernisation, DevOps/DevSecOps, Site Reliability Engineering (SRE) Consultancy, Cloud Optimisation and creating a full Cloud Native Strategy, companies get much more than just engineering know-how. Jamie is also author of ‘The Cloud Native Attitude’ available from Amazon and good bookstores and the soon to be published, ‘Visionaries, Rebels and Machines: The story of humanity’s extraordinary journey from electrification to cloudification’ Link to Jamie's book: https://www.amazon.co.uk/Visionaries-Rebels-Machines-electrification-cloudification/dp/1917490070/ref=sr_1_1?crid=1QZWBMJDKAQJL&dib=eyJ2IjoiMSJ9.PpJEN6zER2QaX8-xzxgf8w.W4uDXhOduj5D-NKmyu7yYfpyv4Q7u4t6dXHqOFb6VqY&dib_tag=se&keywords=visionaries+rebels+and+machines&qid=1745942577&sprefix=visionaries+%2Caps%2C84&sr=8-1 Video Link: https://youtu.be/lm3Q-3WvYFo

    51 min
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About

The Deep Edge Podcast discusses technologies powering a cloud-native, fully connected world: Virtual and physical compute; virtual and physical networking; orchestration; mobile/wireless, wired; Internet of things; NFV; SDN; routing and switching; optical; cable; and hyper-scalers. We deliver the skills, insights, and materials to help our subscribers master their own transformations.

Information

  • Creator
    Ray Mota
  • Years Active
    2020 - 2026
  • Episodes
    72
  • Rating
    Explicit
  • Copyright
    © 2026 The Deep Edge Podcast
  • Show Website
    The Deep Edge Podcast