Digital Disruption with Geoff Nielson

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organicAs AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionAuthor, philosopher, and technologist David Weinberger joins the Digital Disruption podcast to explore how artificial intelligence is changing our understanding of knowledge, human intelligence, human judgment, business leadership, and technology. Look beyond the hype to consider what AI reveals about the world and the limits of our own thinking. Technology is rarely just a tool. It is a lens through which we interpret the world. In this episode, we talk about how machine learning and large language models challenge our reliance on rules and generalizations. David explains why paying attention to details and differences can reveal patterns that human understanding alone might miss. For business and technology leaders, these ideas raise practical questions about AI ethics, bias, and decision-making. Who decides what AI should optimize for? Where does human judgment remain essential? David explores why navigating complexity requires open conversations, diverse perspectives, and a willingness to rethink rigid strategies. Follow for more conversations about AI, technology, innovation, and digital transformation. Tell us in the comments: What is the biggest misconception about artificial intelligence?In this episode:00:00 Intro01:06 How technology shapes our understanding of the world04:45 How AI changes our thinking about intelligence07:19 What learning language reveals about humans and AI09:29 Infotech’s CIO Analytics10:28 Is AI a new way to understand reality?14:21 Why data changed the direction of AI15:45 Machine learning explained: Patterns versus rules19:41 What generalizations leave out23:34 McLean & Company: Human-Centric AI Program24:14 AI and the limits of human understanding27:23 Can we trust answers we don’t understand?29:26 Rethinking fairness through individual differences32:39 AI bias: Who decides what to optimize for?35:22 Why human values require human conversation37:51 Where AI can help business decision-making40:07 Separating AI capabilities from human responsibility42:04 AI writing tools and the importance of human review43:16 Human expertise we can’t fully explain44:56 Is the world becoming more chaotic?48:34 Why particular details matter to us50:09 Information overload and the pressure on leaders54:12 Black swans and the limits of five-year plans56:23 How open conversations uncover business ideas58:09 Why leadership needs more than one perspective59:44 The risks of relying on a single leader01:02:48 Collaboration and innovation: Lessons from Google and beyond01:07:16 Parting advice for business and technology leaders01:11:30 Closing reflections01:12:18 About InfotechOur links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionnow.Tech moves fast. So does work. Digital Disruption NOW helps you keep up and make sense of what matters. All signal. No static. An Infotech production.Are AI data centers in space a practical solution for the future or just an expensive fantasy? We analyze the technical reality. This week we’re covering the AI market rout, datacenters in space, and the Binance hack.In this episode: 0:00 The AI Rocket Ambition1:08 Big Tech’s AI Spending Hangover4:04 The Looming AI Cost Reckoning5:56 Managing AI Token Costs9:54 Is Frontier AI Overkill?11:12 Who Pays for AI Behind the Scenes?13:12 Will Efficiency Gains Bring AI Costs Down?15:05 Infotech CIO Analytics16:18 Project Sun Catcher: Data Centers in Orbit20:43 Cooling, Repairs, and the Challenges of Space Computing25:05 What Would Make Space Data Centers Viable?26:29 Who Owns Your Data in Space?27:32 The Binance Heist and Crypto Security31:13 Zero Trust, Permissions, and Security Failures33:04 Can Crypto Exchanges Be Trusted?37:29 Lessons from the Crypto Hack40:03 Wrap-Up and What’s NextVisit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG Check out other episodes from the Digital Disruption podcast: https://youtube.com/playlist?list=PLIImliNP0zfxRA1X67AhPDJmlYWcFfhDT&feature=shared

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organicAs AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionWhat if we can never fully predict or understand AI and need to rethink how we use it? Stephen Wolfram, creator of Mathematica and Wolfram|Alpha, explains why artificial intelligence remains fundamentally unpredictable and how we can make it useful despite those limits. Stephen joins us to discuss large language models, AI-generated code, and the difference between generating convincing answers and performing precise computation. He explains how combining generative AI with computational tools can help bridge that gap and why understanding what you’re building matters more as automation advances. The conversation also explores how AI could transform cybersecurity, powering both attacks and defenses. Stephen considers how these increasingly complex interactions could outpace human understanding and what that means for oversight and AI transparency. He explains why safeguards need to operate outside the AI itself to limit the consequences