Podcasts about Chief technology officer

Peter chats with Michael Kratsios on the White House's vision for a new golden age of American science, including the Genesis Mission, AI-driven research, and the push to dramatically accelerate scientific productivity. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Michael Kratsios is the White House Director of Science and Technology Policy and Assistant to the President for Science and Technology. He previously served as U.S. Chief Technology Officer and Acting Under Secretary of Defense for Research and Engineering, and later as a managing director at Scale AI. – My companies: Get the blueprint for generative media https://goo.gle/startupgenmedia  Apply to Dave's and my new fund: https://qr.diamandis.com/linkventureslanding   Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Build in the Foundry or get a live demo at: https://voicerun.com Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter  _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Micahel: LinkedIn X Instagram Listen to MOONSHOTS: Apple YouTube – *Recorded on July 29, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Before Matt Schwartz became Chief Technology Officer at Sage Hospitality, a weekend HTML class changed the trajectory of his career. In the first episode of our six-part series with him, Matt shares how that unexpected experience led him from environmental economics into technology and ultimately hospitality technology leadership.Learn more about the Destination AI Forum in Washington, DC (where Matt will be speaking)Want more?Learn more about Sage HospitalityListen to Matt discuss bringing AI into the hotel technology stack on Hotel Tech Insider [Podcast]Podcast episodes with Sage founder Walter Isenberg: The Letter That Turned a Young Dishwasher into a Hospitality LeaderThe Dana Crawford Playbook A few more resources:If you're new to Hospitality Daily, start here. You can send me a message here with questions, comments, or guest suggestionsIf you want to get my summary and actionable insights from each episode delivered to your inbox each day, subscribe here for free.Follow Hospitality Daily and join the conversation on YouTube, LinkedIn, and Instagram.If you want to advertise on Hospitality Daily, here are the ways we can work together.If you found this episode interesting or helpful, send it to someone on your team so you can turn the ideas into action and benefit your business and the people you serve!Music for this show is produced by Clay Bassford of Bespoke Sound: Music Identity Design for Hospitality Brands

Questions? Feedback? Send us a text!Most technology projects in higher education don't fail because of the technology.They fail because institutions struggle to sustain the change required to make them successful.The software gets purchased. The implementation begins. Teams work hard. But somewhere between launch and long-term adoption, priorities shift, leadership changes, or attention moves to the next initiative before the original work delivers its full value.In this episode of Transformed, Higher Digital Co-founder and CEO Wayne Bovier sits down with Julia Arreguy, Chief Technology Officer at the California Community Colleges Technology Center, to explore why organizational change—not technology—is often the determining factor in institutional success.Working across the largest higher education system in the nation, supporting 115 colleges and more than two million students, Julia brings a unique perspective on technology leadership, institutional transformation, AI, and the realities of driving change at scale.This conversation centers on a simple but important idea:Technology challenges are difficult. Organizational challenges are what determine whether the work succeeds.Julia shares insights on:Why organizational alignment is often harder than the technology itselfHow leadership consistency influences long-term project successWhy many institutions abandon initiatives before realizing their intended outcomesHow AI is creating new urgency across higher educationWhy intentional adoption matters more than chasing the latest technology trendWhether institutional structures are prepared for accelerating changeThe leadership behaviors that build trust during periods of uncertaintyWhy supporting internal change-makers can accelerate transformationWhat new CIOs and technology leaders should understand before introducing major changeWhy higher education's people remain its greatest source of optimismThroughout the conversation, Julia offers a practical reminder that transformation isn't about launching more initiatives.It's about staying committed long enough to achieve the outcomes those initiatives were meant to deliver.This episode challenges a common assumption:Technology is rarely the biggest obstacle.The harder work is maintaining alignment, sustaining momentum, and helping people navigate change when the pressure continues to rise.If you're leading technology, operations, strategy, or institutional transformation, this conversation offers valuable insight into what it actually takes to move change forward—and keep it moving.Subscribe to Transformed for more conversations with higher education leaders navigating complexity, technology, and the future of the institution.Subscribe or follow TRANSFORMED wherever you listen, to get the latest episode when it drops and hear directly from leaders and innovators in higher ed tech and digital transformation best practices.Find and follow us on LinkedIn at https://www.linkedin.com/company/higher-digital-inc 

Michael chats with Dr. Michael Park, Professor at the University of Minnesota, Neurosurgeon at M Health Fairview, Chief Technology Officer of SynerFuse, and the primary inventor of SynerFuse technology. Together, they discuss the reality of spinal surgery and the patient experience today, how SynerFuse has combined spinal fusion with dorsal root ganglion stimulation in a single surgery, how that innovation has proved to be safe, how that innovation has proved to reduce post-surgery pain and opioid use, how SynerFuse is aiming to advance the procedure into regular practice, where spinal surgery is headed in the future, and much more.

AI can analyze enormous amounts of information, but more data does not always lead to better decisions.  In this episode of Leader Generation, Tessa Burg talks with Dean Smith, CTO at Credit Benchmark, about why accurate, trusted data matters more than ever and how poor-quality information can quickly lead AI further from the truth. Dean shares a practical way for businesses to make progress without trying to overhaul everything at once: start with one problem, bring together the data needed to solve it and build from there.  Listen to learn how your organization can improve data quality, show value sooner and create a more adaptable data-first culture. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Dean Smith: Dean Smith is Chief Technology & Product Officer at Credit Benchmark, where he leads the company's technology strategy, engineering, data infrastructure and platform development. He is responsible for scaling Credit Benchmark's technology platform and advancing its data capabilities to meet the evolving needs of global financial institutions, with a focus on strengthening the integration between product innovation, data infrastructure and client delivery.  Dean can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

Netflix feels remarkably simple. Open the app. Find something to watch. Press play. But creating that experience is anything but simple. On this episode of Building One, Tomer Cohen sits down with Elizabeth Stone, Netflix's Chief Technology Officer and Chief Product Officer, to explore how one of the world's most iconic consumer products continues to evolve while staying remarkably intuitive. Netflix is no longer just movies and TV. It's live events, games, podcasts, mobile experiences, and AI-powered personalization. Elizabeth shares how Netflix is expanding into entirely new forms of entertainment—without making the product feel more complicated for its members. Before joining Netflix, Elizabeth built products across healthcare, transportation, and finance. That unique perspective shapes how she thinks about product strategy, organizational design, and solving complex problems at scale. In this episode, Tomer and Elizabeth discuss: How Netflix balances world-class content with world-class product and technology Why expanding from one product to many is one of the hardest challenges in product management How Netflix introduces new experiences without overwhelming its members Why content teams and product teams shouldn't operate the same way—and how Netflix bridges the gap How Netflix measures value across movies, games, live events, and podcasts Why AI raises the bar for product quality, taste, and judgment The future of entertainment: more personalized, immersive, and interactive experiences Whether you're building consumer products, leading cross-functional teams, or thinking about the future of AI and entertainment, this conversation offers a rare look inside the product philosophy behind one of the world's most influential technology companies.

Artificial intelligence has quickly become part of everyday life. It helps people write emails, summarize meetings, generate code, and answer questions in seconds.  But the next phase of AI may be less about generating information and more about taking action.  In this episode, Ty Panagoplos, Executive Vice President and Chief Technology Officer at Scotiabank, explains how AI has evolved from a specialized technology used by experts into a mainstream tool available to almost anyone. He explores one of the biggest trends shaping the industry today: Agentic AI.  Ty breaks down what Agentic AI actually is, how it differs from generative AI, and why organizations are paying close attention to its potential to automate increasingly complex tasks. He also discusses how banks are approaching AI adoption, balancing innovation with security, governance, and trust.  He also discusses:  Why ChatGPT changed the public conversation around AI and accelerated adoption  The difference between Generative AI, AI agents, and fully autonomous Agentic AI  How AI is already improving productivity across organizations  Why Scotiabank joined an AI consortium focused on safe AI deployment  The guardrails banks need before autonomous AI can be widely adopted  The risks posed by misinformation, hallucinations, security threats, and bad actors  The emerging role of AI agents in customer service and software development  How AI could help create more personalized banking experiences in the future  What the next three to five years of AI innovation may look like    For legal disclosures, please visit http://bit.ly/socialdisclaim and www.gbm.scotiabank.com/disclosures  Key moments this episode:  00:01:45 Ty Panagoplos' background in technology and banking  00:02:50 Why AI suddenly became mainstream  00:04:45 The biggest opportunities AI creates for businesses  00:06:05 How AI is already being used across banking  00:07:55 What Scotia Intelligence is and how it works  00:09:55 Generative AI versus agentic AI explained  00:12:00 Why Scotiabank joined an AI consortium  00:15:05 The risks of AI and the importance of guardrails  00:16:50 Privacy, hallucinations, scams and other concerns  00:18:00 The next wave of AI tools  00:19:30 Frontier models and the future of cybersecurity  00:20:55 What AI could look like over the next three to five years

For companies in the defense industrial base, a compliance deadline is not paperwork. It is the difference between winning contracts and watching them stall. In this Brand Feature, Jason LaPointe, Chief Technology Officer at Exostar, and Michael Parisi, Chief Growth Officer at Steel Patriot Partners, walk through what it takes to get FedRAMP ready without cutting corners. Exostar was born out of a consortium that included Boeing and Lockheed Martin, and its FedRAMP-moderate posture lets smaller suppliers keep working on Department of War contracts. How does that work? Instead of moving every server and mailbox into a secure boundary, a supplier inherits roughly 80% of the controls from Exostar, which shrinks the scope of its own CMMC audit considerably. The clock was real. At the time, a November transition date loomed, after which many suppliers could no longer self-attest. That specific timeline has since been paused, but the pressure to prove readiness has not gone away. Exostar needed to show it was FedRAMP-moderate and ready for an audit, and working with Steel Patriot Partners, the team pulled a January target in by nearly three months, not by skipping steps, but by moving with confidence. Why build a new platform instead of retrofitting the old one? Jason LaPointe describes a platform first initiative: build the new compliant home, then migrate customers into it. Trying to modernize inside a live production environment would have been disruptive, so the team built alongside rather than on top, which freed them to re-architect and retool without breaking customers. Michael Parisi frames the engagement as embedding, not staff augmentation. Steel Patriot Partners plugged directly into the product team through daily standups and leadership calls, delivered infrastructure as code and deployment pipelines, and kept the work with US citizens, a requirement once controlled unclassified information is in play. What makes an audit go smoothly? Preparation that extends to how questions get answered. Jason LaPointe compares the audit to a deposition, where an unsolicited comment hands an assessor somewhere new to go. Michael Parisi, who spent years in the assessor's seat and ran the practice for a large C3PAO, explains why knowing the auditors and presenting information cleanly protects the outcome. The business math is unforgiving. Miss the audit window and millions in direct contracts can be exposed, while auditors book out six to eight months. Exostar cleared it with a clean, no POA&M result, and the business is now seeing tailwinds through initiatives like Golden Dome. The lesson Jason LaPointe offers other technology and security leaders is about temperament. Every part of the organization gets touched, from R&D to HR to finance, and the willingness to change quickly becomes the governor on success. Having a clear voice at the table for what good looks like, as Steel Patriot Partners provided, is what accelerates the decisions. This is a Brand Feature. A Brand Feature is a ~30 minute in-depth conversation designed to go deep on a company's story, solutions, and customer success. Learn more: https://www.studioc60.com/creation#feature GUESTS Jason LaPointe, Chief Technology Officer, Exostar Website: https://www.exostar.com/ LinkedIn: https://www.linkedin.com/in/jasonlapointe Michael Parisi, Chief Growth Officer, Steel Patriot Partners Website: https://www.steelpatriotpartners.com/ LinkedIn: https://www.linkedin.com/in/michael-parisi-4009b2261/ RESOURCES Learn more about Exostar: https://www.exostar.com/ Aerospace and Defense solutions from Exostar: https://www.exostar.com/industries/aerospace-defense/ Learn more about Steel Patriot Partners: https://www.steelpatriotpartners.com/ Find Your Path with Steel Patriot Partners: https://steelpatriotpartners.com/find-your-path/ Are you interested in telling your story? ▶︎ Full Length Brand Story: https://www.studioc60.com/content-creation#full ▶︎ Brand Spotlight Story: https://www.studioc60.com/content-creation#spotlight ▶︎ Brand Highlight Story: https://www.studioc60.com/content-creation#highlight KEYWORDS Jason LaPointe, Michael Parisi, Exostar, Steel Patriot Partners, Sean Martin, brand story, brand marketing, marketing podcast, brand feature, FedRAMP, FedRAMP-moderate, CMMC, CMMC 2.0, defense industrial base, DIB, controlled unclassified information, CUI, compliance inheritance, C3PAO, FedRAMP audit, platform modernization, GCC High, Department of War, defense supply chain, cybersecurity compliance Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

AI readiness goes beyond testing the model. Even strong AI can fall short when it relies on outdated information, broken workflows, or poor handoffs between AI and human agents. This week on The Modern Customer Podcast, Seth Johnson, Chief Technology Officer at Cyara, shares what companies need to validate before scaling customer-facing AI.

Sid Dixit is originally from central India, and came to the states for college. He is a technologist and builder at heart, serving in leadership roles across major companies. He has built and managed a fleet of satellites, built robots at Amazon, worked at Microsoft on surface tablets, and finally, at Google working on Android. Outside of tech in lives in the Bay Area with his wife and kids. He loves water sports, especially sailing. He spent 10 years in San Diego, and stumbled on the sport.Sid's current company started in 1999, and was acquired in 2010. A few years ago, Sid joined the company, at a time when the company was wanting to rebuild its network from the ground up - starting with a powerful index.This is Sid's creation story at iTradeNetwork.SponsorsUnblockedTECH DomainsMezmoBraingrid.aiLinkshttps://www.itradenetwork.com/https://www.linkedin.com/in/siddharthdixit/Our Sponsors:* Check out Cash App and use my code CASHAPP10 for a great deal: https://cash.app* Check out Plaud AI and use my code CODESTORY for a great deal: https://plaud.aiAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

In the push to integrate AI into go-to-market strategies, are we optimizing for activity or for intelligence?Agility requires not just adopting new technologies like AI, but critically evaluating how they deliver contextual intelligence. It's about adapting your strategy based on smarter signals, not just automating existing processes at a higher volume.Today, we're going to talk about moving beyond the hype of generic AI in sales and marketing to focus on what actually drives revenue. We'll explore the concept of vertical AI, specifically for go-to-market teams selling to technical audiences, and how decoding intent signals from public developer conversations can create a significant competitive advantage.To help me discuss this topic, I'd like to welcome, Tal Peretz, CEO and Co-Founder at Onfire. About Tal PeretzTal Peretz is the CEO and Co-Founder of Onfire, a contextual AI platform that helps technology companies decode real-time market signals and drive revenue growth using developer and IT buyer intent data. Prior to Onfire, Tal was Chief Technology Officer at OwnID, a Tel Aviv based startup focused on identity security solutions. Tal served at the 8200 intelligence force and built and scaled advanced data and AI systems focused on large-scale entity resolution and signal intelligence. Drawing on this background, he recognized a fundamental gap in modern go-to-market technology: while AI promised precision, revenue teams were still operating on incomplete, noisy, and outdated data. Under his leadership, Onfire was designed from the ground up to solve the data layer for IT sales by combining structured third-party intelligence with first-party customer context into a continuously updated market map. Tal is married to Shai and is a proud father of two, Dan and Ran. Tal Peretz on LinkedIn: https://www.linkedin.com/in/tal-peretz/ ---------- Resources ---------- Onfire: The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

