What's Up with Tech?

• If Identity Becomes Portable, Does Trust Become Universal?

  Interested in being a guest? Email us at [email protected] has become the entry ticket to the internet, and users are now choosing safety over price and speed. We sit down with Raj from Trua to dig into the 2025 Trust Survey and why verification has shifted from a nice-to-have to a must-have. From shocking stats on consumer expectations to the real reasons fear and fatigue are rewriting behavior, we map out what it takes to build platforms people will actually use—and pay for.We walk through the practical playbook: make safety the first thing users see, put verified badges and last-checked timestamps front and center, and adopt “friction by design” to deter bad actors without punishing good ones. Raj breaks down progressive checks that scale with risk—identity and address for low-stakes, licenses and criminal screens when necessary, and liveness for high-impact flows like dating and hiring. He explains why trust tech is emerging as its own category and how a reusable, tokenized credential can follow you across apps, slashing repeated data collection while boosting conversion and confidence.AI and deepfakes add urgency. With bots posing as people, human identity verification becomes essential for high-risk interactions, and continuous authentication helps separate real users from synthetic scams. We also explore the regulatory landscape, why co‑opting consumers is cheaper and more effective than piling on rules, and how brands like Apple translate privacy into loyalty. The gig economy emerges as the flash point: tens of millions move across platforms that need fast, safe onboarding and fewer data silos to breach.If you care about growth, retention, and brand resilience, now is the time to operationalize trust. Subscribe, share this episode with a product or security leader, and leave a review with one change you’ll make to bring safety to the surface.Inspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifySupport the showMore at https://linktr.ee/EvanKirstel

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• Cisco’s Incubation Engine For Agentic AI And Quantum Networking

  Interested in being a guest? Email us at [email protected] if the most human-feeling teammates on your projects moved at machine speed and collaborated across every vendor you use? We sit down with Vijoy Pandey is GM and Senior Vice President of Outshift to unpack how agentic AI and quantum networking move from shiny demos to dependable, scaled systems that actually ship results.We start by reframing innovation horizons around risk instead of time. Technology risk is where quantum lives today, with foundational challenges from hardware to protocol. Market risk is where agentic AI thrives, as teams test real enterprise use cases beyond coding assistants. Platform risk is the mandate for a company like Cisco: open, interoperable architectures instead of brittle point tools. That lens shapes everything OutShift builds.You’ll hear a clear blueprint for the Internet of Agents: discover the right capabilities across vendors, grant task and transaction-based access that expires fast, enable real-time many-to-many messaging across voice and video, and close the loop with rigorous measurement that feeds reputation and policy. We spotlight Agency (AGNTCY), the Linux Foundation–hosted open source project backed by a broad industry coalition, designed to make multi-agent collaboration portable and trustworthy.The proof shows up in production. A healthcare triage flow uses a Webex voice agent that coordinates with insurance and diagnostics agents to verify claims and route patients to the right human expert faster. In networking, a multi-agent pipeline built with Swisscom stress-tests configuration changes like a chess engine, exploring outcomes, generating tests, and catching cascading failures before they hit production. On the horizon, quantum networking becomes a scale-out fabric that links quantum computers, data centers, and sensing devices—accelerating timelines by five to ten years while delivering near-term classical benefits in security and precision.If you care about enterprise AI, open standards, and the road to quantum-ready infrastructure, this conversation maps the path from uncertainty to impact. Subscribe, share with a colleague who’s building with agents, and leave a review with the one capability you want most from an Internet of Agents.Inspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifySupport the showMore at https://linktr.ee/EvanKirstel

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• From Surveillance To Smarter Stores With AI

  Interested in being a guest? Email us at [email protected] don’t just record anymore—they inform, alert, and help teams act before problems get expensive. We sit down with Jeff Corrall Chief Product Officer at March Networks, to unpack how AI-powered video is evolving from security footage to real operational intelligence you can search, measure, and scale without ripping out legacy systems.Jeff explains why continuous video analysis is costly and how an image-first approach delivers the wins that matter. By capturing snapshots at set intervals or when simple edge analytics detect an event, their platform sends images to the cloud for deeper interpretation. That means retailers catch blocked fire exits before fines hit. Managers get texts when queues spike. Regional leaders track trends across hundreds of sites in real time. And teams can literally “Google” their stores for spills, cash left out, or outdated signage, fixing issues at the speed of a search.We also dig into the AI3 camera, a 360-degree device that blends people counting, queue monitoring, and traffic flow with traditional video, replacing multiple sensors with one scalable unit. Beyond retail, transit agencies pair passenger counts with payment data to spot revenue leakage, while banks audit promotional compliance by uploading an example poster and finding any branch where it’s still displayed. The near-term horizon is especially exciting: fusing point-of-sale data with AI triggers to calculate conversion, surface anomalies with visual proof, and notify the right person to take action—before customer experience or revenue suffer.If you care about operational excellence, loss prevention, and smarter use of your existing cameras, this conversation is packed with practical insights. Follow the show, share it with a colleague who owns store ops or security, and leave a quick review to tell us what you’d automate first.Support the showMore at https://linktr.ee/EvanKirstel

