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: 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 problem

00:28 Welcome to Digital Disruption NOW

00:59 Anthropic’s IPO prospectus: promises and risks

03:58 Anthropic’s finances: revenue, losses, and profitability

06:28 Can Claude justify Anthropic’s valuation?

11:48 AI bubble risks and an interconnected tech economy

17:12 Anthropic IPO: final takeaways

18:08 CIO Analytics: a single platform to run IT

19:16 Apollo’s AI payoff report: Big Tech vs. everyone else

20:46 The AI productivity paradox

23:23 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 growth

33:20 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 systems

38:03 The reality of legacy mainframe migration

40:35 The doorman fallacy: what automation overlooks

42:09 Why institutional knowledge still matters

43:23 Episode recap and closing credits

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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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-organic

As 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=digitaldisruption

AI 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 Intro

01:04 Why AI’s economic impact is hard to measure

04:16 The case for optimism about AI

05:49 How AI is changing tasks and productivity

09:24 CIO Analytics: API-Driven IT Advisory

10:15 Turning AI productivity into new revenue

13:16 Lowering the barriers to entrepreneurship

14:43 Can one person build a billion-dollar company?

17:18 The AI agents marina uses in work and life

20:19 Which tasks are worth automating?

23:32 Why better AI results start with organized data

28:28 How AI can reinforce bad business decisions

30:53 Using AI as a data analyst while keeping human judgment

32:01 Building an authentic brand without chasing AI doom

37:44 Making AI useful and accessible to more people

40:23 Women, AI adoption, and the need for relatable use cases

46:49 Why education still matters in the AI era

49:29 Questioning AI predictions and taking responsibility

53:10 Lessons on entrepreneurship and long-term success

55:55 Avoiding burnout and knowing when to pivot

59:20 Finding the confidence to change careers

1:00:52 Why telling your team to “Use AI” isn’t enough

1:02:50 Building entrepreneurial teams and managing AI agents

1:04:55 Lead AI adoption from the front

1:05:36 McLean & Company’s Human-Centric AI Program

Connect with Marina:

LinkedIn: https://www.linkedin.com/in/marinamogilko/

Instagram: https://www.instagram.com/siliconvalleygirl/

X: https://x.com/siliconvalleymm

Facebook: https://www.facebook.com/marina.mogilko

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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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 Intro

00:40 AI frees up half the work. what happens next?

01:12 How AI is reshaping the future of work

03:30 How AI changes the cost of work and access to talent

06:23 Will AI replace all human work?

09:40 Is the fear of becoming obsolete justified?

12:12 McLean & Company’s human-centric AI program

12:52 AI and the erosion of the entry-level career ladder

17:32 What does “work ready” mean in the age of AI?

19:51 Why human judgment is becoming an essential skill

20:58 How to build a skills-powered organization

23:20 Making learning part of everyday work

24:38 Reskilling employees for new career opportunities

26:23 Turning workforce transformation into action

29:56 Setting a vision and proving ROI with focused pilots

32:15 Who should own workforce transformation?

33:35 Involving employees and preparing them for what comes next

35:12 Unilever’s approach to reskilling and career transitions

36:43 Why digital transformations fail

39:17 Moving from one-time transformation to continuous reinvention

41:16 Making space for learning and employee wellbeing

42:34 How to reinvest AI’s productivity gains

45:44 Why IT, HR, and business leaders need to work together

48:15 Why adding AI isn’t enough to transform work

51:12 The value of outside perspectives in AI transformation

53:13 Final Advice: Learn, unlearn, and relearn

54:40 About Infotech

Connect with Ravin:

LinkedIn: https://www.linkedin.com/in/ravinjesuthasan/

X: https://x.com/RavinJesuthasan

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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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 Intro

02:12 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-awareness

11:48 Could AI have a subjective experience?

17:49 What split-brain experiments reveal about consciousness

20:49 Building your AI strategy with Infotech

21:56 The Self: One mind or many parts?