Financial advisors are being pitched new AI tools almost every day.The promise is simple: more automation, better client service, and fewer hours buried in administrative work.But adding AI to a fragmented technology stack doesn't automatically make your business smarter. If your client data is incomplete, trapped inside disconnected systems, or flowing through tools you haven't properly vetted, AI may amplify the problems you already have.Today, I'm talking with Triad's Chief Technology Officer, Quin Kilgore, to explore why the next era of advisor technology won't be won by the firm with the most software.We discuss why the tools that helped build your firm may not be the tools that carry it forward, where convenience can create hidden compliance risks, and how AI could reshape everything from marketing attribution and advisor coaching to client events and everyday operations.3 Insights From This Week's Episode…#1.) The Hidden Risk Beneath Every AI Tool Advisors tend to focus on what a new AI tool can do. But the bigger risk may be hiding in incomplete client records, fragmented systems, and unclear data policies. We explore why AI adoption can make weaknesses in your firm's foundation much harder to ignore.#2.) Why Today's Tech Stack May Become Tomorrow's BottleneckFor years, advisory firms built their businesses around software that was expensive to customize and painful to replace. Quin explains how quickly that equation is changing, and why advisors may need to reconsider what a “core” technology system even looks like.#3.) The Client Intelligence Advisors Are Leaving BehindYour client conversations contain far more valuable information than a traditional fact finder can capture. We explore what becomes possible when that information can be organized, understood, and used throughout the firm.INTERESTED IN TRIAD'S AI MASTERMIND?Triad's AI Advisor Lab, led personally by Michael Hyatt, is built for financial advisors who want to cut through the hype, apply AI more effectively, and stay ahead as the industry evolves. Apply here to see if the mastermind is the right fit for your firm: https://bradleyjohnson.com/178-ai-advisor-labSHOW NOTEShttps://bradleyjohnson.com/178FOLLOW BRAD JOHNSON ON SOCIALXInstagramLinkedInFOLLOW DBDL ON SOCIAL:YouTubeTwitterInstagramLinkedInFacebookDISCLOSURE DBDL podcast episode conversations are intended to provide financial advisors with ideas, strategies, concepts and tools that could be incorporated into their business and their life. No statements made in the episode are offered as, and shall not constitute financial, investment, tax or legal advice. Financial professionals are responsible for ensuring implementation of anything discussed related to business is done so in accordance with any and all regulatory, compliance responsibilities and obligations. The Triad member statements reflect their own experience which may not be representative of all Triad Member experiences, and their appearances were not paid for. Triad Wealth Partners, LLC is an SEC Registered Investment Adviser. Please visit Triadwealthpartners.com for more information. Triad Wealth Partners, LLC and Triad Partners, LLC are affiliated companies. TP07265629240See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Nathan Michael, Chief Technology Officer, Shield AI joined Grayson Brulte on The Road to Autonomy podcast to discuss why the future of warfare is autonomous.The conflicts in Ukraine and Iran have made the case for autonomy abundantly clear. Drones create asymmetric advantage by driving down the cost per effect, delivering outcomes at reach without putting pilots and service members into harm's way. As trust in these systems grows through engineered performance and assurance, autonomous systems will increasingly engage in combat and change the face of modern warfare.Shield AI's solution to the future of warfare is Hivemind, an AI pilot designed from the beginning to be platform agnostic, mission agnostic, and domain agnostic. This architecture aligns with the Air Force's autonomy government reference architecture for the Collaborative Combat Aircraft program, which mandates modularity and no vendor lock-in.No vendor lock-in is becoming a global standard, with nations demanding sovereign autonomy, ownership of data, and the flexibility to swap in the most performant AI pilot as the technology rapidly improves. Hivemind is now expanding beyond the air and maritime domains into space through a series of defense partnerships.Episode Chapters0:00 How Shield AI is Thinking About Autonomy in a World Full of Conflict1:56 Are Drones the Modern Equivalent of the Abrams Tank?4:09 Is Society Ready for Autonomous Warfare5:58 Developing Hivemind and the Aha Moments Along the Way10:50 Deploying V-BAT in Ukraine and Integrating Hivemind on One-Way Attack Drones13:59 The Autonomy Factory and Adapting Hivemind Across Platforms17:41 Going from Air to Sea with Huntington Ingalls22:39 Deploying Hivemind on the Airbus Lakota Helicopter for Contested Logistics25:52 Winning the U.S. Air Force CCA Mission Autonomy Production Contract29:37 Autonomy Government Reference Architecture and No Vendor Lock-In35:34 Expanding Hivemind into Space38:17 X-Bat, the World's First AI-Powered VTOL Fighter Jet40:34 AUTNMY AI--------About The Road to AutonomyThe Road to Autonomy is the leading applied intelligence platform covering the convergence of automation, autonomy, and the Autonomy Economy.™.Through our podcasts, newsletter, Indices and proprietary applied intelligence, we set the narrative for institutional investors, industry executives, and policymakers navigating the convergence of automation, autonomy, and economic growth.Join institutional investors and industry leaders who read This Week in The Autonomy Economy every Sunday. Each edition delivers exclusive insight and commentary on the autonomy economy, helping you stay ahead of what's next.Sign up for This Week in The Autonomy Economy newsletterFollow The Road to Autonomy IndicesSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

In episode 197 of Cybersecurity Where You Are, Sean Atkinson sits down with Ben Wilcox, Chief Technology Officer and Chief Information Security Officer at ProArch; and Ed Skoudis, President of SANS Technology Institute. Together, they discuss artificial intelligence (AI), operational technology (OT) data, and how understanding creates the foundation for AI-ready OT data.Here are some highlights from our episode:00:54. Introductions to Ben and Ed02:16. How we understand and integrate AI into OT environments04:30. How OT diverges from information technology (IT) in data responsibilities05:23. Opportunities for AI to assist OT06:33. The importance of meeting OT systems where they are08:10. A passive and incremental approach that respects the operations machines are doing12:29. Efficiency gains, public safety improvements, and other benefits of AI-ready OT data17:47. What lifecycle management, asset hierarchies, and governance look like for OT data22:14. The promise of AI to help to make OT environments understandable23:19. A team sport: How IT and OT can work together to understand assets and data28:38. The need for translation in IT-OT communication29:01. Recommendations for how to make OT data AI readyResourcesCIS Critical Security Controls®CIS Controls version 8.1 ICS WorkbookArtificial Intelligence and Large Language Models Companion GuideCIS Controls v8.1 Enterprise Asset Management Policy TemplateCIS Controls v8.1 Software Asset Management Policy TemplateCIS Controls v8.1 Data Management Policy TemplateCIS Controls v8.1 Account & Credential Management Policy TemplateEstablishing Essential Cyber HygieneProArchCybersecurity for Critical InfrastructureEpisode 77: Data's Value to Decision-Making in CybersecurityEpisode 183: The Role of CISO in Supporting Risk TranslationIf you have some feedback or an idea for an upcoming episode of Cybersecurity Where You Are, let us know by emailing podcast@cisecurity.org.

In the push to integrate AI into go-to-market strategies, are we optimizing for activity or for intelligence?Agility requires not just adopting new technologies like AI, but critically evaluating how they deliver contextual intelligence. It's about adapting your strategy based on smarter signals, not just automating existing processes at a higher volume.Today, we're going to talk about moving beyond the hype of generic AI in sales and marketing to focus on what actually drives revenue. We'll explore the concept of vertical AI, specifically for go-to-market teams selling to technical audiences, and how decoding intent signals from public developer conversations can create a significant competitive advantage.To help me discuss this topic, I'd like to welcome, Tal Peretz, CEO and Co-Founder at Onfire. About Tal PeretzTal Peretz is the CEO and Co-Founder of Onfire, a contextual AI platform that helps technology companies decode real-time market signals and drive revenue growth using developer and IT buyer intent data. Prior to Onfire, Tal was Chief Technology Officer at OwnID, a Tel Aviv based startup focused on identity security solutions. Tal served at the 8200 intelligence force and built and scaled advanced data and AI systems focused on large-scale entity resolution and signal intelligence. Drawing on this background, he recognized a fundamental gap in modern go-to-market technology: while AI promised precision, revenue teams were still operating on incomplete, noisy, and outdated data. Under his leadership, Onfire was designed from the ground up to solve the data layer for IT sales by combining structured third-party intelligence with first-party customer context into a continuously updated market map. Tal is married to Shai and is a proud father of two, Dan and Ran. Tal Peretz on LinkedIn: https://www.linkedin.com/in/tal-peretz/ ---------- Resources ---------- Onfire: The Agile Brand podcast is brought to you by TEKsystems. Learn more here: https://aglbrnd.co/r/2868abd8085a9703 We're proud to be a media partner for #MAICON26 - Oct. 13-15! Learn how AI can power your marketing and business and help you grow smarter. Use code AGILE150 to save! https://aglbrnd.co/r/7fe458ced0f04658Reach your customers with Reddit. Spend $500 in ad spend, get $500 back in ad credit! Learn more: https://advertalize.com/r/491818c79fb1873fChaser is the only Slack-native project management platform that helps teams turn messages into tracked tasks, automate follow-ups, and maintain team-wide visibility, without adopting another tool. Now integrated with Claude and other GenAI tools. Learn more at trychaser.com and use code AGILEBRAND for a 3-month free trial (normal trial is 14 days).The most influential minds in software, AI, and engineering leadership will be at WeAreDevelopers World Congress North America, September 23-25 in San Jose. Learn more: https://aglbrnd.co/r/60a7299222a7bcf1 Start building your own apps with Replit and get $20 off. Learn more: https://aglbrnd.co/r/93531742a7625a20 Enjoyed the show? Tell us more at and give us a rating so others can find the show at: https://aglbrnd.co/r/faaed112fc9887f3 Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkihlstromDon't miss a thing: get the latest episodes, sign up for our newsletter and more: https://aglbrnd.co/r/35ded3ccfb6716ba Check out The Agile Brand Guide website with articles, insights, and Martechipedia, the wiki for marketing technology: https://www.agilebrandguide.com The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company Hosted on Acast. See acast.com/privacy for more information.

This episode features Andre Priebe, Chief Technology Officer at iC Consult Group, the world's largest independent provider of identity security services.Andre has spent more than two decades leading IAM projects for large-scale enterprises across workforce, customer, and device identity domains. As CTO, he steers iC Consult's Centers of Excellence, service portfolio, and vendor strategy, and advises strategic customers on shaping their identity programs.In this episode, Andre explains why the gap between identity security awareness and actual maturity is growing every day, and how AI is making it faster and easier for attackers to find the weaknesses organizations already know they have. He breaks down why recovery is the most underestimated phase of the NIST cybersecurity framework and what it really costs when organizations haven't prepared for it.This episode is a candid look at the state of identity security from someone who sees it across hundreds of organizations every year.Guest Bio Andre Priebe serves as the Chief Technology Officer at iC Consult Group, a vendor-independent system integrator specializing in Identity & Access Management and Identity Security with a global team of over 850 employees. Boasting more than two decades of experience managing IAM projects focused on workforce, customer, and device identities within large-scale enterprises, Andre steers the Centers of Excellence, the service portfolio, and vendor strategy at iC Consult.Andre's role involves a deep focus on emerging approaches, trends, and technologies within the IAM sector, assessing their business value for iC Consult's clientele. He is an innovator with a patent in DevOps-related IAM methodologies, and he holds a B.Sc. and an MBA.Guest Quote  “Threat actors, for them, it's easier than ever before, faster, more efficient to identify that kind of technical debt, the weaknesses. They are not going for your latest Entra ID, conditional access, configuration with all the fancy stuff in place to really make sure that nobody else accessing that resource. No. They're going for the old systems, for old protocols, for areas that might be out of control, out of visibility. Third parties, contractors, unmanaged devices.”Time stamps 0:40 Meet Andre Priebe: Veteran IAM Expert 2:43 The State of Identity Security Awareness 4:51 The Reality of Technical Debt 6:16 How AI Is Changing the Attack Landscape 10:37 Zero Trust Is Mandatory but Almost Nobody Has Achieved It 15:06 What Customers Are Actually Asking About Now 19:19 Planning for Identity Recovery 26:08 The Most Underestimated Part of Recovery 29:56 Return to Trustworthiness vs Return to Operations 39:42 AI Agents and Non-Human Identities 44:02 Conclusion and Final ThoughtsSponsor The HIP Podcast is brought to you by Semperis, the leader in identity-driven cyber resilience for the hybrid enterprise. Trusted by the world's leading businesses, Semperis protects critical Active Directory and Entra ID environments from cyberattacks, ensuring rapid recovery and business continuity when every second counts. Visit semperis.com to learn more.LinksConnect with Andre on LinkedInConnect with Sean on LinkedInDon't miss future episodesLearn more about SemperisHIP Conference 26 is coming to Nashville, September 8–10, 2026.Join us to explore this year's theme, Redefining Resilience, at the world's premier practitioner-led conference focused on securing hybrid identity environments.If you love the conversations on the HIP Podcast, this is where the community comes together in person. Learn more and register at https://www.hipconf.com/.

Could the disaster recovery plan designed to protect your company make a ransomware incident even worse? In this episode, I speak with Darren Thomson, Vice President and Chief Technology Officer for EMEA at Commvault, about Resilience Operations, commonly known as ResOps, and why cyber recovery now requires security, infrastructure, identity and data teams to work from one coordinated plan. Darren argues that many companies are accepting a difficult reality. Even with considerable investment in prevention and detection, a breach may eventually succeed. That does not make cybersecurity controls any less necessary, but it means recovery can no longer be treated as a secondary activity managed by another department. The problem is that security operations and infrastructure teams have traditionally worked toward different objectives. Security specialists concentrate on identifying and stopping threats. Infrastructure teams protect data, maintain backups and restore systems after outages. During a cyberattack, a successful recovery requires both sets of expertise. A backup administrator may be able to restore data quickly, but a forensic specialist must establish whether that data is clean. Without that confirmation, the company risks restoring malware and restarting the incident. Darren explains why a conventional disaster recovery plan may be particularly dangerous during ransomware. These plans were commonly designed for physical failures such as a lost data center. Data would be copied from one location to another so operations could continue. If the source data is infected, however, fast replication can carry the malware into the recovery environment. This is where ResOps enters the discussion. Darren describes it as an operating model rather than a product. It combines established practices from security and infrastructure management into a continuous program for testing, learning and improving recovery. Individual technology projects may come from the program, but resilience itself never reaches a final completion date. AI adds pressure on both sides. Criminals can use it to create faster and more effective attacks, while defenders can use machine learning to inspect large volumes of information, detect patterns and identify the newest clean recovery point. Companies must also protect AI systems as they would any other business application, including the models, data repositories and identities connected with them. Darren offers one practical starting point for CIOs and CISOs: Mean Time to Clean Recovery, or MTCR. This measures how long it takes to restore an application and its data with evidence that both are free from compromise. Before measuring MTCR, leaders must define their minimum viable company. These are the systems and services the business cannot operate without. Once that list exists, teams can test how long a verified clean recovery would take and replace assumptions with evidence. The initial answer may be uncomfortable. Teams may know how to restore an application without knowing whether the backup is clean. Security may know how to inspect the system but lack an established workflow with the recovery team. Darren sees those gaps as the starting point for a useful ResOps program because they provide everyone with a shared problem and a measurable objective. If your most important systems disappeared today, how long would it take to bring the minimum viable company back using verified clean data? Listen to the episode and share your answer with me.