of unpredictable behavior. Follow for more conversations about AI, technology, innovation, and digital transformation. In this episode:00:00 AI beyond human understanding01:29 AI hype vs. long-term potential05:35 ChatGPT and natural language interfaces06:47 Combining generative AI with Wolfram Language08:41 CIO Analytics: API-Driven Advisory10:00 Understanding the world through computation13:17 How Simple rules create complex behavior16:15 Human-like AI vs. precise computation21:08 Why AI struggles with 100% accuracy22:39 McLean & Company’s Human-Centric AI program23:37 Where AI works and where it falls short27:17 The risks of AI-generated code29:49 Why understanding matters more than implementation33:51 Can we understand AI’s black box?36:37 Computational irreducibility explained39:49 Why AI needs external guardrails42:08 The limits of AI control43:25 AI-powered cyberattacks and defenses45:03 Automation and the future of work49:48 How Wolfram research uses automation54:00 AI coding and the rise of small software tools55:57 Choosing what to build when more is possible59:58 Finding value as an AI startup01:01:33 Leading innovation at Wolfram research01:07:47 Bringing Wolfram|Alpha to life01:10:48 Why managing scientific research is different01:13:01 Building teams that think broadly01:15:07 Matching people to projects and preserving their work01:19:30 Advice for founders: Build something you want01:21:03 Why CEOs need to understand their business01:24:03 Hiring beyond the polished interview01:26:15 Final thoughts 01:27:02 About InfotechOur links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionnow.Tech moves fast. So does work. Digital Disruption NOW helps you keep up and make sense of what matters. Coming to you from the Masonic Temple, Digital Disruption NOW is the latest podcast in the Digital Disruption network, bringing you a weekly take on tech, work, and what it all means. We break down the biggest headlines, debate the hottest topics, and explore how technology is changing the way we live and work. From the news everyone’s talking about to the developments you might have missed, get real perspectives and insights you can actually use. All signal. No static. An Infotech production.Is AI delivering real business value, or just bigger promises?Geoff and Jeremy break down Anthropic’s IPO prospectus, debate AI productivity and ROI beyond Big Tech, and examine OpenAI’s claims about modernizing legacy COBOL systems.From Claude’s growth and AI bubble risks to the gap between faster tasks and measurable business results, explore what the headlines mean for tech and work.In this episode:00:00 Intro: AI, productivity, and the guacamole problem00:28 Welcome to Digital Disruption NOW00:59 Anthropic’s IPO prospectus: promises and risks03:58 Anthropic’s finances: revenue, losses, and profitability06:28 Can Claude justify Anthropic’s valuation?11:48 AI bubble risks and an interconnected tech economy17:12 Anthropic IPO: final takeaways18:08 CIO Analytics: a single platform to run IT19:16 Apollo’s AI payoff report: Big Tech vs. everyone else20:46 The AI productivity paradox23:23 Is AI investment being measured in the right companies?26:41 Will more AI actually improve productivity?29:08 Why individual time savings don’t guarantee business growth33:20 Is AI becoming essential to staying competitive?34:52 Can OpenAI solve the COBOL code crisis?36:59 Why rewriting code isn’t the same as replacing systems38:03 The reality of legacy mainframe migration40:35 The doorman fallacy: what automation overlooks42:09 Why institutional knowledge still matters43:23 Episode recap and closing creditsVisit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast Follow us on YouTube: https://www.youtube.com/@InfoTechRG Check out other episodes from the Digital Disruption podcast: https://youtube.com/playlist?list=PLIImliNP0zfxRA1X67AhPDJmlYWcFfhDT&feature=shared

Explore API-driven IT advisory with CIO Analytics, a single platform to run your IT department that brings together your data, AI-powered analysis, and expert guidance to help you improve IT performance. Check it out here: https://www.infotech.com/cio-analytics?utm_source=youtube&utm_medium=social&utm_campaign=cio-analytics-youtube-organicAs AI reshapes work, help your team build the human judgment and practical skills to adapt with McLean & Company’s Human-Centric AI Program here: https://hr.mcleanco.com/training/programs/human-centric-ai?utm_source=youtube&utm_medium=social&utm_campaign=digitaldisruptionAI promises to transform the economy. When will that promise translate into measurable business growth?Entrepreneur and Silicon Valley Girl creator Marina Mogilko explores the gap between AI hype and economic impact, sharing where she sees opportunities for businesses, workers, and entrepreneurs.Marina joins us to discuss AI productivity, entrepreneurship, and the future of work. She examines why AI’s economic contribution remains difficult to measure, even as it helps small teams do more and creates new revenue opportunities.Drawing on her own experience, Marina explains how AI could lower the barriers to starting a business for