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• 5G To Autonomous: Making Networks Think

  Interested in being a guest? Email us at [email protected] if your network could understand intent, adapt in real time, and deliver the exact experience you need—whether you’re at a packed concert, inside an ambulance, or running a factory floor? We dive into the shift from manual engineering to autonomous networks and how open standards are making AI practical, measurable, and global.Claudia Muñiz, Global Head of Sales for Cognitive Network Solutions at Ericsson, explains why 5G’s real promise is differentiated connectivity and how the Service Management and Orchestration (SMO) layer unlocks it. We trace the journey from early self-organizing networks to an open RAN ecosystem where developers ship RAN apps once and deploy everywhere. Expect clear examples of digital twins and multi-objective reinforcement learning tuning antennas across massive configuration spaces, with live results: higher throughput, faster speeds, fewer dropped calls, and better spectral efficiency—proof that AI at the radio layer moves the needle when paired with the right data and processes.We also separate hype from reality on large language models in telco. Lightweight, energy-aware models handle millisecond decisions at the edge, while LLMs shine in cloud workflows, documentation, coding, and natural language operations. With partnerships that blend domain expertise and elastic compute, engineers can ask plain-English questions and get guided actions, all built on a unified, secure data layer. The conversation lands on what matters most: time-to-first value, measurable gains in churn, revenue, energy, and effort; and the near future of intent-based networking that coordinates specialized agents to meet business goals across open interfaces.If you care about 5G, open RAN, AI-driven operations, developer ecosystems, and the real-world path to autonomous networks, this is your roadmap. Subscribe, share with a colleague who lives in dashboards, and leave a review with the one question you want us to tackle next.Inspiring Tech Leaders - The Technology PodcastInterviews with Tech Leaders and insights on the latest emerging technology trends.Listen on: Apple Podcasts SpotifySupport the showMore at https://linktr.ee/EvanKirstel

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• How A Decentralized GPU Network Beats The Cloud On Price And Flexibility

  Interested in being a guest? Email us at [email protected] happens when thousands of retired Ethereum GPUs meet a tidal wave of AI demand? We sit down with Hidde Hoogland Founder at Decent to unpack how a former mining operation evolved into a decentralized edge provider and why connecting to Aethir’s GPU marketplace changed the math on utilization, cash flow, and scale. It’s a candid look at turning stranded hardware into a real business with clearer ROI targets and a pricing story that can undercut hyperscalers by 60–80 percent for many workloads.We trace the journey from proof-of-work mining to a three-part operating model: sourcing hardware directly from vendors, hosting and maintaining systems, and owning the facility layer. Hine explains how decentralized GPU-as-a-service works for both sides of the market: buyers get location choice, hourly rentals, and on-chain payments; providers get a single platform that aggregates demand. The kicker is stability. Aethir’s static lease fees create a baseline even when GPUs sit idle, letting operators scale into actual demand rather than guessing. That foundation supports a portfolio approach to revenue: pay OPEX in fiat, stack tokens for growth, and invest in GPU SKUs with clear utilization histories and 12–24 month payback windows.We also zoom out to the European landscape. The Netherlands offers elite fiber and interconnect density but faces expensive power and a saturated grid. That reality shifts strategy toward storage-heavy growth while onboarding next-gen GPUs like 5090s where the numbers make sense. The medium-term vision is compelling: pair decentralized compute with distributed storage so teams can run inference, fine-tune LLMs, and manage data gravity without surrendering cost control or flexibility. If AI demand keeps rising, this “house of DPin” model could redefine how we think about cloud alternatives at the edge.If this conversation sparked ideas about your own GPU strategy or you’re curious about decentralized infra economics, follow the show, share it with a teammate, and leave a quick review to tell us what you want to hear next.Support the showMore at https://linktr.ee/EvanKirstel

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