In this episode of the Facilitation Lab podcast, host Douglas Ferguson interviews Taran Lent, Chief Technology Officer at Illumia, about how his organization moved from individual AI experimentation to enterprise-wide capability. Lent describes building an "enablement task force" that deliberately avoided becoming a governing bottleneck, instead creating conditions for employees to play, learn, and share what worked, before this year's push to elevate personal AI habits into shared team and company-wide skills, standards, and vetted tools. He talks about using AI as a contrarian thought partner and even having it grade his own interviewing and meeting behavior, while cautioning that transcripts alone miss tone and body language. The conversation also covers the governance side of scaling AI, including a stakeholder review process for new tools and skills, the four-to-six-week approval timeline for new vendors, and guardrails to prevent incidents like an unauthenticated internal dashboard. Lent connects this to Illumia's recent merger of Transact and CBORD, crediting a shared "humble, hungry, smart" culture for making the integration smoother, and closes by arguing that judgment, creativity, and human discernment remain the differentiators as AI adoption accelerates.

La Commissione europea impone a Google di condividere i dati delle ricerche con i motori concorrenti e di aprire Android ai servizi di intelligenza artificiale alternativi a Gemini. Due decisioni importanti per il settore tecnologico destinate a cambiare molte attuali dinamiche. Ne parliamo con Innocenzo Genna, esperto di regolamentazione europea in ambito digitale e Roberto Pezzali, esperto di tecnologia della redazione di Dday.it.Fastweb ha iniziato una sperimentazione con Starlink per usare normali smartphone 4G in aree remote del Paese dove è assente il servizio di telefonia mobile terrestre. È il primo test in Italia della tecnologia “Direct to Cell” come spiega Max Gasparroni, Chief Technology Officer di Fastweb + Vodafone.Con Stefano Sordi, direttore generale di Aruba, ci occupiamo delle nuove estensioni Internet di primo livello che verranno assegnate nei prossimi mesi: nasceranno nuovi domini collegati a specifici brand, regioni o città.E come sempre in Digital News le notizie di innovazione e tecnologia più importanti della settimana.

If you're feeling burnt out, it's not the work you're doing. It's the mission you're on. Today, we're talking to Justin Fanelli, Chief Technology Officer of the Department of the Navy. We discuss why direct communication is fuel rather than friction, how the most driven government workers are often the ones who've already "made it" elsewhere, and why burnout has almost nothing to do with hours worked and everything to do with whether you feel connected to something bigger. All of this right here, right now, on the Modern CTO Podcast! 

Every marketer and business leader is talking about AI right now, but many companies are stuck. They've run the pilots, tried the tools and still can't turn any of it into real results.  In this episode, Tessa Burg talks with Dhiraj Rajaram, Founder and CEO of Mu Sigma, about why that gap between AI hype and AI impact exists. And what it actually takes to close it. Dhiraj breaks down some big ideas in an easy-to-follow—and very entertaining—way, like why every new technology creates a bubble and why AI is no different. He explains why most companies are trying to bolt AI onto old ways of working rather than rethink how decisions are made.  If you've ever wondered why your company's AI investment has not paid off the way you had hoped, this conversation will give you a new way to think about the problem. You'll walk away with practical language and a framework you can bring back to your own team along with a clearer picture of what needs to change before any new technology can really move the needle.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Dhiraj Rajaram: As Founder, Chairman and CEO of Mu Sigma, Dhiraj Rajaram built one of India's first profitable unicorns. He pioneered decision sciences, digitizing management consulting by mapping decision and perception traces—visionary concepts now critical in an agentic, AI-driven corporate world. Today, Mu Sigma helps over 140 Fortune 500 organizations, including Microsoft, Walmart, Pfizer and Dell, convert technology investments into scalable decision systems. An elite business leader and University of Chicago Booth School of Business Distinguished Alumnus, Dhiraj's background spans consulting at PwC and Booz Allen Hamilton. He has been recognized by Fortune's 40 Under 40 and Ernst & Young Entrepreneur of the Year. He can be reached on www.mu-sigma.com. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

Why are companies spending heavily on AI tools while struggling to show meaningful improvements in productivity, revenue, or business performance? In this episode of Tech Talks Daily, I speak with Matt Cloke, Chief Technology Officer at Endava, about what it takes to become an AI-native business, why deploying thousands of AI licenses does not amount to an AI transformation, and how companies can move from experimentation to measurable business outcomes. Matt has played a central role in Endava's own adoption of artificial intelligence and the development of Dava.Flow, the company's methodology for applying AI throughout the technology delivery lifecycle. With more than 11,000 employees and clients operating across multiple industries, Endava has treated itself as "client zero," testing AI internally before advising other companies about how to introduce it across their operations. Matt shares the story of a CEO who proudly told him that his company had completed its AI transformation after purchasing 10,000 licenses for an AI tool. Twelve months later, the business had seen little return on its investment and returned for help understanding what becoming AI-native actually required. The story captures one of the biggest problems with enterprise AI adoption today: buying technology is easy, but changing how people think about problems, redesign workflows, and create business value is much harder. We discuss why Matt believes becoming AI-native is primarily a mindset. Rather than treating AI as another application added to the technology stack, employees should become curious about where AI can improve existing processes, remove unnecessary work, and create new ways of delivering value. Matt also explains his idea that AI works best when it becomes invisible. Instead of requiring employees to constantly interact with chatbots and standalone AI applications, software agents can operate inside existing workflows, monitor information, prepare responses, identify problems, and bring people into the process when human judgment is required. His own use of AI agents provides a practical example. While attending meetings that prevented him from monitoring email for several days, Matt used agents to review incoming messages, redirect requests, identify urgent communications, and prepare draft responses. Rather than handing complete control to automation, he determined which actions required approval and where AI could operate independently. This leads to a wider discussion about human oversight and accountability. Matt argues that managing AI agents may increasingly resemble managing teams. Leaders do not inspect every decision made by every employee, but they establish responsibilities, controls, escalation points, and circumstances where intervention is required. Companies introducing agentic AI need similar approaches to supervision. We also examine two mistakes Matt frequently sees companies make. The first is treating AI adoption as a software rollout, buying tools for employees and expecting productivity gains to appear automatically. The second is creating centralized AI centers of excellence and expecting a small group of specialists to determine how every department should use the technology. Matt argues that employees closest to business processes are often best placed to identify opportunities for improvement. At Endava, the legal team runs monthly AI hackathons to redesign its own workflows, supported by technology specialists but led by people who understand the work itself. For companies operating in payments, financial services, and other regulated industries, the conversation turns to reliability, auditability, traceability, and risk. Matt explains how Dava.Flow allows companies to translate regulatory requirements and operational controls into policies that AI systems must follow and demonstrate throughout the delivery process. Rather than searching for a single killer AI application, Matt recommends examining end-to-end business workflows. Companies can map how information moves between employees, departments, and systems, identify unnecessary handoffs and manual processes, and determine where AI agents can improve speed, cost, and performance without replacing entire technology platforms. Leadership is another major theme throughout the episode. Matt believes the companies that achieve meaningful results from AI will be led by executives who personally use the technology, understand its capabilities, and demonstrate the behaviors they expect from their workforce. He shares how Endava brought senior leaders from legal, technology, people, and other business functions together to build software agents themselves. The experience changed how executives thought about technology investments, including one leader realizing that an existing vendor contract might no longer be necessary because the company could build the required capability internally. For CIOs, CTOs, technology leaders, and business executives under pressure to demonstrate returns from AI investment, this conversation provides practical lessons on becoming AI-native, redesigning workflows, managing software agents, maintaining human accountability, operating AI in regulated industries, and moving beyond technology adoption toward measurable business value. The companies that succeed with AI may not be those buying the most tools or making the biggest announcements. They will be the ones whose leaders understand the technology, whose employees rethink how work gets done, and whose AI systems quietly become part of everyday business operations.

Your cybersecurity tools were built for people: a login, a single sign-on, an email address. But the AI agents now showing up inside your company don't work that way, and most of them slip right past your controls. So how do you find the "Shadow AI" already running in your business, and get a handle on it? Let's find out with our guest Nancy Wang, Chief Technology Officer at 1Password, who works at the front edge of how machines get access to systems. Your hosts are Kip Boyle, CISO with Cyber Risk Opportunities, and Jake Bernstein, Partner with K&L Gates.   LinkedIn profile profile: https://www.linkedin.com/in/wangnancy/   1Password: https://1password.com/

What happens to blockchain networks, digital assets, and the wider internet when quantum computers become powerful enough to break the cryptography protecting them? In this episode of Tech Talks Daily, I speak with Bruno Martins, Chief Technology Officer of the Algorand Foundation, about what quantum computing means for blockchain security, why post-quantum cryptography is becoming a technology priority, and how enterprises should evaluate blockchain infrastructure for payments, digital assets, identity, and other business applications. Bruno brings experience from across several major blockchain ecosystems, including Consensys and IOHK, alongside a background in applied cryptography, key management systems, enterprise blockchain development, and software engineering. His perspective provides a useful view of how the blockchain industry has changed from experimental projects and speculative use cases toward platforms expected to support real financial transactions and business operations. We begin with the quantum threat itself. Bruno explains why the cryptographic systems protecting blockchains, financial infrastructure, communications, messaging platforms, and much of the internet could eventually become vulnerable to sufficiently powerful quantum computers.  While the exact timeline remains uncertain, he argues that waiting for a cryptographically relevant quantum computer to arrive before beginning migration would leave companies with too little time to update infrastructure, applications, wallets, accounts, and user behavior. The conversation examines why post-quantum security is not simply a future technology problem. Large digital ecosystems can take months or years to migrate, and businesses need time to understand their cryptographic dependencies, introduce new standards, educate users, and build systems capable of adopting new security methods without disrupting existing operations. Bruno shares how Algorand has been working on post-quantum security for several years, including the deployment of Falcon signatures for state proofs and plans to introduce quantum-resistant account types and additional protections across consensus and network communications. We discuss why cryptographic agility may be more important than simply replacing existing cryptography with newer algorithms that have not yet experienced decades of testing in real-world systems. This leads to one of the most valuable technical lessons in the episode. Moving directly from classical cryptography to post-quantum cryptography introduces its own risks because newer cryptographic methods may later reveal weaknesses. Bruno explains why hybrid approaches, where digital assets and accounts can be protected by both established and quantum-resistant cryptography, could provide a more responsible path for institutions managing long-lived systems and valuable assets. We also examine how enterprises should evaluate blockchain platforms. With thousands of networks competing for developers, users, and institutional adoption, Bruno argues that businesses need to look beyond market attention and transaction speed. Throughput, decentralization, security, programmability, finality, operational risk, and the ability to trust the state of a ledger all influence whether blockchain infrastructure is suitable for real business operations. Payments provide a practical example. Companies issuing payment products backed by stablecoins need confidence that transactions are final and cannot later be reorganized or reversed by the underlying network. Bruno explains why instant finality can reduce operational uncertainty and risk for companies building financial applications on public blockchain infrastructure. The conversation also turns to AI agents and agentic commerce. If autonomous software agents begin negotiating, purchasing services, exchanging value, and conducting transactions with other agents, they will need payment rails, identity systems, trusted counterparties, and ways to establish ownership and accountability. Bruno explains why stablecoins, digital identity, decentralized finance, and blockchain infrastructure could become increasingly relevant as AI systems begin participating directly in economic activity. Throughout the episode, Bruno offers a balanced assessment of the blockchain industry itself. He discusses the problems created by technical fragmentation, competing standards, thousands of networks, and ecosystem tribalism. Greater cooperation between blockchain communities, particularly around wallets, hardware, cryptographic standards, and post-quantum security, could make it easier for enterprises and developers to build applications that work across ecosystems. For technology leaders, security professionals, blockchain developers, and anyone responsible for long-lived digital infrastructure, this conversation provides a practical introduction to quantum threats, post-quantum cryptography, cryptographic agility, blockchain finality, stablecoins, and the technical questions companies should ask before choosing distributed infrastructure. The quantum threat may not arrive tomorrow, but migrating complex systems takes time. The companies and technology platforms preparing today will be in a much stronger position to protect digital assets, maintain trust, and continue operating when current cryptographic standards eventually need to change.

Sejal Amin is the Chief Technology Officer at Priceline, where she leads product engineering, infrastructure, data, and technology operations. Pedro Gutierrez is Senior Director of Software Engineering, where he has helped drive developer experience initiatives and the adoption of Priceline's product operating model.In this episode of the Engineering Enablement podcast, Justin Reock talks with Sejal and Pedro about Priceline's journey from a project-based organization to a product operating model and the role developer experience played in making that transformation successful. They discuss how DX metrics and developer feedback helped identify organizational bottlenecks, guide structural changes, empower engineering managers, and build trust across teams. They also explore the importance of clear communication, creating a dedicated developer experience team, and how their operating model has helped prepare Priceline for AI-driven software development.Where to find Sejal Amin:  • LinkedIn: https://www.linkedin.com/in/sejal-aminWhere to find Pedro Gutierrez: • LinkedIn: https://www.linkedin.com/in/pedro-gutierrez-b6605422Where to find Justin Reock:• LinkedIn: https://www.linkedin.com/in/justinreock In this episode, we cover:(00:00) Intro(01:07) Meet Sejal Amin and Pedro Gutierrez(01:47) How Priceline's developer experience journey began(04:55) Lessons from Priceline's first developer experience surveys(06:55) How DX improved Priceline's developer experience surveys(09:47) Identifying the causes of organizational slowness(12:33) How the product operating model changed the way Priceline works(14:10) Priceline's phased rollout with DX(18:14) How DX insights drove organizational changes(19:33) Why Priceline improved developer experience before org change was complete(22:18) How clear communication builds trust(24:25) Early results from Priceline's Core Four(25:38) Creating a culture of continuous feedback to build trust(27:40) What has changed in the engineering manager role(30:10) Resources for learning about the product operating model(32:40) What Pedro learned from implementing DX(34:51) The developer experience team(35:59) How AI tools have impacted Priceline's teams (37:20) How the product operating model supports AI-driven development(39:13) Final advice for engineering leadersReferenced:• Measuring developer productivity with the DX Core 4• Transformed: Moving to the Product Operating Model (Silicon Valley Product Group) • Team Topologies• Flow Framework• Project to Product: How to Survive and Thrive in the Age of Digital Disruption with the Flow Framework

Michael speaks with Anthony Vinci, former career intelligence officer and the first Chief Technology Officer of the National Geospatial-Intelligence Agency. They discuss Anthony's new book, "The Fourth Intelligence Revolution: The Future of Espionage and the Battle to Save America", which explores how artificial intelligence and intensive competition with China have transformed modern spycraft. Anthony explains his forecast where "machines are going to spy on machines," rendering legacy counterterrorism and Cold War operations obsolete. He warns that adversarial surveillance strategy now directly targets the digital lives of everyday Americans, demanding an urgent re-assessment of how Washington approaches economic espionage to protect national sovereignty.

In this episode of The Product Podcast by Product School, Carlos González de Villaumbrosia sits down with Jeff Kunins, Chief Product Officer and Chief Technology Officer at Axon, the company that created the Taser and the body cameras federal agencies wear. Axon ingests more video per year than YouTube, and with a market cap of approximately $32.9 billion and $2.78 billion in revenue, growing 33% year over year, it is one of the highest-growth companies in the S&P 500. What you'll learn:How law enforcement agencies are using AI inside body cameras and Tasers to save lives, not just hit metrics.Why Axon declared a public moratorium on facial recognition AI for six years and what finally changed.How Axon embeds external activists and researchers directly into product manager squads as a design input, not a compliance process.Building first-party AI models for real-time license plate detection while using foundation LLMs for everything else.Key takeaways:Axon created the Taser and the body cam, and now ingests more video per year than YouTube. Most people have never heard of them.Build only what you must to be differentiated. Everything else, license from the best available source.Ethics review is not a compliance burden. When embedded in the product lifecycle, external critics help you see around corners and design better products.Credits:Host: Carlos Gonzalez de VillaumbrosiaGuest: Jeff KuninsSocial Links:Find out more about Product School hereFollow our Podcast on TikTok hereFollow Product School on LinkedIn here

Ryan Bishara and Christian Lau team up on an AI and data playbook that delivers an engaging, penalty free experience for LAFC employees and fans on and off the pitch.   Ryan, Christian and Kimberly discuss LAFC's innovative ethos; building an analytics and data program from the pitch up; LAFC's AI plays; making mistakes and continuous learning; keeping AI onside with responsive governance; prioritizing joy and the human experience; if convenience and privacy can co-exist; staying accessible and engaging fans; and how analytics/AI continue to play out in a rapidly evolving ecosystem.  Ryan Bishara and Christian Lau serve as the EVP of Revenue & Strategy and Chief Technology Officer, respectively, at the LA Football Club (LAFC).  A transcript of this episode is here.