23:38 How LLMs differ from human minds

28:19 Octopus intelligence, AI agent swarms, and identity

32:52 Why Human Intelligence Is Collective

38:19 Why Blaise believes AGI is already here

43:59 Multi-agent AI and the next frontier of intelligence

47:25 Recursive self-improvement and the singularity

50:41 AI coding agents and the risks of faster automation

54:18 AI Alignment: whose values should AI follow?

58:20 Will smarter AI dominate humanity?

1:01:42 Mass surveillance, power, and human disempowerment

1:04:09 AI breakthroughs in medicine, robotics, and space

1:08:12 Why are we so pessimistic about the future?

1:11:29 Why AI doom gets more clicks

1:13:16 Taking AI researchers’ fears seriously

1:16:42 Nostalgia and the accelerating pace of change

1:21:08 Is our economy ready for AI?

1:24:07 AI, job loss, and the fear of losing income

1:26:36 What should leaders and society do next?

1:29:23 AI, climate change, and clean energy

1:31:06 Moving AI computing into space

1:31:42 Final thoughts

1:32:06 About Infotech

Connect with Blaise:

LinkedIn: https://www.linkedin.com/in/blaise-ag%C3%BCera-y-arcas-85626a42/

X: https://x.com/blaiseaguera

IG: https://www.instagram.com/blaiseaguera

Our links:

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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 AI

00:47 Predictive AI vs. generative AI

03:01 How large language models fit into predictive AI

06:59 What kind of AI is solving real-world problems?

08:06 The two “wows” of AI: Impressive demos vs. deployment

09:28 Build your AI strategy with Info-Tech

10:37 Why predictive AI is still delivering business value

12:32 Why most AI pilots fail to reach production

16:25 AI hype and mismanaged expectations

19:31 AI agents, AGI, and the promise of autonomy

20:44 Can predictive AI make generative AI more reliable?

23:57 Why full AI autonomy remains unrealistic

26:59 Large language models vs. human intelligence

29:21 The limits and diminishing returns of AI models

31:35 What businesses are getting wrong about AI

35:35 Bridging the gap between technology and business leaders

37:18 Why leaders need a semi-technical understanding of AI

38:59 Three questions every predictive AI project must answer

42:22 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 AI

1:01:43 Eric Siegel’s six-step AI deployment framework

1:04:42 Why AI is a business improvement project, not a tech install

1:06:02 What’s new in The AI Playbook

1:09:30 Eric’s advice for business and technology leaders

1:10:46 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=podcast

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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 essential

00:47 Peggy Johnson, CEO of Agility Robotics

01:41 Are humanoid robots creating a dystopian future?

03:43 How workers respond to robots in the workplace

05:42 Why build robots in the human form?

07:27 Will humanoid robots replace human jobs?

11:45 Why reshoring manufacturing will require robotics

14:12 Info-Tech AI strategy

14:42 What humanoid robots could do by 2032

17:35 The biggest barrier to adoption: Robot safety

19:17 Why robots in the home are still years away

22:13 How big and powerful is agility robotics’ Digit?

24:44 Can humanoid robot accidents be prevented?

28:29 Competing with Elon Musk and Tesla Optimus

30:56 What separates deployment from a robotics demo

33:37 How companies deploy humanoid robots

37:01 Which industries are adopting robotics?

39:24 Scaling production to meet demand

41:08 How AI is accelerating humanoid robotics

45:36 How digit makes decisions on the factory floor

48:52 Hardware and software upgrades for robots

50:57 What comes after agility robotics’ Digit?

53:22 Will robots eventually do everything humans can?

55:58 The future of physical AI and automation

58:13 Peggy Johnson’s advice for business and tech leaders

59:32 About Info-Tech

Connect with Peggy:

LinkedIn: https://www.linkedin.com/in/peggyljohnson/

X: https://x.com/agilityrobotics

IG: https://www.instagram.com/agility_robotics/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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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 extinction

00:43 Inside the race to build AGI

01:24 What does AGI actually mean?

05:16 AI safety warnings or marketing hype?

07:27 The rivalries driving the AI race

08:44 Building a boardroom-ready AI strategy

09:51 The personal feuds behind AGI

10:58 AI’s Manhattan Project mindset

12:27 Is AI the new atomic bomb?

14:58 Can advanced AI be contained?