solopreneurs and women entrepreneurs. She also questions the idea of a one-person billion-dollar company.From organizing company data to building targeted AI agents, the conversation explores what it takes to turn AI adoption into business value. Marina shares why experience, strategic thinking, and accountability remain essential, and how leaders can prepare their teams for sustainable growth.Follow for more conversations about AI, technology, innovation, and digital transformation.In this episode:00:00 Intro01:04 Why AI’s economic impact is hard to measure04:16 The case for optimism about AI05:49 How AI is changing tasks and productivity09:24 CIO Analytics: API-Driven IT Advisory10:15 Turning AI productivity into new revenue13:16 Lowering the barriers to entrepreneurship14:43 Can one person build a billion-dollar company?17:18 The AI agents marina uses in work and life20:19 Which tasks are worth automating?23:32 Why better AI results start with organized data28:28 How AI can reinforce bad business decisions30:53 Using AI as a data analyst while keeping human judgment32:01 Building an authentic brand without chasing AI doom37:44 Making AI useful and accessible to more people40:23 Women, AI adoption, and the need for relatable use cases46:49 Why education still matters in the AI era49:29 Questioning AI predictions and taking responsibility53:10 Lessons on entrepreneurship and long-term success55:55 Avoiding burnout and knowing when to pivot59:20 Finding the confidence to change careers1:00:52 Why telling your team to “Use AI” isn’t enough1:02:50 Building entrepreneurial teams and managing AI agents1:04:55 Lead AI adoption from the front1:05:36 McLean & Company’s Human-Centric AI ProgramConnect with Marina:LinkedIn: https://www.linkedin.com/in/marinamogilko/Instagram: https://www.instagram.com/siliconvalleygirl/X: https://x.com/siliconvalleymmFacebook: https://www.facebook.com/marina.mogilkoOur links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

If AI can free up half a company’s labor capacity, what happens to the people doing the work?Ravin Jesuthasan describes AI transformations that have freed up 40–50% of labor capacity. Is your organization ready for what that means for its workforce?The futurist and bestselling author explains how AI is reshaping the future of work and why its productivity gains don’t have to translate into layoffs.Ravin joins Geoff on this episode of Digital Disruption to discuss generative AI, AI agents, and the impact of automation on jobs. He explains why entry-level roles are under pressure, how traditional career paths are changing, and why judgment, empathy, and curiosity are becoming increasingly valuable.Drawing on examples from Standard Chartered and Unilever, he explores how organizations can prepare employees for new opportunities through upskilling and reskilling. He breaks down what it means to build a skills-powered organization where learning becomes part of everyday work.Ravin also shares how leaders can reinvest AI productivity gains in employee wellbeing, better customer experiences, and continued innovation.Follow for more conversations about AI, technology, innovation, and digital transformation.In this episode:00:00 Intro00:40 AI frees up half the work. what happens next?01:12 How AI is reshaping the future of work03:30 How AI changes the cost of work and access to talent06:23 Will AI replace all human work?09:40 Is the fear of becoming obsolete justified?12:12 McLean & Company’s human-centric AI program12:52 AI and the erosion of the entry-level career ladder17:32 What does “work ready” mean in the age of AI?19:51 Why human judgment is becoming an essential skill20:58 How to build a skills-powered organization23:20 Making learning part of everyday work24:38 Reskilling employees for new career opportunities26:23 Turning workforce transformation into action29:56 Setting a vision and proving ROI with focused pilots32:15 Who should own workforce transformation?33:35 Involving employees and preparing them for what comes next35:12 Unilever’s approach to reskilling and career transitions36:43 Why digital transformations fail39:17 Moving from one-time transformation to continuous reinvention41:16 Making space for learning and employee wellbeing42:34 How to reinvest AI’s productivity gains45:44 Why IT, HR, and business leaders need to work together48:15 Why adding AI isn’t enough to transform work51:12 The value of outside perspectives in AI transformation53:13 Final Advice: Learn, unlearn, and relearn54:40 About InfotechConnect with Ravin:LinkedIn: https://www.linkedin.com/in/ravinjesuthasan/X: https://x.com/RavinJesuthasanOur links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Is AI consciousness already here and can we reclaim our technological optimism? Google’s Blaise Agüera y Arcas shares why he believes AGI has already arrived and what AI can teach us about consciousness, cooperation, and the human mind.Blaise joins us on this episode of Digital Disruption to talk about AI consciousness, large language models, and why intelligence is inherently social. He explains how AI agent swarms work together, what recursive