Continuing to expand our technology for the betterment of farming is the driving force at Redox. It is passionate quest of our research team, headed by Dr. Gifford Gillette.“It's an incredibly challenging time in agriculture right now,” Gillette said. “We are doing our absolute best to provide answers and solutions for the challenges that growers face.”Each summer, a group of talented interns helps this effort, and this year's additions of  Sheldyn Rogers, Dallas Cummins, Shianne Bair and Cyrus Taylor have made an immediate, positive impact with their work ethic and quick acclimation. The company's firm commitment to research is evidenced by a new state of the art laboratory, three PhD's on staff and the recent addition of Jackeline Garza as Chief Technology Officer. 

Have you ever wondered whether the biggest competitive advantage in wealth management is no longer investment performance alone, but the ability to turn information into action faster than everyone else? In this episode of Tech Talks Daily, I welcome Bob Pisani, Chief Technology Officer at Addepar, a platform that helps investment professionals manage and analyze more than $9 trillion in assets globally. Our conversation explores why modern wealth management has become a technology challenge just as much as a financial one, and why firms that continue relying on fragmented legacy systems risk falling behind in an industry where speed, data quality, and client expectations are changing faster than ever. Bob explains how wealth advisors have historically spent far too much of their day moving between disconnected systems, stitching together spreadsheets, and trying to answer client questions using incomplete information. While that may once have been acceptable, today's investors expect near real-time visibility into their portfolios, along with personalized guidance that reflects rapidly changing market conditions. That changing expectation places an enormous premium on time, making technology one of an advisor's most valuable assets. Our discussion explores why successful AI initiatives begin long before deploying a model. Data quality, governance, and creating a trusted source of truth remain the foundations that determine whether AI produces reliable insights or simply accelerates poor decisions. Bob shares how Addepar approaches this challenge by bringing together fragmented financial data, standardizing it across hundreds of custodians, and creating the conditions where AI can produce meaningful, actionable intelligence rather than more noise. We also look at practical examples of AI already improving advisor productivity today. From summarizing portfolio performance and analyzing complex alternative investment documents to introducing intelligent agents that reduce operational workload, Bob explains how AI is freeing experienced professionals to spend less time gathering information and more time building trusted client relationships. One of my favorite moments in our conversation comes when we discuss predictive intelligence. Instead of waiting for advisors to search for answers, AI is beginning to surface opportunities, risks, and client conversations before anyone even knows which questions to ask. That represents a fundamental change in how financial advice can be delivered, moving from reactive reporting toward proactive guidance that is grounded in trusted data. We also address one of the biggest questions surrounding AI in financial services. Will technology replace human advisors? Bob offers a thoughtful perspective, arguing that while AI can automate repetitive work and accelerate decision-making, qualities such as judgment, precision, trust, and human relationships remain impossible to automate. Those are the characteristics clients ultimately value most when making important financial decisions. As our conversation draws to a close, Bob shares why he believes the gap between firms embracing AI and those delaying modernization will widen rapidly. The organizations investing today in clean data, modern platforms, and AI-ready operations will be better positioned to serve clients, attract talent, and compete in an increasingly fast-moving market. Can wealth management continue to rely on yesterday's technology in an AI-driven world? And if time has become the industry's most valuable asset, how is your business making the most of it? I'd love to hear your thoughts after listening.

Thanks to our Partners, NAPA TRACS, Today's Class, KUKUI, and Pit Crew Loyalty Watch Full Video Episode Artificial intelligence is rapidly changing how consumers search for auto repair services, and shop owners who don't adapt risk becoming invisible online. Carm Capriotto welcomes Heather Myers, Chief Technology Officer at KUKUI, and Connor Tracy, Director of Partner Development at KUKUI, to explain how AI-powered search is transforming local marketing. They separate fact from fiction, share practical strategies for improving AI visibility, and explain why strong marketing fundamentals remain the key to long-term success. What You'll Learn Why optimizing your Google Business Profile remains the most important step for local AI search visibility.How AI platforms like ChatGPT and Google's Gemini use consistent business listings to recommend local repair shops.Why maintaining accurate Name, Address, and Phone (NAP) information across online directories is more critical than ever.How AI now crawls social media platforms for business information and why authentic, human-created content improves discoverability.What "Google jail" is, how AI is filtering reviews, and why violating Google's review policies can seriously damage your online presence.Why review gating and incentivized reviews can put your business at risk.How to use AI effectively by following the principle of "trust but verify."Why better prompting leads to better AI-generated results and how to avoid incomplete or misleading responses. AI is changing the way customers find and evaluate repair shops, but success still depends on the fundamentals. Accurate business listings, a well-maintained Google Business Profile, authentic content, ethical review practices, and thoughtful use of AI tools will position your shop to earn trust, improve visibility, and convert online searches into paying customers. Heather Myers, Chief Technology Officer at KUKUI Connor Tracy, Director of Partner Development at KUKUI, Listen to Connor's other episodes HERE Thanks to our Partner, NAPA TRACS NAPA TRACS will move your shop into the SMS fast lane with onsite training and six days a week of support and local representation. Find NAPA TRACS on the Web at http://napatracs.com/ Thanks to our Partner, Today's Class Optimize training with Today's Class: In just 5 minutes daily, boost knowledge retention and improve team performance. Find Today's Class on the web at https://www.todaysclass.com/ Thanks to our Partner, KUKUI Stop juggling multiple marketing tools. KUKUI's integrated platform delivers 4x better website conversions, automated follow-up, and real-time ROI tracking. Get industry-leading customer support with KUKUI at https://www.kukui.com/ Thanks to our Partner, Pit Crew Loyalty You're probably tired of chasing new customers who never return. We understand. Pit Crew Loyalty ends the one-and-done cycle, turning first visits into lasting, reliable revenue at https://www.pitcrewloyalty.com/ Connect with the Podcast: Visit the Website:https://remarkableresults.biz/Subscribe on YouTube:https://www.youtube.com/carmcapriottoFollow on Facebook:https://www.facebook.com/RemarkableResultsRadioPodcast/Follow on LinkedIn:https://www.linkedin.com/in/carmcapriotto/Follow on Instagram:https://www.instagram.com/remarkableresultsradiopodcast/Join Our Virtual Toastmasters Club:https://remarkableresults.biz/toastmastersJoin Our Private Facebook Community:https://www.facebook.com/groups/1734687266778976Join our Insider List:https://remarkableresults.biz/insiderAll books mentioned on our podcasts:https://remarkableresults.biz/booksOur Classroom page for personal or team learning:https://remarkableresults.biz/classroomBuy Me a Coffee:https://www.buymeacoffee.com/carmSpecial episode collections:https://remarkableresults.biz/collections The Automotive Repair Podcast Network: https://automotiverepairpodcastnetwork.com/ Remarkable Results Radio Podcast with Carm Capriotto: Facilitating Wisdom Through Story Telling and Open Discussion. https://remarkableresults.biz/Diagnosing the Aftermarket A to

È finita l’era dell’elettronica di consumo con prezzi in discesa e migliori prestazioni? La scelta di Apple di aumentare fino al 25% i prezzi dei suoi laptop potrebbe essere l’inizio di un trend generalizzato e diffuso, che potrebbe condizionare le prestazioni dei prodotti e interessare tutto il settore per almeno uno o due anni, spiega Gianfranco Giardina, direttore del magazine digitale Dday,it.I sistemi di AI come i chatbot hanno bisogno delle informazioni presenti sul web per rispondere agli utenti ed è quindi necessario creare motori di ricerca progettati per i modelli linguistici di grandi dimensioni (LLM) e gli agenti autonomi di intelligenza artificiale. Gli strumenti creati per gli esseri umani sono infatti lenti e poco efficienti spiega Antonio Mallia, Ceo di Seltz, startup che ha recentemente raccolto finanziamenti per un valore di 12,5 milioni di dollari.La Commissione Europea ha assegnato ad un consorzio guidato da Domyn una gara per la costruzione di un modello di intelligenza artificiale di frontiera “aperto” basato su oltre 400 miliardi di parametri. Ne parliamo con Luca Antiga, Chief Technology Officer di Domyn, azienda italiana specializzata in intelligenza artificiale.E come sempre in Digital News le notizie di innovazione e tecnologia più importanti della settimana.