16:28 AI regulation and the global arms race

17:35 What is P(doom)?

19:54 What will force governments to act?

21:29 What AI researchers say in private

23:08 Why the public backlash is growing

26:15 Why Kevin Roose changed his mind about AI

29:42 Is advanced AI inevitable?

32:28 AGI and the point of no return

34:38 The race to automate AI research

36:23 AI and gradual human disempowerment

40:10 What happens when AI masters your skills?

42:18 Will AI liberate us or replace us?

44:18 The AI claims Kevin does not believe

46:21 Is the AI boom a financial bubble?

50:20 AI labs and economic concentration

55:08 Inside the AGI chronicles

57:07 How should people prepare for AI?

58:29 About Info-Tech

#ai #futureofwork #technologypodcast #aibubble #bigtech #artificialintelligence #technology #datacenter #agi #anthropic #futureofai

Connect with Kevin:

LinkedIn: https://www.linkedin.com/in/kevin-roose/

X: https://x.com/kevinroose

IG: https://www.instagram.com/kevinroose/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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Why have the United States and China pulled so far ahead in the global technology race? Mehran Gul, author of The New Geography of Innovation, argues that the answer goes far beyond individual companies or breakthrough technologies.

In this episode, we sit down with Mehran to discuss how successful innovation ecosystems are actually built, why Silicon Valley remains so difficult to replicate, and how China rapidly emerged as a global technology superpower. We also talk about why Europe and India have struggled to produce technology giants at the same scale, and how talent, capital, universities, government, and entrepreneurship shape long-term competitiveness.

Mehran also breaks down the extraordinary concentration of money flowing into AI companies like OpenAI, Anthropic, and Nvidia, whether today’s AI valuations are sustainable, and why a major market correction could still happen without ending America’s technological dominance.

From AI investment and venture capital to Silicon Valley, China, Europe, India, and the future of global innovation, this episode looks beyond the AI hype to ask a much bigger question: who will actually shape the next era of technology?

Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation.

In this episode:

00:00 The AI bubble and America’s technology lead

01:47 The new geography of innovation

05:30 How China became a technology superpower

09:13 Can other countries replicate China’s success?

13:17 What does “innovation” actually mean?

16:21 Are tech valuations measuring real innovation?

21:03 Does geography determine who wins in technology?

25:01 Will the U.S. and China dominate the next decade?

29:31 Why Europe’s push for tech sovereignty is struggling

33:05 Can government policy actually create innovation?

37:24 PayPal vs. Skype: How innovation creates more innovation

39:47 Is America’s technology dominance a zero-sum game?

43:52 Who is the world’s third-largest technology power?

45:07 Why “indispensability” may matter more than tech sovereignty

47:00 What This global tech race means for business leaders

48:32 Why AI investment is becoming more concentrated

51:29 Are we betting too much on a few tech leaders?

53:35 What Japan’s collapse can teach us about U.S. tech

56:13 Could the AI bubble actually burst?

59:22 Could China overtake the U.S. in Technology?

1:03:29 When government helps and hurts innovation

1:05:51 Predictions for the next era of global technology

1:07:50 Do We need to redefine innovation?

1:10:02 Where business leaders should look for innovation

1:14:02 Why venture capital isn’t actually global

1:18:00 Final thoughts

1:19:41 About Info-Tech Research Group

Connect with Mehran:

LinkedIn: https://www.linkedin.com/in/mehrangul?originalSubdomain=ch

X: https://x.com/mehrangul_

Our links:

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Are we in an AI bubble? Veteran Silicon Valley investor Bill Reichert says yes, but that doesn’t mean the AI revolution is slowing down.

In this episode we sit down with Bill Reichert, General Partner at Pegasus Ventures, to discuss the unprecedented investment pouring into AI, why many AI startups will fail, and where the next wave of innovation could emerge. This conversation highlights everything from data centers and quantum computing to China’s growing technology ecosystem and what businesses need to do to innovate and compete.

Bill also shares his “Yellow Jacket Paradox,” raising a bigger question about the future of AI: If biological intelligence can accomplish so much with so little energy, could a fundamentally new AI architecture eventually disrupt today’s LLMs, data centers, and AI leaders?