self-improvement looks like today, and why he questions the idea that smarter machines will inevitably dominate humanity.He questions why we find it easier to imagine catastrophe than a better future. And this conversation examines how negative news shapes our expectations of AI, and why taking its risks seriously can coexist with optimism about its potential.From AI alignment and mass surveillance to jobs and economic inequality, Blaise considers whether our institutions are ready for the changes ahead. He shares how AI could accelerate progress in medicine, robotics, and climate solutions, while emphasizing the work needed to turn those possibilities into reality.This episode asks an important question: As AI becomes more capable, how do we make sure the benefits reach everyone?Follow for more conversations about AI, technology, innovation, and digital transformation.In this episode:00:00 Intro02:12 Rethinking artificial intelligence 04:35 Can technology be considered alive?06:13 What does it mean for AI to be conscious?08:23 Multi-agent systems and the role of self-awareness11:48 Could AI have a subjective experience?17:49 What split-brain experiments reveal about consciousness20:49 Building your AI strategy with Infotech21:56 The Self: One mind or many parts?23:38 How LLMs differ from human minds28:19 Octopus intelligence, AI agent swarms, and identity32:52 Why Human Intelligence Is Collective38:19 Why Blaise believes AGI is already here43:59 Multi-agent AI and the next frontier of intelligence47:25 Recursive self-improvement and the singularity50:41 AI coding agents and the risks of faster automation54:18 AI Alignment: whose values should AI follow?58:20 Will smarter AI dominate humanity?1:01:42 Mass surveillance, power, and human disempowerment1:04:09 AI breakthroughs in medicine, robotics, and space1:08:12 Why are we so pessimistic about the future?1:11:29 Why AI doom gets more clicks1:13:16 Taking AI researchers’ fears seriously1:16:42 Nostalgia and the accelerating pace of change1:21:08 Is our economy ready for AI?1:24:07 AI, job loss, and the fear of losing income1:26:36 What should leaders and society do next?1:29:23 AI, climate change, and clean energy1:31:06 Moving AI computing into space1:31:42 Final thoughts1:32:06 About InfotechConnect with Blaise:LinkedIn: https://www.linkedin.com/in/blaise-ag%C3%BCera-y-arcas-85626a42/X: https://x.com/blaiseagueraIG: https://www.instagram.com/blaiseagueraOur links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

Predictive AI often gets ignored, yet it may hold the real key to business value in the current tech landscape.Machine learning expert Eric Siegel, author of The AI Playbook and Predictive Analytics, joins the Digital Disruption podcast to explain why organizations should invest at least as much in predictive AI as they do in generative AI. He breaks down how predictive AI can improve real-world operations, why so many AI pilots fail to reach deployment, and where the promise of autonomous AI agents encounters reliability challenges. While generative AI captures the headlines, Eric argues that more dependable returns often come from systems that predict outcomes and improve decision-making.The conversation explores the differences between predictive and generative AI, why meaningful business value comes from deployment rather than impressive demos, and the limitations of fully autonomous AI agents and artificial general intelligence. Tune in to learn how predictive AI could make generative AI more reliable, why business leaders and data scientists need to work together, and whether AI will really cause a job apocalypse.Like and follow for more conversations on AI, technology, innovation, the future of work, and digital transformation. 00:00 Why businesses may be investing in the wrong AI00:47 Predictive AI vs. generative AI03:01 How large language models fit into predictive AI06:59 What kind of AI is solving real-world problems?08:06 The two “wows” of AI: Impressive demos vs. deployment09:28 Build your AI strategy with Info-Tech10:37 Why predictive AI is still delivering business value12:32 Why most AI pilots fail to reach production16:25 AI hype and mismanaged expectations19:31 AI agents, AGI, and the promise of autonomy20:44 Can predictive AI make generative AI more reliable?23:57 Why full AI autonomy remains unrealistic26:59 Large language models vs. human intelligence29:21 The limits and diminishing returns of AI models31:35 What businesses are getting wrong about AI35:35 Bridging the gap between technology and business leaders37:18 Why leaders need a semi-technical understanding of AI38:59 Three questions every predictive AI project must answer42:22 Will AI replace developers and other technical roles?49:29 Who should own AI strategy and accountability?53:41 Is AI creating the productivity gains we were promised?55:49 Could future technology overcome today’s AI limitations?59:21 How organizations can unlock more value from AI1:01:43 Eric Siegel’s six-step AI deployment framework1:04:42 Why AI is a business improvement project, not a tech install1:06:02 What’s new in The AI Playbook1:09:30 Eric’s advice for business and technology leaders1:10:46 About Info-Tech Connect with Eric:LinkedIn: https://www.linkedin.com/in/predictiveanalytics/X: https://x.com/predictanalytic?lang=en IG: https://www.instagram.com/eric_siegel/Our links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