Dead On Arrival: What was just Hype and what was just wrong Timing? Some technologies and products get over-hyped, and never seem to come to fruition? Some just come to fruition, but years or even decades later? In this episode of Tech Deciphered, what is Dead On Arrival versus just wrong timing Navigation: Intro The Fork Cold Open General Magic The Metaverse Dead on Arrival The soon to be Resurrected… Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show: Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Bertrand SchmittIntroduction Welcome to Tech Deciphered episode 78, Dead on Arrival. Was it just hype or just wrong timing? In this episode, we are going to discuss two different types of businesses that as an investor, as an entrepreneur, you want to think carefully about. Looking back, you want to understand better what happened. If we take dead on arrival, we’re talking about businesses, technologies that maybe the tech work fine, but actually no one cared about it, no one wanted it. It’s really a mismatch in terms of what consumer want versus what you are trying to deliver. It’s a classic example of a solution finding for a problem. On the other hand, will it happen but not like that, not now? It’s a type of business where we were too early. We tried to make it work, but actually the technology is not ready now, but it might become ready in the future. As an entrepreneur, as an investor, obviously, you want to make sure you are not in one of these two technologies, one of these two categories. But it’s really a useful lesson to learn which situation you might be in because it will help you make better decision and pick better industries going forward. Nuno, what’s your take on this tough analysis?Nuno Goncalves PedroYeah, in hindsight, everything looks like, “Oh, of course, this wasn’t meant to work,” etc. But here we’re going to take a stab, as you mentioned, at things that are just wrong timing. They might have failed miserably in the past, but they might work in the future. The Fork To have this stake on the ground approach to it, as we’ve had in previous episodes, of defining exactly what we think will happen, but just not like that, versus the dead-on-arrival, which is a little bit more of a hardcore view on it. To your point, we want to really split between those two things because in some ways people are like, “Well, are we ever going to go and have different ways of interacting, for example, in terms of input and output, like with glasses or things like that, that really scale to become pretty pervasive?” We probably would agree that, “Yes, that will happen”. Maybe not in the way that we’ve anticipated until now, and certainly it’s going to take longer than we’ve expected. In some ways, the “will happen, not like that” is a little bit like Amara’s law or Nuno’s law, as referred to in the past. We tend to overestimate the speed at which we get to a revolution, underestimate impact. The “will happen, not like that” will probably fit into that. They will have probably bigger impact than we thought they would, but they will just take longer. Therefore, the solutions we’ve had until now are not great solutions. Whereas the dead-on-arrival, we’re saying, “Hey, we don’t think actually this works.” It’s to your point, not solving a problem that actually needs to be solved, or it’s solving it in the wrong way. Yeah, it’s basically an attempt to really frame, if you’re an entrepreneur, if you’re a venture capitalist, if you’re someone who is an angel investor and is looking at the market right now, what things should you put some real money and real resources, real time behind versus not, and really share that with you guys: our audience.Bertrand SchmittCold Open I always like to go back to a company called General Magic, a company that was legendary in Silicon Valley, spun out of Apple in the 1990s. There was even a movie made about General Magic. It’s a company that tried to basically build the first modern smartphone with touchscreens, app ecosystem. The only issue was it was years before the technology existed to support it. But Nokia at the time was less ambitious and more practical with what the technology was able to do at the time. But what’s interesting with this company is that obviously the smartphone was coming, just took 10 more years, 15 more years. Interestingly enough, some of the people in the team ended up being very successful in that exact space. Tony Fadell, for instance, who ended up creating the iPhone, co-create at least, and Andy Rubin, who end up building up Android, selling that to Google and leading the charge with Google Android.Nuno Goncalves PedroYeah, a very successful team. Tony Fadell, obviously, later on did Nest as well. Megan Smith, who was later the Chief Technology Officer of the US. A lot of people that came out of it that did a lot of important things. To be honest, I think a lot of the technology that was developed that was in some way a capacity or that are reused later on by some of these team members. I’m not saying they were infringing on any IP, but definitely there was a lot of reuse of tech. But it was too soon, right? They were doing something that was truly ambitious too soon. But a lot of these principles, a lot of these things ended up manifesting themselves, and particularly in the iPhone later on and in that deployment. Another such example is actually the metaverse. We did two episodes back in the day, a long time ago, on the metaverse. We debunked it a little bit. Back then, I think it was a very nuanced debunking, if I recall it correctly, Bertrand, because we were saying, “Hey, it’s going to happen in some ways, but it’s an evolution, not a revolution,” not in the way that we saw definitionally. We were huge fans of Matthew Ball and his analysis around media, but somehow we disagreed, I remember, with his definition of what the metaverse is and how it will look like. There’s no doubt that there’s going to be a metaverse in the future, probably metaverses in the future before there’s any given unification. In those metaverses, we do believe. But this whole hype cycle around metaverse and what’s happening clearly didn’t work out well, as proven also by all the write-offs done by Meta on their metaverse stuff. That much must have hurt. It’s related to AR and VR as well and to the enriched reality positioning of a lot of these technologies, which we’ll talk about later. But, again, it was probably something that’s going to happen. It’s going to happen likely in a different product manifestation as the one that was anticipated by a lot of the pundits that opined on what’s happening around metaverse in the future. But it’s going to happen. It’s just going to take longer. It’s going to probably come from angles of entry that are likely not what people had anticipated earlier on. Maybe it’s from gaming, maybe from something else. But definitely it’s going to happen.Bertrand SchmittYes, and you could argue that Apple did a similar mistake with the Vision Pro. I think the Vision Pro is the worst launch of an Apple product. When we say launch, it’s been three years maybe?Nuno Goncalves PedroSince the Newton, maybe?Bertrand SchmittYes, that’s my point. You have to go back a really long time to have such a disastrous launch. I think for me, it’s very interesting because it’s really a category where on one side there is a metaverse of some sort. You should argue if you are just using Twitter, or Facebook, these are some parallel universe in parallel to your real life. But the full on metaverse where you need some extra super heavy glasses to make it work, that simply has not worked. Don’t get me wrong, there are some super small, narrow cases where your heavy VR glasses makes sense for some training, for some simulation, for some light gaming. But given the weight, the disconnection from the real world, it has really never taken fire. Even at cheaper price like Meta was able to do, at more expensive price, much higher quality like the Vision Pro did. It looks like people have an issue with putting heavy glasses on top of them. We’ll talk later about the other side: AR glasses. But the traditional metaverse, heavy glasses, VR glasses, yes, it’s not feeling right, and I don’t think it will ever be right. It needs a different form factor to go at scale.Nuno Goncalves PedroDefinitely fundamental shifts on the metaverse. Just a quick reminder, Meta actually changed their name because of metaverse.Bertrand SchmittYes. Nuno Goncalves PedroIt’s not just that they’re writing off the investments, it’s their name is apparently wrong. It didn’t really happen in that way. You are saying that this persistent embodied virtual world, which was the early definitions of what a metaverse was, didn’t really happen until now. It might happen at some point, but not in that way. But, obviously, a lot of the enablement layers are still work in progress, right? Real-time 3D, presence, avatars, all of these things are moving on. A lot of these enablers will be ready once there is a time where these technologies and businesses that are fundamentally anchored around these technologies will emerge. It’s, again, right components, wrong product alignment, but at the same time, it will happen, just not yet.Bertrand SchmittAgain, I think we’re going to face a split of a virtual reality light that you can call AR with very light glasses that are not a pain to wear, that are more limited, especially today or the next 5 years. The VR glasses that will stay a niche product that are useful for some use cases. Do you want to do a flight simulation? You want to do military training? There will be use for that. But beyond that, it’s more limited. We forgot to talk about the Google Glass. This one was an early, early AR glasses. But, again, here we go back to the capabilities. Simply, we were not there at the time.Nuno Goncalves PedroDead on Arrival We’re moving to Dead on Arrival. What things do we think are relatively dead on arrival? We’ll be nuanced on a couple of these aspects. Not everything is totally dead on arrival. But maybe let’s start with a good one, which is some of the crypto summer promises, particularly around NFTs, non-fungible tokens, and the decentralization of everything, the tokenization of everything. That didn’t quite work the way people thought it would. A lot of people were very happy for a period of time that they had some NFT that was worth a ton of money. Good for them. I hope they sold it back then. Some did actually, fortunately for them, but most of them did not. As an asset and the tokenization element, we’re not questioning that tokenization itself doesn’t make any sense. But from my perspective, a lot of the elements of tokenization plus the tokenization of everything don’t make necessarily imminent sense. I think we’re going to have a world that not everything is going to be tokenized, and a world where, to be honest, having the latest ape token as an NFT is maybe not something I really need. It’s dead on arrival in some ways. What do you think, Bertrand?Bertrand SchmittIt feels like it’s a tale of two worlds. On one side, there was clearly exuberance and bullshit. All these cryptocurrencies that make no sense, have no values. The NFTs are the same: no values, no sense, no logic in them. At the same time, we can see that Bitcoin, Ethereum, and few others were significant products, invention, that have a current total market value that is significant. I would say we can see that step by step, little by little, there is some tokenization happening, but it has been much more narrow than what was initially thought, expected. But it’s happening step by step. I think there is value in tokenization, but definitely not as much value as people expected. I think for one simple reason: it’s very expensive to set up in the sense that it doesn’t work so well, actually. It requires a lot of computing power for stuff that might not justify it as simple as that. Why do you want to replace a very efficient, superfast database by something slow, expensive to maintain? Why? You need to have real reason for that. I think in most situations, there was not a real justification to make that switch. I think, again, there is a niche for tokenization. It’s getting used. Obviously, there is stablecoin as well that are working and provide value. But definitely, the use cases have narrowed. The success stories have been few and far between. It’s definitely a space, but I don’t think it has lived up to the expectations. The expectations were simply quite insane in terms of what to expect, and it failed to achieve that. I don’t think it qualifies as a true revolution. It has been successful again in our situation: in Bitcoin, in Ethereum, in some tokenization. But beyond that, it was not the dramatic change that people were picturing.Nuno Goncalves PedroYeah, it’s been successful and there is a security, in this case, a currency of types, that links to the value of that specific network and the utility of that specific network. But on this case, in particular, the NFT stuff, I think there were two core premises that were very valuable about it. One was the premise of digital collectibles, the element itself being collectible and the fact that I have a unique one was only minted one. It’s a unique thing out there. I think at some point people forgot that actually digital collectibles are not as valuable as people think they are. Physical collectibles are more valuable. The reason for that is just human nature. I want to have something in physicality. I want to have something that I can show people, etc, that has a physicality to it. Digital collectibles, I think there was a problem fundamentally in part of the articulation of NFTs that reside in the value of digitization of these collectibles in and of themselves. I think that was part of the problem. The second problem was really the notion of provenance, the notion of certification, the notion of “this is what it says it is, and nobody can say this is something else.” This notion of provenance. That, I think, fits more into the point you were making, which is the point around use cases. This doesn’t fit all use cases. The provenance piece and the certification piece doesn’t fit for all use cases. Probably it might fit actually even more for actual physical assets where you want to have a certificate, that thing is what it says it is, but it’s actually maybe a physical asset rather than a digital asset. Again, lo and behold, it doesn’t apply to all the use cases that relate to provenance. I don’t think we need to tokenize all the provenance ledgers in the world for this to be working well. Again, it was a little bit of an overreach. In some ways, all these players were very happy. There was a lot of bullshit. To be honest, this is an area that I do think there was actual active fraud. All due respect to a lot of the players in the market, but there was active fraud. Honestly, there was bullshit.Bertrand SchmittI agree with you. I was going to say that it’s one of the rare sector in technology where I think frauds, scams were prevalent. Yes, you might have some shitty startups in general and stuff, and there might be fraud. I think true fraud is rare. True scam is rare. But here for NFTs, for cryptocurrencies, that was the majority you could argue. That’s the part that I never really liked in all that industry. If you look at NFT, personally, I never understood the concept. For me, it made simply no sense because, yes, you can say, “Oh, I have created this rare digital token.” But sure, so what? Who cares? Who cares? You can have hundreds, thousands, millions of unique digital tokens. How does it matter? What’s the use case? What’s the connection? You can show it on your screen, but then how is it unique anymore? It’s not like people have to come to your house and check stuff on site or something like physical art. No, not at all. I don’t know. I think it was surprisingly true bullshit. Again, I’m still a believer in Bitcoin. I think there is true logic to have a separate virtual digital currency. But you don’t need hundreds of them. You just need one, maybe two for some variation. The same for tokenization, it doesn’t need to happen everywhere. Just need to happen where there is really strong real logical value. Beyond that, there is no point.Nuno Goncalves PedroYeah, makes sense. Maybe moving to our next one. I think we discussed this in a previous episode, which was the whole 3D TV stuff. We just don’t think that’s the product, right? It’s not going to be a 3D TV. I believe when we discussed this in the episode—I don’t want to lie too much—but I believe that’s what we came up with… It looks a bit more holographic or the manifestation comes through other mechanisms like glasses, etc. But we thought it was just dead on arrival. Nobody wanted to have glasses on the couch to watch the 3D TV, but also the 3D TVs themselves they tried to develop were very holographic, were super clunky and very heavy. In some ways, I think TV manifestation somehow is not a great manifestation for this. I put it on the dead-on-arrival pile. I have one, just to be clear. I still have one.Bertrand SchmittYeah, but it’s a weird one because if you remember, it suddenly happened. I remember being shocked as a consumer. Suddenly everyone talks about 3D TV. In a few months, 3D TVs are all out everywhere. Then after a few years, no one bothered to keep adding that because consumers didn’t care. I think one issue was, I think it has only worked with Blu-rays. I don’t think any streaming service supported that. With the rise of streaming, that was certainly a pretty big issue in the first place. Interestingly, in the movie theaters, do we still have movies being shown in 3D? I think we still have a few, but it’s really few and far between the movie theater.Nuno Goncalves PedroYeah, IMAX won on that format, the high-end format, IMAX won, not the 3D thing.Bertrand SchmittBut, yeah, if you’re on the TV at home, you don’t want to bother. Maybe if you’re in the movie theater, more high-end experience, you are willing to wear special glasses. I think it makes sense. I think, I guess at home, we are just too busy doing multiple things at once. Rarely sitting all around 2 hours for a movie, so you watch your phone, you check on something else. You don’t want to have these glasses on top that block you from the rest of what’s happening at home.Nuno Goncalves PedroYeah, it just didn’t work. I’m not sure it will work in any case, so we’ll see. But definitely, I don’t think that’s the right form factor.Bertrand SchmittIt technically worked, but practically, it was not accepted by consumers.Nuno Goncalves PedroLet me rephrase. I think it was a solution to a problem nobody thought they had. The execution of the product was the wrong one. It’s like that’s not what people wanted. Maybe we do want some 3D immersive experience, but that’s not the 3D immersive experience that we want, not manifested like that in effect, with its limitations, etc.Bertrand SchmittI want to say that we are not denigrating some of these experiments. Me, I still remember putting a Vision Pro and watching some content that is natively created by Apple for the Vision Pro. It’s an amazing magical experience, truly. But at the same time, I’m always worrying to have to think I’m going to spend 30 minutes putting my Vision Pro on my head. It’s heavy, it’s painful. Again, we go back to, I’m disconnected from everything else, and I don’t like that.Nuno Goncalves PedroWhen there was real technological development, like the case of 3D TVs, that technology development may have served other purposes. Again, we applaud those that put the money where their mouth was, the companies, the individuals that wanted to move forward some of these technology stacks, maybe less so the people that just decided to create NFTs for the sake of it with apes. No attack on those guys specifically, but just to create a specific view on that. But there’s a lot of stuff we’re talking about today which is actually great technological development. There’s stuff that came out of it that is very, very valuable technological development. Maybe to our next one on mobility, physical mobility. The Segway. Everyone’s like, “Oh, this is going to change how we move around the world, in particular for shorter distances, etc.” Well, apparently no. Apparently, it’s not super intuitive. There are still Segways out there for use by police forces, tours, and all that stuff. People say, “Oh, it’s…” No, well, it never scaled. It wasn’t changed. It didn’t change how relatively short local mobility was going to be done. I think part of it is actually the problem with the product. The product is not as intuitive as people thought it would be, and it has other issues around that in terms of security and safety. If you’re going to have a device or something that moves you around, what’s the minimum-accepted level of security that you would have. The fact that you have to incline to move it is actually not super as initially some probably people thought it’s actually not as intuitive as some might have thought it was. I think it’s a dead-on-arrival play. The vehicles of the future, I’m not sure, look like that at all. Happy to eat my words down the road, but I don’t think so.Bertrand SchmittYes, and I remember the massive hype at the start of this product. They were hiding it, but still telling you, We have seen it. That’s true. It’s going to totally change how cities are planned. I mean, the level of hype and bullshit was insane before the launch of the product and before anyone outside of a few knew what it looked like. Then we saw what it looked like, and it was on one side, an engineering marvel, the self-stabilization system was new. I mean, very few people had seen something like this before. At the same time, as you said, the issue was what happens if it loses battery? What happens if you fall from it? Quite frankly, if you look at today’s modern electric scooter, you have 95% of the value of a Segway without any of the downsides. You don’t need to learn a new way to do things. If you lose battery, it still works. I guess you can still push it. It’s not too expensive. You don’t have massive computers to just make it work. You don’t have massive robotics. It’s clearly an impressive engineering solution. But the exact example of a solution to a problem people didn’t have, when ultimately a much more simple and elegant solution was there for people who care. To be clear, you still could use a regular bike. The alternative was still your regular bike. But now you have electric scooters that are a clear, closer alternative, I guess, in spirit to what was supposed to be the Segway. Sometimes, let’s be careful. Overengineering might not be the answer.Nuno Goncalves PedroEven scooters, which are, to be honest, I would argue a much easier philosophical view of how mobility should be done and a much easier form factor, so to speak, in terms of mobility, even those won’t have wide adoption to everyone. It’s not like everyone’s going to use a scooter. The bar for a scooter is much less than a bar for a Segway.Bertrand SchmittYes. I think in a way, the electric scooter is showing us in some ways that the limit of the dream is that even well-executed, even cheap, even easy to use, even low-risk in a way, there is still only so much that people are willing to use it because it’s a pain to bring with you everywhere. Actually, in some ways, you could argue it has only worked with this distributed platform, like lime and others that let you take one and drop it when you are done using it. But that was not a model that was workable for the Segway. I totally agree. You could argue that bikes are still the gold standard or now electric bikes are still the gold standard for who want that level of mobility.Nuno Goncalves PedroWell, the next one is to be a favorite of, I guess, everyone that didn’t invest in them, which is Juicero, which was the machine that basically created Juices out of squeezing a bag. I’m going to be nice here to… There were a bunch of well-known investors. They raised, I think, 120 million or something like that.Bertrand SchmittThat’s insane.Nuno Goncalves PedroIt is insane. But maybe the vision was not that vision. It was something grandiose and the complexity around dealing with liquids and whatever. I’m not really sure we didn’t pass or invest on the company.Bertrand SchmittBig old juice bags.Nuno Goncalves PedroMaybe. You’re being facetious. Anyway, I’m not trying to attack the guys who actually invested in this, the investors that put money into this. But it was basically one of these examples that we’re trying to solve a problem that didn’t exist. It’s like a solution for a problem that doesn’t exist. I can just squeeze a bag of concentrated thing and make a juice. I can do something around the juice. As I said, maybe the big vision was well beyond that, and I’m not sure many of us will ever know what the big vision actually was. But yes, it was a solution, a $400 machine to a problem that nobody really had. That didn’t work.Bertrand SchmittI think the most crazy part of the story is that the business exploded when there was this Bloomberg reporter that showed that you could squeeze the bag with your hands without a machine and get the same juice. That’s pretty insane. That’s just so unbelievable.Nuno Goncalves PedroThe funny part of the story is MSCHF, this company that does all their on-point, slightly artistic, whatever, one-off, drops, etc, etc. Shout out to Gabriel. Gabe Wally, who was the founder there. This is funny. They actually did a collectible series of figurines of that startup toys, of which Juicero was one of them. Jibo, which I don’t think you’d appreciate. Bertrand, and the Theranos minilab. So someone is also making money on that, which is funny. So well done, MSCHF.Bertrand SchmittWhy not? Why not? Maybe we can go quickly over Lytro. This one was, I would say, brilliant technology. It was a camera able to capture light in a different way. You could actually dynamically change focus after the picture was taken. So something quite impressive, and I still remember looking at their products and thinking, should I get one? At the same time where it didn’t work, it was too limited in terms of image quality versus shooting the real picture. It was very tough to sell as an independent device because either you’re in the phone or you are in a DSLR, but there was no spot in between. In some ways, phones solved the issue not directly, but they kept adding cameras. At some point, you had not one, but two, but three, but four, but five cameras in your phone. You had a specific mode for anything you needed, and that’s it. Phone manufacturers managed to convince people they should pay for all these cameras, or provide a low-end version if you don’t want to pay for all these cameras. But yes, very interesting technology that did not manage to find a go-to market.Nuno Goncalves PedroYes, it’s falling in love with a technology solution that, as you said, was incredible, and not falling in love with what problem you are actually trying to solve. Because a lot of the elements of the problem that you’re trying to solve, either you take another picture. All due respect, instead of me trying to change the field of view, etc, and the focus, post picture taken, I take another picture. To be honest, you can take thousands of pictures now with different setups. Also, ignoring the fact that this was pre this whole AI boom. So obviously, that one I will be kind on. But with the AI boom, you can do a lot of things to pictures and changes and stuff like that. All of that changes the game in and of itself. Obviously, Lytro or Lytro, not sure how you spell them, or how you say their name, but they failed before that. So again, this was super great tech, great investors, good investors on board, but just nobody wanted that device. Why would I want this thing? A total failure on arrival. I think one also other aspect of it that may have been misinterpreted and underestimated by some of the early investors, certainly in the company, is the value chain. There is a value chain for cameras, for SLRs, DSLRs, etc, etc. They know what they’re doing, and they’re doing their own level of innovation. In some ways, that fits squarely into that value chain, which I’m sure is a complex value chain to manage in and of itself. Maybe that’s created its own dynamics as well.Bertrand SchmittI think they try to insert themselves in the value chain, but I’m not sure first that they managed to get technology as small as it should have been. They simply didn’t convince anyone. The Sony or Nikon of the world, or the Apple or Google of the world, to use their technology in their phones, because no one really saw the value, per se. One thing to keep in mind, using their technology means you had a big trade-off in terms of megapixels. Actually, you will benefit from that great effect around the focus that can move anywhere after the fact. But in exchange, you had to lose dramatically the number of megapixels. At the time, all the rage was about how do I get more megapixels for my phone with good image quality. That was all that you were selling to consumers. Consumers would not have bought 10 times less megapixels for a weird benefit that at the time no one cared about. I think you are very right to introduce the fact that, of course, they could not have guessed at the time, but today you can get for free this refocusing effect with AI, actually.Nuno Goncalves PedroThat’s exactly the point I was making on the value chain. They went into a value chain that has a lot of players in it, and they got kicked in the butt anyway, because people were like, Why would I adopt it? They didn’t serve the purpose of the use case or the user flow. They didn’t anticipate competitive dynamics to it. Then they actually went straight up into a technology plus IP logic on a value chain that would be like, “Hey, dudes, just get out of here.” What would be the incentive for people to bring them on board? It’s like in some ways, they did all the mistakes under the book in that sense. Again, I’m not trying to diss the company, the founders, the investors, but it feels that was the problem in the end.Bertrand SchmittYes.Nuno Goncalves PedroShall we do some rapid fire dead-on-arrivals?Bertrand SchmittYes. A fan favorite. Have you tried a keyboard projector on?Nuno Goncalves PedroYes. I think I mentioned that in a previous episode, I did have one of the early ones and whatever. Yes, somehow we forgot that there’s other best, better ways of input, maybe voice would be a better way of input if that’s the problem, but anyway.Bertrand SchmittThis one is interesting because you just use it for one minute, and you discover it’s horrible.Nuno Goncalves PedroIt’s a horrible experience.Bertrand SchmittYou have to type on it. You don’t see exactly where you type. Each time you type, you are hurting your fingers because it’s not a smooth keyboard feeling, but you are tapping a solid surface. That’s amazing that it went to manufacturing, and basically no one gave feedback. There is no way it’s working. No way technically working, but practically, no one would want to use that.Nuno Goncalves PedroIt’s bad in all aspects. The finger’s touching. It needs to be a very over-engineered experience for it to actually detect the key stroking and all that stuff. It’s an over-engineered solution by default. It’s not private because once you have the keyboard projector, you’re like, “Where am I keyboarding projecting on?” It’s something that others can see. There are other alternatives that are better. The keyboards on our phones are pretty good these days, with autocorrection in most cases, I wouldn’t say all cases. Voice can also be an interesting replacement to that. If that’s what you’re going for, voice recognition has improved dramatically over the last few years. Again, it’s one of these, “Yeah, cool.”Bertrand SchmittIt’s clear that, first, touch has replaced a physical keyboard where you need one. And two, now voice recognition is getting better for sure.Nuno Goncalves PedroThe opposite side is that voice assistants were going to take over everything, that everything was going to be voice assistant-led. Alexa is going to run your life. You’re going to have games for voice. I actually have a good friend of mine who did a startup in that space. Actually, the company got acquired, and everything’s going to be voice, which, as we know, is also not true. We need to visualize sometimes. Sometimes we still want to write because we want either the added value of privacy or of expression at some standpoint. There are a lot of things that are happening around voice that are exciting. We just mentioned voice recognition, but not everything is going to be voice. Certainly not for the foreseeable future, and so that doesn’t work. Also, as the ultimate platform, we also want some visuals. We also want to have other kinds of interactions. There are limitations to voice assistants, for example. Voice assistants were not quite the next platform that people said they were going to be. I would say they’re a channel, but they’re definitely not a platform. That’s how, at least I see them.Bertrand SchmittYes, a channel versus a platform. I would agree with you. I must say I start to feel that we could be close to the future we have seen in Her. This movie, Her, I guess you saw it as well, where these guy keep talking to his personal assistants, and it’s becoming his friend, maybe even his love. I start to feel we are getting close enough with AI that this becomes a possibility. But again, it’s not your only way to interact. You want to type, you want to see stuff. There are many situations where you don’t want to be seen talking with someone. It’s more of a channel versus a platform. Yes, Alexa, it’s quite amazing how it went to the roof and crashed and burned. It moved up very quickly. Amazon invested billions, hired thousands of people, which was the right move. I mean, you have something that seems to work well enough and could be game changer, why not? But it was quite impressive as a crash and burn. It’s pretty rare to move that fast up and down.Nuno Goncalves PedroI agree. A lot of money is put into this stuff. I mean, Google went after it as well. I think Google probably executed better. Their tools and their hub tools, etc, were better in their devices. But to be honest, it was the beginning of something, it wasn’t really there. It’s shocking because a lot of people have Alexa at home, and Google Hubs at home, and whatever at home. But it’s really not that powerful. I have a bunch of Google stuff at home, and I still use it for very basic information. It’s not really doing much for me. It’s not like magically now with AI, it’s going to be much better. It’s not. It’s a legacy device now. Maybe in the future, we’ll have some stuff that will be cool, but definitely not the voice assistant manifestation that we saw in the past. I know the next is exciting to you, so I’ll let you go for it, Bertrand.Bertrand SchmittNetbooks. If you remember Netbooks, this was a horribly underpowered PC device. I kept buying one after the other, hoping that the next one would be fast enough. Trying to be a small, lightweight portable PC, they were called netbooks. Usually, they also had a small screen, like 10, 12-inch, 9-inch, and each time it was horrible. Very poor battery life, 2-3 hours, super, super, super slow. They were equipped typically with a full Windows OS, and they were killed overnight by the iPad. After 2 years of the iPad, no more netbooks. Oh, yes, and they had this… Typically, they would be equipped with… What was this name of the CPU? It was an Intel Atom CPU, I believe, or Celeron. Again, the root cause why, it was so slow. It was horribly slow.Nuno Goncalves PedroSo netbooks didn’t work. We didn’t want to go back to that. The iPad won and all [inaudible 00:34:05].Bertrand SchmittI think it has been proven at this stage. There are some small mini PCs these days. You have, for instance, the ROG Ally for gaming. There has been some revival with some Chinese manufacturers making some small PCs. I have to admit, I bought some, so I kept trying. It’s much more powerful, no question. Better battery life also. But we go back to the fact that if you have a very limited screen size, 7, 8, 10 inch, it’s just tough to put a full desktop operating system to good use. You need something more simplified, more touch friendly for it to be really practical. Yes, you can run the full desktop Excel on it, but will you do it on an 8-inch screen? Probably not.Nuno Goncalves PedroNetbooks, and maybe we’ll end with Google Glass. I mean, obviously, we’re going to talk about AR and VR in just a bit. I think it’s a good segue to our next section, and we’re not necessarily saying AR, VR is dead on arrival. We actually think they’re going to be out there for us in the future. But Google Glass, in the way that a lot of the first wave wearables were developed, was cool, but not enough. I think even the recent ones, the Meta Ray-Bans. I see a lot of friends of mine now, you’re wearing Meta Ray-Bans, and they’re like, “Oh, this is so cool”. It’s like, “How is that different from the Google Glass, but now a little bit nicer?” It still feels to me that’s the wrong way to approach it. Either we go with a more comprehensive solution for glasses or a solution for glasses that’s a little bit more easily integrated into existing frames, etc, for those of us, like the two of us, who have actual eyeglasses, or I don’t see it quite happening this way. I think just as a formality in how it was deployed, it seems to me it’s been the wrong angle a couple of times, even, to be honest, beyond the first wave of wearables. It’s been a little bit the wrong way to approach this, the wrong paradigm.Bertrand SchmittIf you remember the Google Glass, initially, they were launched in… Again, overhyped. You couldn’t even buy them, but still, it was overhyped. You could see a marketing department going crazy when they were showcasing models wearing Google Glass, that sort of stuff, fashion shows. That was insane. How is it connected to the value proposition of the Google Glass? Absolutely not. But you remember what killed the Google Glass?Nuno Goncalves PedroThis is the Robert Scoble in the shower thing. The whole lack of privacy thing.Bertrand SchmittYou tried to have this vision of the Google Glass that models are wearing and stuff in fashion shows. You have this guy, Robert Scoble, taking his picture with his Google Glass in the show, half-naked. Oh, wow, that quickly dropped. In the interest into Google Glass.Nuno Goncalves PedroRobert’s a good guy for the most part, so we’ll let him get away with it. But yes, it was not a good moment for the use of Google Glass. But to your point, it was overhyped. I don’t even recall that I had to do so many things to actually get access to one. I still have it. Then in the end, it was just totally underwhelming. I do think the meta Ray-Ban solutions, etc, etc, now they’re doing it with other brands as well, are more elegant because it’s around voice activation and stuff like that. But still, it’s not this. The soon to be Resurrected… I think these kinds of solutions are dead on arrival, which may be a good segue to the resurrection pile, so to speak, that will happen, just not like that pile that we have to share today.Bertrand SchmittYes. That’s the question. Are we in resurrection mode with AR glasses? The Ray-Ban, Oakley glasses, are the way to go? There are also some other brands like XREAL, for instance, that are a different approach. It’s more fun to watch movies that I personally like a lot and use a lot. I know quite a few fans for this. There is a market for either the XREAL for movies, meta, or Ray-Ban, for light information on top of your glasses. There are niches. I don’t know if it’s full resurrection mode yet, but I can see again, with AI, that there is the ability to do more and more. Will it be connected to your phone, will be independent from a phone? That’s also stuff to see. I guess at this stage, connection to a phone has some value. It’s making a comeback.Nuno Goncalves PedroI think it’s suffering from being overhyped. It makes sense that the category comes back. The use of glasses, a lot of people actually have eyeglasses. The use of different mechanisms that really expand your view. We’ve seen that with the advent of foldables in mobile phones. People want bigger screens. They want to get as close as they can to the tablet experience without necessarily having to go to laptops, etc. Definitely, I think the use cases make sense. It’s just how do you deploy it, and who’s going to deploy it best? I don’t think we’ve seen anyone that’s been particularly enlightened about doing it. All the great developments with Android XR from Google, Samsung doing a bunch of things in terms of deployment out there as well at the same time. I mean, are these guys going to redefine this category and create the first ever wearable, at least AR great experience or VR category of experience, or are we going to have much of the same? In the same way, it took several years for the smartphone category to be recategorized as a smartphone category under the iPhone. That was the category-defining moment. It was the vision of a bunch of people, obviously led by Steve, but a bunch of people that went to market and said, This is how we view the market to be, and they just nailed it. We haven’t seen the guys who’ve nailed it, I think, is the issue thus far, either on the VR side or the AR side. We just haven’t seen it.Bertrand SchmittDefinitely, we have not seen that. There are, of course, rumors that Apple is ending their Vision Pro program, and at the same time, is full-on on AR glasses, an alternative to the Meta Ray-Ban. We will see. I start to think I have trouble to see Apple pull this off because it starts to feel that, yes, they are great at making more efficient supply chain these days, but I feel after 10 years plus of Tim Cook leading the business, that’s all there is to Apple these days: thinner phones, pink colors for your latest device.Nuno Goncalves PedroVariations.Bertrand SchmittMore efficient chips, for sure. They have great chips. But beyond that, they canceled their car program, the Vision Pro was not successful in the marketplace. They have trouble to find the next story and to execute on the next story, quite frankly. You could argue that their most successful recent launch has been the AirPods.Nuno Goncalves PedroI think that’s absolutely spot on. We’ve discussed it in previous episodes how much… It’s taken much longer than I thought it would. I always said after Steve’s passing, that it would take maybe 5 to 10 years for the beginning of the demise of Apple, and it is taking longer. There was definitely some gravity created. Steve passed away in 2011, right? They’ve been hanging on to their time, so it’s now 15 years. It seems that only now Apple is really suffering in terms of product lines. Probably they started 1 or 2 years ago. They have a new CEO coming in September, so we’ll see if John will do a better job, if he’s really a product guy, and that’s how he’s going to go for it. He’s going to go for a few products really nicely done that can have great experiences, which is Steve’s hallmark, instead of what you said was the milking of the cow, so to speak, under Tim Cook. There’s nothing wrong with it created in a hugely valuable company with a huge amount of still innovations around the edges, but it’s like now they need real product innovation, a new category definition, play, and is John going to be the guy for that or not?Bertrand SchmittYes. Positively, Tim increased market cap of Apple. He didn’t destroy the business. We are not trying to tell that Tim Cook was a failure, but definitely it was not Steve Jobs. It was more a caretaker, optimizer type of CEO. But to go to the next level, you need another type of CEO. Quite frankly, it’s hard to find when it’s not a founder CEO.Nuno Goncalves PedroYeah, I think it will be difficult to find, but we’ll give John a chance once his time comes in September 2026, as one would. Moving to another topic that we’ve discussed in the past, self-driving. It’s going to happen. We all are waiting for it to happen. Self-driving cars, self-driving vehicles that we don’t need to drive in this mess of traffic, in particular spending a lot of my time in Southern California where traffic is incessant. The driving is… How can I put it in a nice way? Awful. People don’t seem to know what they’re doing. I think we all want to have self-driving cars. It’s taking longer than we thought it would, but I do think it’s going to happen. I wouldn’t put a mark on the sand on how long to get this world of self-driving cars. It’s going to coexist with non-self-driving cars for sure for a period of time. But I, for one, know deeply that it will happen, and I look forward to it. I love driving, but not in horrible traffic with horrible drivers.Bertrand SchmittWe are for sure very close. I mean, now, Tesla self-driving is extremely good. I have taken Waymo many times with great experience. It’s not going too fast, it’s not going on the highway, so there are some limits. But I would say really impressive all in all. I think we are pretty close. I don’t know if you know, but Waymo is working on expanding to many, many more cities, actually. I think we might be at a tipping point there. Quite frankly, I expect that teenagers in 10 years from now are not going to bother to learn driving. I mean, we’ll see, but I think many won’t.Nuno Goncalves PedroI mean, Waymo is now doing also stuff on freeways, certainly in the Bay Area. I had a friend of mine who took one recently, and he was scared. He was scared shitless—I think that would be the right way to put it—because the car wasn’t going that fast, people are aggressive on the freeway around your car. But to your point, I’ve used it in city. In the city, it’s great, and it’s aggressive enough. That’s one of the things I was a bit afraid about Waymo, that it wasn’t going to be aggressive enough in city driving, it is pretty aggressive. Yeah, maybe we’re closer than we think. Maybe it’s a couple of years rather than a decade, which is normally where we put the stake on the ground. But it’s definitely going to happen. I think there was an overhype too soon. There were great movements around level 3 and level 4 autonomy that in some ways were misconstrued early on as full autonomy. But now we will likely get what we ask for. Then at some point someone’s saying, “Hey, but why don’t we just have the flying objects instead?” We’ll get back to that. The flying car stuff, the eVTOLs and all that stuff, we’ll see.Bertrand Schmitt10 years ago, I remember the overhyping was very, very strong with self-driving. I nearly believed the bullshit. It was so strong in 2015, 2016 that nearly everyone thought it’s here in the next 12 months, basically. I think that was a lesson for quite a lot of people. Don’t trust the Silicon Valley bullshit machine, hype machine. It can go way too strong, way too fast. You absolutely need to spend time to understand realistically where we truly are. You cannot just buy the premise.Nuno Goncalves PedroMoving maybe to robotics and humanoids. Again, it’s going to happen both for consumer and for industrial. The humanoid form, I think, at some point will be important. Just not yet. I think we’re behind now the big buzz sentence is embodied AI, where you have physical AI manifestations. AI manifested through robots and other kinds of devices. It’s going to start happening in certain beachheads. But, hey, we’ve had this offer for a long time, and I know you still have your frustrations, Bertrand, with the Sony AIBO. I won’t traumatize you more than that, but definitely it will happen. We will have humanoids at some point. We’ll have different specialty devices that will help us in activities that we do both as consumers and also in the B2B and enterprise space, even in the industrial space. The writing’s on the wall that definitely is going to happen.Bertrand SchmittYes. I think the question, as always, is how do you get there? I think the intermediate steps of your optimized robot, a physically optimized robot, like a Roomba to clean your home or some other robots to mow your grass, a good example, I think initially you have to start a small, practical, not too technology advanced and progress your way. Truly humanoid robots are very disruptive because technically, if they work, they can do everything a human could do. But practically, I don’t think it’s that true because a lot of constraints. You have to have enough weight, you have to have enough force, you have to have enough vision, you have to have enough AI to just understand commands and move around. But, again, with all the progress in AI, the progress in electric motors, I am optimistic that there is a chance for the humanoid robot, but it’s not 3 years. It’s probably not even 5. It’s probably more like 10. Let’s not forget that a lot of demos with humanoid robots today are fake. It’s a remote operator, remotely controlling a robot. It’s not a robot working by himself in many, many, many situations. That, I think, is another thing hurting the reputation of some of these companies because these fake demos, they look great, but once you dig a bit, you realize it was a fake demo because it certainly didn’t come with a warning that it’s remotely operated.Nuno Goncalves PedroMoving maybe to the next one that it will happen, but not exactly like that. Quantum computing, I think for the most, it’s been in many cases a solution looking for problems. It’s beautiful, but it’s like, “What’s the problems we’re trying to solve?” I think we’re going to start having beachheads into problem solution and apps. I’m sure a lot of people out there would say, “Well, there’s already killer apps for this, a lot of the scientific modulation, cryptography, breaking, all that stuff.” But I’m like, “Yeah, cool.” It still feels very much like a bunch of pieces and hardware in effect that is trying to solve a problem that needs to be very much defined into several problems, several areas of problem solution going forward. Will it happen? For sure. I’ve been hearing about quantum computing since I was in college, since I was 17 when I got into college. I’m sure it will happen. It will have manifestations. There’s a lot of stuff probably already residing on some of these instances. But a full mainstream view of what quantum computing can do for us is still quite ways out.Bertrand SchmittYes, I mean, there has been some reports that some key steps in the technology starts to be working and that potentially the technology could start to deliver results in the coming 2-3 years. What I mean by results, results that will dramatically change how you need to encrypt because a lot about quantum computing is actually trying to decrypt the current technologies that are used to protect your information online. This one is big. If we manage to have a limited use of quantum computing things that work in a few years, that will have a dramatic impact on how we encrypt data. That’s the one piece I’m looking for: do we really manage to solve encryption with computing? If yes, then we need to make a lot of changes how we encrypt things.Nuno Goncalves PedroFusion energy, the gift that keeps on giving, but this somehow doesn’t fully happen. I know you’re a big fan.Bertrand SchmittI would say, practically, I’m a big fan of nuclear fusion energy because in a way, it’s working. It’s solved in terms of safety. Latest Gen5 reactors are ultra-safe. They cannot go out of control anymore. China has a working reactor. In some ways, part of me would say, “Why bother with fusion when we have fission that is working extremely well, and we know how to make?” If we are efficient about the process, we could make for really cheap. Having a better source of energy today will already be great for the world. I would like to see scale with fission. It’s great to research fusion. Fusion is near a limitless form of energy. This is exciting. I think what’s interesting with fusion these days, it’s not just the big governments working on spending billions before seeing any potential returns, but there is a lot of startups that are working on it. The bar went lower in terms of researching fusion. That part gets me excited. But again, I think we should go fission first and parallel with some fission investment, fusion research, and hopefully, fusion comes at some point, but we should not wait for fusion would be my big take.Nuno Goncalves PedroGood point. Last but not the least, we’ve dedicated episodes on this, so maybe today we’ll just do the little teaser. If you guys haven’t heard our episodes on AI and the bubble and all those things. The last big one that’s just not like that, it will happen is AI itself, and in particular, AGI, so generalized AI that will be just like a human. Obviously, it’s happening. We’ve discussed in previous episodes, there’s a lot of breakthroughs in terms of methodological approach beyond the GPT curse of actual hallucinations that doesn’t seem to be solvable. There’s a lot of things happening around reinforcement learning, evolutionary computation, and other methodological approaches to AI that we think will create tremendous breakthroughs. There’s definitely a lot of funding going into it. We quantified it recently. I think 63, the number probably has changed in the last couple of weeks, but 63 new AI labs that have raised significant rounds upfront, just getting into the market, some of them as high as hundreds of millions or even over a billion dollars for the first round of funding. Obviously, there’s a lot of dramatic things happening in that space. There’s a lot of capital going to that space. It’s going to happen. It’s going to take much longer than, I think, we think it’s going to take. I just saw, I think, Marc Andreessen recently saying, AGI is already upon us. Maybe it is. Maybe he knows something we don’t know. But I suspect we’re still ways to go in a lot of the developments on AI. For now, it will continue its complications and its limitations. But definitely it will untap a lot of great productivity enhancements, technological enhancements, even in the short term that at least I’m very excited about. Then the AGI story, I think, will be a story that will be told later.Bertrand SchmittI might actually disagree on this one. I actually believe, like Marc Andreessen, that we are at AGI. We reached AGI a few months ago with the latest ChatGPT 5.5 with Claude Anthropic, Opus 4.7, 4.6 even. For me, in some specific space, let’s say coding, for instance, I truly believe we have reached AGI. It is totally replacing people for development, testing, writing, specifications, doing design. Yes, there are some use cases where it’s not working as well. But for at least the coding side, I think AGI is truly there. Is it better than the best human experts at every piece of the puzzle? No. I think if you go to some very specialized development stuff like a CUDA development, for instance, or some kernel development, it might not be at the level of the top human experts. But as we can hear about stories around security to the new versions that are unreleased yet of Anthropic and others seem to be at the level of the best human experts at cybersecurity. I think we are actually there. I think that’s why there is an acceleration the past six months in terms of investments in data centers. There was a big question in 2023, 2024, 2025, “Are we investing too much? Is it a bubble?” And so on. That was true because revenues were increasing, but not that fast. The increase in the growth in revenues for Anthropic is insane. No one has ever seen that in the whole history of technology, what happened to them the past six months. Growing so fast at such a scale, no one has seen. I think that’s truly because they have stumbled upon AGI for coding. Coding is such a huge, large market that even if we are just solving coding, even if we never solve more than that, I think it’s already one of the biggest markets in the world, full stop.Nuno Goncalves PedroBut that, for me, I think maybe it’s a definitional thing. That, for me, is still narrow AI. AGI, as defined, is a type of AI that can match or surpass human capabilities across virtually all cognitive and intellectual tasks. Coding is just one of them. I think there’s a lot of narrow AI right there, to your point, that can replace humans maybe today. Coding may be a great example of that. But I don’t think we are at the AGI. I haven’t seen any agents out there that can replace fully human beings, where I would not understand that they’re actually AI. Anyway, again, maybe you guys have seen stuff that I haven’t seen. I just feel there’s a lot of overhype on what the AGI actually is. But the ability to surpass us as human beings, I haven’t seen it yet across the board, not on a specific domain.Bertrand SchmittYes, I think my point is that I have seen it on a few domains. If you look at mathematics, for instance, and there are more and more examples of people who are using AI to solve math problems that only the very top people in the world were able to solve that are now being solved by AI. I start to feel that we are getting a few examples in different fields where AI is matching the absolute best experts in the world. I would just go back in terms of market size. Already what we got today, and today is not the limit, but what we got today, and especially AI combined with all these agents, harness agents, that’s also that specific combo that makes a difference. This is, for me at this stage, huge market. Does it solve everything? Does it replace a human for everything? No, you still need the human in the loop. You don’t let your AI go wild for weeks and just check once in a while. But you could argue very few humans are able to do that, quite frankly, to run by themselves for weeks without control.Nuno Goncalves PedroI feel there’s still a great deal of confusion because there’s dramatic impact on narrow AI domains where things are being done that weren’t done before, where there’s these great mathematical proofing, coding stuff is being done very easily, etc, etc. But still that, for me, is not the definition of AGI. AGI is a human being. It’s like someone who can really be a human being. Ideally, become top end of what a human being will look intellectually across domains. I don’t think that’s where we are. Again, maybe definitional, maybe that’s what Marc means, but I mean-Bertrand SchmittYeah, the question is, what does it mean? I would argue it’s beating 80% of humanity today pretty easily. Most of humanity doesn’t know how to code. It will be unable to do coding at the level AI is doing. It will be unable to do math at the level AI is doing. Use ChatGPT to check for medical issues and stuff. It’s not perfect for sure, but, again, it still beats most humans. I don’t know. I feel that we are reaching a level where it’s truly beating most of humans, many experts in many fields. I feel the definition of, “Hey, it has reached the level of an average human being.” I would say it passed that one. Is it the same as a human being? No. But reaching the level of your average human being, I think we are there in a lot of fields.Nuno Goncalves PedroConclusion Well, in conclusion, in episode 78 of Tech Deciphered, we went into two piles: the pile of dead-on-arrival products, technologies, businesses, and the pile of “it will happen, but not like that” or “not yet” pile of technologies, business out there as well. We went into a bunch of topics today that were of extreme importance back in the past where we thought the world was going to change, anywhere from self-driving to fusion in the nuclear space. We also went into some dramatic, dramatic mistakes like Juicero and other deployments like Segway that seem to be really very much dead on arrival. With that, I would ask you if you’re excited, and you want to share with us some of your agreements or disagreements on today’s episode, as well as your own dead-on-arrival versus merely-early examples, feel free to do so on LinkedIn, X, or via email. Thank you, Bertrand.Bertrand SchmittThank you, Nuno.