Subscribe and follow for more conversations with the world’s leading thinkers on AI, technology, innovation, and digital transformation.

In this episode:

00:00 The AI bubble is here

01:02 Why this tech cycle is different

03:30 Is AI growth sustainable?

04:18 Why most AI startups will fail

06:11 What separates AI winners from the hype

09:08 The “unfair advantage” in AI

10:59 Where is the next big AI opportunity?

13:16 Investing beyond generative AI

18:13 Why AI is becoming a commodity

19:05 The data center and energy opportunity

20:17 How AI is transforming every industry

22:23 Is AI changing venture capital?

26:13 Does more investment create better technology?

29:01 China, the US, and the global innovation race

34:28 The race for quantum computing

36:51 Is China really just copying the west?

40:06 Why big companies struggle to innovate

45:54 Startups as corporate innovation labs

47:29 How to spot an overhyped tech vendor

49:13 Why companies need to test before they invest

51:04 Why innovation pilots fail

52:49 Escaping “pilot hell”

54:54 Will the pace of innovation ever slow down?

57:30 How AI changes the future of work

59:48 Does AI mean we’ll have to work harder?

01:03:06 The leadership mistake that causes burnout

01:06:08 Control vs. unlimited growth

01:07:12 The “Yellow Jacket Paradox”

01:09:29 Why today’s AI architecture may be wrong

01:11:13 Will today’s data centers become obsolete?

01:13:38 The price of innovation

01:14:08 Closing thoughts

Connect with Bill:

LinkedIn: https://www.linkedin.com/in/billreichert/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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Hany Farid, one of the world’s leading experts on deepfakes and digital forensics, joins us to explain why AI-generated content is pushing us toward a world where we can no longer trust what we see, hear, or even who we’re talking to online.

From AI-generated misinformation and social media manipulation to voice cloning, deepfake video calls, and North Korean IT workers infiltrating major companies, Hany breaks down how rapidly the threat landscape is evolving. He explains why humans are not good at detecting deepfakes, how digital forensics experts actually identify manipulated media, and why organizations need to rethink cybersecurity, remote hiring, and digital identity.

This episode also dives into Big Tech’s role in the crisis, whether regulation and liability can make technology safer, the growing influence of large language models on how we access information, and what it will take to rebuild trust online.

Despite the risks, Hany remains optimistic about AI’s potential. The challenge, he argues, is learning from the mistakes of the social media era and finding a way to harness AI’s power without sacrificing safety, security, and trust.

Subscribe and like this video for more conversations with the world's leading thinkers on AI, technology, innovation, and digital transformation.

In this video:

00:00 North Korean IT workers are already inside companies

00:41 Welcome to a “trust no one” digital world

01:49 How much of the internet is already fake?

04:59 Are we heading toward the dead internet?

07:06 What happens when we can’t agree on facts?

08:20 The existential threat of a post-truth world

09:49 Could AI control the information we see?

11:33 Who is manipulating us online?

13:20 How AI is supercharging scams and fraud

15:41 Why you can’t reliably detect a Deepfake

17:28 Should Big Tech be held liable?

19:37 Hany’s Advice: Get social media off your phone

21:26 Can liability force Big Tech to change?

24:25 Should kids be banned from social media?

25:37 The real problem with social media’s business model

28:08 Will Big Tech control the future of AI?

31:20 “China will beat us” and the case against AI regulation

33:31 How experts actually detect deepfakes

36:16 How real-time face swap deepfakes work

39:39 The Deepfake threat facing businesses

40:25 AI fraud is already costing companies millions

41:47 How fake workers get hired

42:49 Why voice biometrics are no longer secure

#ai #futureofwork #technologypodcast #cybersecurity #deepfakes #digitaltrust #bigtech #aivoice #digitaltransformation #futureofjobs #futureofai #tedtalk

Connect with Hany:

LinkedIn: https://www.linkedin.com/in/hany-farid-40a97935/

Our links:

Visit our website: https://www.infotech.com/?utm_source=youtube&utm_medium=social&utm_campaign=podcast

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