The robot workforce is already here. AI-powered humanoid robots are entering factories and warehouses to address a growing labor gap, but are they filling jobs or replacing the people who do them?Peggy Johnson, CEO of Agility Robotics, joins us to talk about how Digit is moving from robotics demonstrations into real workplaces. She explains why humanoid robots could become essential to manufacturing and logistics, how AI is accelerating their capabilities, and why safety remains the biggest barrier to widespread adoption.From physical AI and labor shortages to robot fleet managers and the future of work, this episode looks beyond the fear of robot overlords to ask: how will humans and robots work together in the years ahead?Subscribe for more conversations on AI, technology, innovation, the future of work, and digital transformation.00:00 Why humanoid robots may be essential00:47 Peggy Johnson, CEO of Agility Robotics01:41 Are humanoid robots creating a dystopian future?03:43 How workers respond to robots in the workplace05:42 Why build robots in the human form?07:27 Will humanoid robots replace human jobs?11:45 Why reshoring manufacturing will require robotics14:12 Info-Tech AI strategy14:42 What humanoid robots could do by 203217:35 The biggest barrier to adoption: Robot safety19:17 Why robots in the home are still years away22:13 How big and powerful is agility robotics’ Digit?24:44 Can humanoid robot accidents be prevented?28:29 Competing with Elon Musk and Tesla Optimus30:56 What separates deployment from a robotics demo33:37 How companies deploy humanoid robots37:01 Which industries are adopting robotics?39:24 Scaling production to meet demand41:08 How AI is accelerating humanoid robotics45:36 How digit makes decisions on the factory floor48:52 Hardware and software upgrades for robots50:57 What comes after agility robotics’ Digit?53:22 Will robots eventually do everything humans can?55:58 The future of physical AI and automation58:13 Peggy Johnson’s advice for business and tech leaders59:32 About Info-TechConnect with Peggy:LinkedIn: https://www.linkedin.com/in/peggyljohnson/X: https://x.com/agilityroboticsIG: https://www.instagram.com/agility_robotics/Our links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG

What is PDoom, and why are the people building artificial intelligence willing to risk human extinction?Kevin Roose, a New York Times technology columnist, Hard Fork co-host, and author of The AGI Chronicles, shares what he learned from interviewing more than 150 people inside the world’s leading AI companies.Kevin joins us on Digital Disruption to talk about what artificial general intelligence really means and how fear, ego, rivalry, and mistrust are accelerating the race between OpenAI, Anthropic, and Google DeepMind. He also explains why AI leaders compare this moment to the Manhattan Project: if they don’t build AGI first, someone more dangerous might.Kevin also shares why he estimates a 10% chance of AI-caused extinction and discusses the private fears of AI researchers, government regulation, autonomous AI agents, and whether the AI boom is a bubble or the beginning of a profound transformation.This episode moves beyond the hype to ask an important question: If advanced AI is inevitable, how much control do we still have over what happens next?Subscribe and follow for more conversations about AI, technology, innovation, and digital transformation.In this episode:00:00 Why AI builders fear human extinction00:43 Inside the race to build AGI01:24 What does AGI actually mean?05:16 AI safety warnings or marketing hype?07:27 The rivalries driving the AI race08:44 Building a boardroom-ready AI strategy09:51 The personal feuds behind AGI10:58 AI’s Manhattan Project mindset12:27 Is AI the new atomic bomb?14:58 Can advanced AI be contained?16:28 AI regulation and the global arms race17:35 What is P(doom)?19:54 What will force governments to act?21:29 What AI researchers say in private23:08 Why the public backlash is growing26:15 Why Kevin Roose changed his mind about AI29:42 Is advanced AI inevitable?32:28 AGI and the point of no return34:38 The race to automate AI research36:23 AI and gradual human disempowerment40:10 What happens when AI masters your skills?42:18 Will AI liberate us or replace us?44:18 The AI claims Kevin does not believe46:21 Is the AI boom a financial bubble?50:20 AI labs and economic concentration55:08 Inside the AGI chronicles57:07 How should people prepare for AI?58:29 About Info-Tech#ai #futureofwork #technologypodcast #aibubble #bigtech #artificialintelligence #technology #datacenter #agi #anthropic #futureofaiConnect with Kevin:LinkedIn: https://www.linkedin.com/in/kevin-roose/X: https://x.com/kevinrooseIG: https://www.instagram.com/kevinroose/Our links:Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcastFollow us on YouTube: https://www.youtube.com/@InfoTechRG