AI is moving fast, but most teams are still figuring out how to use it responsibly. In this episode, Tessa Burg talks with advertising attorney Candice Kersh about the legal and practical questions marketing leaders are facing right now. They cover what companies should worry about, where risk tends to show up and why policies, training and better decisions matter more than ever.  This is the conversation that will help you cut through the AI noise. You'll get a clearer understanding of AI contracts, copyright, ownership, data protection, synthetic performers and what brands need to think about before launching AI-powered work. It's a helpful listen for anyone trying to move faster with AI without creating bigger problems later.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Candice Kersh: Candice is a leading advertising and marketing attorney and a longtime member of Frankfurt Kurnit's advertising, marketing, and public relations practice. Widely recognized for her expertise and practical approach, she is consistently ranked by Best Lawyers in America, Chambers USA, The Legal 500, and Super Lawyers, and was named a 2025 Financier Worldwide Distinguished Advisor in Advertising and Marketing. The first woman named “Advertising Lawyer of the Year” by Best Lawyers in America and the only lawyer recognized by Folio as a Top Woman in Media, Candice is a go-to advisor for brands navigating complex advertising, marketing, and emerging technology issues.  Her client testimonials speak volumes about the trust her clients place in her and the high standard of counsel she provides.  Candice's experience, insight, and creative problem-solving make her a trusted advisor on the full range of advertising and marketing law issues, including IP, right of publicity, advertising clearance, false advertising and substantiation, AI-related matters, talent and sponsorship agreements, union issues, agency and media agreements, and branded entertainment deals—helping leading brands clear legal hurdles and bring innovative campaigns to market. Candice can be reached on LinkedIn or on her firm's website, fkks.com. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

Artificial intelligence has made translation faster and more accessible than ever, but it isn't the right solution for every learning project. Interpro Translation Solutions' Nicholas Strozza, CEO, and Beshar Bahjat, Chief Technology Officer discuss how AI is changing translation, where human expertise remains essential, and what L&D leaders should consider when creating equitable learning experiences for multilingual audiences.Show Notes:Nicholas Strozza and Beshar Bahjat of Interpro Translation Solutions discuss the evolving role of AI in translation, the difference between translation and localization, and how organizations can balance speed, cost, quality, and learner experience when delivering training across languages. Key points include:Translation and localization are not the same thing. Translation converts content from one language to another, while localization adapts the entire learner experience—including language variations, imagery, audio, cultural references, and regional preferences.AI is a powerful starting point, not always a finished product. For many projects, AI can accelerate translation, but human review remains critical when accuracy, brand reputation, compliance, or learner safety are at stake.The right approach depends on your goals. Organizations should evaluate audience, content type, language, risk level, and long-term translation needs before deciding how much AI or human involvement is appropriate.Learning equity matters. Learners who speak another language deserve the same high-quality experience as English-speaking learners. Poor translations can negatively impact comprehension, engagement, accessibility, and training outcomes.Human expertise remains essential in the age of AI. Professional linguists increasingly serve as reviewers, editors, and quality experts who ensure translated content reflects local language, culture, terminology, and organizational standards.Learn more about Interpro Translation SolutionsPowered by Learning earned Awards of Distinction in the Podcast/Audio and Business Podcast categories from The Communicator Awards and a Gold and Silver Davey Award. The podcast is also named to Feedspot's Top 40 L&D podcasts and Training Industry's Ultimate L&D Podcast Guide. Learn more about d'Vinci at www.dvinci.com. Follow us on LinkedInLike us on Facebook

Predicting the Future: AI, Geopolitics & Better Decision Making w/ Anthony Vinci of VICO - AZ TRT S07 EP10 (292) 6-28-2026       What We Learned This Week Think in Probabilities Great decision-makers don't predict one future. They prepare for multiple possible futures. Look for Leading Indicators Government budgets, regulations, elections, trade policy, and geopolitical developments often signal future trends before markets fully respond. AI Is Becoming a Strategic Advisor AI is increasingly functioning as a research assistant, intelligence analyst, and scenario-planning tool—not just a content generator. Everything Is Connected Politics, economics, technology, energy, and national security influence one another more than ever before. Understanding those relationships creates a competitive advantage. Focus on Second-Order Effects Many investors react to headlines. The bigger opportunities often lie in anticipating the ripple effects that follow.     AZ TRT Podcast Predictive Forecasting: AI, Geopolitics & Better Decision Making Guest: Anthony Vinci Links: https://www.linkedin.com/in/anthony-vinci/ https://www.anthonyvinci.com/ https://www.vico.io/ Anthony Vinci is the Founder and CEO of VICO, an AI-powered forecasting company that helps governments, financial institutions, and corporations assess political, geopolitical, and economic event risk. Rather than predicting a single outcome, VICO converts news, expert analysis, and real-world signals into probability-based forecasts to improve decision-making. Before founding VICO, Anthony served as the first Chief Technology Officer of the National Geospatial-Intelligence Agency (NGA), where he led the integration of artificial intelligence into U.S. intelligence operations. He also held senior leadership roles at Bridgewater Associates and Cerberus Capital Management, focusing on technology, national security, aerospace, and strategic investments. Anthony is the author of The Fourth Intelligence Revolution, recognized by the Financial Times as one of the Best Books of 2025. His work focuses on the intersection of AI, intelligence, geopolitics, and global finance. Theme Today's world moves faster than ever. Political events, wars, technological breakthroughs, trade policy, and artificial intelligence all create ripple effects throughout the economy and financial markets. The question isn't simply: "What will happen?" Instead, it's: "What are the most likely outcomes, and how should we prepare for them?" That is the foundation of predictive forecasting. Segment 1 The World Has Become an Event-Driven Economy One of the biggest themes discussed was how major events rarely stay isolated. Instead, they create ripple effects throughout politics, economics, and financial markets. Examples from 2026 include: The conflict involving Iran Concerns over the Strait of Hormuz disrupting global shipping Oil price volatility Inflation concerns AI adoption across industries Global trade tensions For example, if shipping through the Strait of Hormuz were disrupted, the effects could extend far beyond oil: higher energy prices increased transportation costs higher inflation pressure on consumer spending lower corporate profits political consequences during the 2026 midterm elections One geopolitical event can trigger dozens of second- and third-order consequences. Narrative Economics Markets increasingly react to information almost instantly. News travels within seconds through: X (Twitter) social media financial news AI-generated analysis Sometimes markets move more from the narrative than from the underlying facts. The speed of information has increased volatility. AI as an Intelligence Analyst AI is evolving beyond a simple chatbot. Examples discussed: Claude drafting emails in seconds ChatGPT analyzing massive amounts of information AI summarizing research AI identifying patterns humans might overlook Rather than replacing executives, AI increasingly acts like an executive assistant or intelligence analyst that can evaluate possible outcomes and estimate probabilities. Segment 2 Forecasting Through Leading Indicators One of Anthony's core ideas is that forecasting begins with identifying early signals rather than reacting after events occur. Examples include: Government Spending Watching federal budgets provides clues about future economic priorities. For example: A proposal to increase defense spending from roughly $1 trillion toward $1.5 trillion could benefit industries such as: aerospace defense contractors cybersecurity satellite technology Markets often recognize these trends before the spending actually occurs. Elections Forecasting elections isn't just about polling. Leading indicators include: redistricting economic conditions inflation employment approval ratings legislative trends These become measurable inputs rather than opinions. Tariffs and Trade Tariffs and sanctions affect: supply chains inflation manufacturing exports corporate earnings Rather than relying solely on headlines, investors can monitor government announcements and policy developments as early indicators. VICO Anthony explained that VICO was created to help organizations answer questions like: "What happens if tariffs increase?" "What happens if a regional conflict expands?" "What happens if inflation persists?" Instead of producing opinions, the platform attempts to quantify probabilities so businesses can make better strategic decisions. Current users include: investment firms hedge funds insurance companies corporations government agencies The platform is also available through Bloomberg Terminal. Segment 3 Thinking Like an Intelligence Officer Anthony explained that investing and intelligence analysis are surprisingly similar. Neither profession knows the future with certainty. Instead, both attempt to improve decision-making through probabilities. Questions include: What's the upside? What's the downside? What scenarios exist? What is the probability of each? Instead of asking for certainty, professionals ask for better odds. AI as a Thought Partner Rather than replacing human judgment, AI becomes another analyst at the table. It helps: challenge assumptions compare scenarios estimate probabilities reduce emotional decision-making The objective isn't perfect predictions. It's consistently making better-informed decisions. Indicators and Warnings (I&W) Government intelligence agencies constantly monitor "Indicators and Warnings." Examples include: military activity cyber threats terrorism supply chain disruptions political instability The same thinking can apply to investors and business owners by identifying leading indicators before markets fully react. Rare Earth Minerals A fascinating discussion centered on rare earth materials. These minerals are essential for: semiconductors missiles satellites electric vehicles MRI and CT scanners advanced electronics Although called "rare," many are relatively abundant. The challenge is that mining and processing are concentrated in a handful of countries, particularly China. This explains why governments increasingly view domestic production as a national security issue. Segment 4 Second- and Third-Order Effects One of the strongest concepts discussed was cascading consequences. Instead of focusing only on one event, ask: "What happens next?" Example: Conflict with Iran↓ Shipping disruptions↓ Higher oil prices↓ Higher transportation costs↓ Inflation↓ Reduced consumer spending↓ Lower corporate earnings↓ Market volatility↓ Political consequences↓ Policy changes Understanding these chains of events helps improve forecasting. AI Regulation AI is both part of the opportunity and part of the risk. Potential future regulations may focus on: cybersecurity national security privacy export controls access to advanced AI models computing infrastructure One challenge will be balancing innovation with security while remaining globally competitive. Anthony noted that governments may have access to AI capabilities that are not immediately available to the private sector, highlighting the strategic importance of advanced AI systems.   Closing Thought One of the biggest lessons from this conversation is that forecasting isn't about predicting the future with certainty—it's about improving the quality of your decisions. The best investors, business leaders, and intelligence professionals don't rely on opinions alone. They gather data, monitor leading indicators, evaluate multiple scenarios, and assign probabilities to each possible outcome. In an increasingly interconnected world, those who think like forecasters rather than reactors will be better positioned to navigate uncertainty and identify opportunities before the crowd.         Tech Topic: https://brt-show.libsyn.com/category/Tech-Startup-VC-Cybersecurity-Energy-Science  Best of Tech: https://brt-show.libsyn.com/size/5/?search=best+of+tech   'Best Of' Topic: https://brt-show.libsyn.com/category/Best+of+BRT      Thanks for Listening. Please Subscribe to the AZ TRT Podcast.     AZ Tech Roundtable 2.0 with Matt Battaglia The show where Entrepreneurs, Top Executives, Founders, and Investors come to share insights about the future of business.  AZ TRT 2.0 looks at the new trends in business, & how classic industries are evolving.  Common Topics Discussed: Startups, Founders, Funds & Venture Capital, Business, Entrepreneurship, Biotech, Blockchain / Crypto, Executive Comp, Investing, Stocks, Real Estate + Alternative Investments, and more…    AZ TRT Podcast Home Page: http://aztrtshow.com/ 'Best Of' AZ TRT Podcast: Click Here Podcast on Google: Click Here Podcast on Spotify: Click Here                    More Info: https://www.economicknight.com/azpodcast/ KFNX Info: https://1100kfnx.com/weekend-featured-shows/

On this episode of Coaching Call, Sifu Rafael welcomes Yosi Kossowsky, MCEC, PCC, for a thought provoking conversation on leadership, communication, team performance, and creating lasting impact.With more than 30 years of multinational corporate experience and 17 years as a professional coach, Yosi has helped leaders and organizations transform the way they think, communicate, and lead. His unique journey from Chief Technology Officer and Senior Director of Talent Management to executive coach gives him a rare ability to combine analytical thinking with a deep understanding of people.Yosi specializes in helping leaders gain strategic clarity, improve communication, strengthen team dynamics, and build cultures where people and performance thrive together. His practical coaching approach empowers individuals to navigate change, prevent burnout, lead through uncertainty, and align professional success with personal fulfillment.Whether you're leading a business, managing a growing team, or striving to become a more intentional leader, this conversation will provide valuable insights you can apply immediately.Join us as we explore what it really takes to lead with purpose, communicate with confidence, and inspire others to perform at their highest level.Watch on YouTube and subscribe:https://www.youtube.com/@sifurafaeltv?sub_confirmation=1Sifu Rafael is a master instructor and the founder of Speaking Prowess, where he combines expertise in communication and leadership to help individuals unlock their full potential. As a professional speaker, solutions expert, and executive coach, Sifu Rafael leverages years of experience to guide clients toward their goals with clarity, purpose, and strategic insight. His mission is to make the art of effective communication accessible to all, empowering personal and professional growth. Sifu Rafael's unwavering dedication to improving communication skills has earned him a reputation as a trusted mentor and coach. His vision is clear: to enhance communication worldwide, one individual at a time.This episode is brought to you by Sifu's Mind Body Method, a lifestyle transformation that blends movement, mindset, nutrition, hydration, fasting, journaling, and faith. Learn more at sifumethod.comThat's where connecting with Sifu Rafael matters.Through Speaking Prowess and Sifu's Mind Body Method, Sifu Rafael helps leaders, entrepreneurs, and experts refine their message, command a room, and step onto more stages with clarity and confidence. From podcasts and live shows to keynote stages and curated experiences, Sifu Rafael helps people get seen, heard, and positioned as trusted voices in their industry while sharpening their speaking skills along the way.If you know you're meant to speak, lead, and impact at a higher level, this conversation is your invitation.Visit sifurafael.com to connect, explore speaking opportunities, and start positioning yourself for more stages, stronger presence, and real influence.#coachingcall #sifurafael #leadership #executivecoaching #teamperformance #communication #leadershipdevelopment #personalgrowth #speakingprowess #coaching

What happens when a software company building AI tools for HR teams uses those same tools to transform itself? Josh McKenzie, Chief Technology Officer at ELMO Software Group, shares how his team rebuilt their entire software development lifecycle around AI agents and redrew the boundaries of every engineering role. He breaks down how to lead that shift without losing people's trust, why domain expertise is the real SaaS moat, and how the right analytics partner unlocks decisions HR teams have never been able to make before. Key Moments: The SaaS Moat: What AI Can't Erode (06:37): Josh argues SaaS value runs deeper than software. Accountability, compliance, and domain expertise keep purpose-built platforms irreplaceable. How ELMO's AI Journey Started (10:23): ELMO started by mapping every role against AI impact. Turning that lens on their own engineering team set the full transformation in motion. Why ELMO Chose ThoughtSpot Over Building Its Own Analytics (18:42): A homegrown tool requiring too much user expertise led ELMO to look elsewhere. ThoughtSpot Spotter and natural language capabilities closed the gap. Why HR Teams Are the Most Underserved (20:21): Payroll here, benchmarking data there, performance data somewhere else. HR teams have been drowning in spreadsheet hell for years. Josh explains how AI finally closes that gap. From Engineer to CTO: Build a Team of Complements (24:17): Josh reflects on the mindset shift that defined his path to the C-suite. Great leadership means building a team whose strengths cover your blind spots. Key Quotes: “ ThoughtSpot was particularly interesting for us… The big thing for us was the Spotter product. Allowing users to bridge that data analyst gap was really important. So, that product has yielded really, really great results for us.” - Josh McKenzie “I think it's really important that we instill a culture where it's okay to fail, and it's okay to make a mistake. You want to be vocal about your mistakes so others don't repeat the same mistake.” - Josh McKenzie “My belief is you want to focus on your secret sauce. So, what is the thing that makes your business super successful? And for us, that's where we came to look at ThoughtSpot. It has a really nice visual user interface and allows you to create some great dashboards.” - Josh McKenzie Mentions Hiring and Onboarding Taking Longer Despite Widespread AI Adoption, New Australian Research Finds The 5 Levels of AI Coding (Why Most of You Won't Make It Past Level 2) WireGuard: Next Generation Kernel Network Tunnel | Jason A. Donenfeld Guest Bio As the Chief Technology Officer, Josh McKenzie is responsible for both technical strategy and delivery (build, release and operation) of the ELMO product suite. Josh has a proven track record of successfully leading technology teams and implementing transformative strategies that enhance efficiency, drive growth, and elevate overall technological capabilities. Josh has 20 years of experience in technology, primarily in FinTech. Before joining ELMO in 2024, Josh held executive and senior positions at Lendi Group, OFX, ASX and Westpac. Josh holds a Bachelor of Computer Science from the University of Newcastle and an MBA from the University of Sydney. Hear more from Cindi Howson here. Sponsored by ThoughtSpot.

Send us Fan MailIn this episode of the WTR Small Cap Spotlight podcast, Eric Robinson, Senior Vice President of Operations, and Joe Wong, Chief Technology Officer of Arq, Inc. (Nasdaq: ARQ), join Tim Gerdeman (Vice Chair, Co-Founder & CMO, Water Tower Research) and Peter Gastreich (Managing Director, Water Tower Research).In a technical deep-dive into operations, Eric and Joe shared views on the science and commercial applications of activated carbon, the engineering challenges Arq encountered in scaling granular activated carbon (GAC) production at its Red River facility, the surging demand for GAC in PFAS drinking water treatment, the competitive dynamics and supply-side barriers in the activated carbon market, Arq's path forward on GAC capacity decisions, and the strategic optionality remaining at the idled Corbin facility.Subscribe and visit watertowerresearch.com for open-access small cap research, podcasts, and conference schedules.

Today on Leader Generation, Tessa Burg welcomes back Linda Owens, Global Vice President of Digital Customer Experience at Sherwin-Williams. Six years after becoming the podcast's very first guest, Linda returns to discuss how B2B leaders can navigate rapid changes in technology, AI and buyer behavior while staying focused on what matters most: the customer. Linda shares practical advice for separating meaningful trends from hype, creating trust earlier in the buying journey and designing customer experiences that reduce friction across every touchpoint. She also explains why customer obsession should drive every decision, how to use experimentation without losing sight of scale and what leaders need to do to successfully manage change across their organizations. Whether you're leading digital transformation, evaluating AI initiatives or looking for ways to create more value for customers, this conversation offers actionable insights you can apply immediately. Tune in to learn how today's most effective B2B leaders are building customer experiences that drive both business growth and long-term loyalty. Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Linda Owens: Linda Owens is the Global Vice President of Digital Customer Experience at Sherwin-Williams, where she leads initiatives that advance digital customer experiences, scale eBusiness capabilities and drive enterprise transformation. With more than 20 years of experience spanning marketing, sales, ecommerce and digital customer experience, she has helped organizations modernize customer engagement and accelerate growth across B2B and B2C markets. Throughout her career, Linda has led cross-functional teams and developed digital strategies that improve customer experiences across channels and global regions. Her expertise includes ecommerce strategy, digital marketing, customer journey optimization, CRM lifecycle programs, Martech and digital innovation. She is passionate about simplifying complexity, empowering high-performing teams and creating customer-centric solutions that deliver measurable business impact. Linda can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

The Big Unlock · Marshall Glanzer, Chief Technology Officer, Town Square Health In this episode, Marshall Glanzer, Chief Technology Officer of Town Square Health, outlines a bold model for scaling fully capitated risk programs for Medicare recipients. Transitioning from food-delivery logistics at GrubHub, Marshall brings critical structural insights for digital health innovators seeking to scale clinical models without eroding patient trust. The core theme of the discussion centers on a counter-intuitive tech strategy: utilizing advanced digital infrastructure to intentionally deepen human relationships rather than automate them away. Town Square orchestrates unified “coordinated care visits,” bringing the patient, primary clinician, and a remote specialist into a single conversation to act as a multi-disciplinary “healthcare oracle” at the point of care. For technology vendors, Marshall defines a safe clinical AI deployment roadmap using an “augmented clinician” framework. Advanced workflows, like chat-first patient portals managed by an automated “AI judge,” rely on the licensed physician as the ultimate orchestrator. This approach elegantly bypasses commercial barriers like malpractice liability, credentialing, and fractured billing, leveraging the financial alignment of value-based care to fully absorb modern R&D costs. Take a listen.

Most of us think about water in terms of filtration, purity, and quantity. But what about movement? What if water was never meant to be still?  Zeev Zohar, co-founder and Chief Technology Officer of Mayu Water joins us this week on the podcast. Zeev is a multidisciplinary entrepreneur, inventor, award-winning industrial designer, and advanced physics thinker who is helping people look at water in a completely new way.  Through Mayu, Zeev has helped create the Mayu Swirl, a glass water system inspired by the natural movement of spring water. By using vortex motion, Mayu encourages water to move the way it does in nature, supporting aeration, taste, and a more intentional relationship with the water we drink every day. In this conversation, Autumn and Zeev explore: • What structured water actually means • Why movement matters in nature • The difference between tap water and spring water • How vortex motion may change the way water behaves • Why oxygenation and aeration can impact taste • The role minerals may play in hydration • Why water interacts with everything it touches • How intention, gratitude, and ritual can change the way we relate to water • Why hydration is about more than simply drinking more This conversation will make you rethink something you use every single day. Water is not just a background part of health. It may be one of the most foundational. ✴️ Find Mayu Water on Facebook, Instagram, YouTube, or X

Send us Fan MailIn this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second and final compilation of our three-part HumanX Live series.Our first compilation explored how AI amplifies the human potential it can never replace. This one turns to the technical side, and to a question that gets harder the more these systems touch our lives: how do you build AI you can actually trust not to fail when it matters most? As technology reaches further into the moments that count (the systems that monitor our health, drive our cars, and work alongside us on the job), these four builders share how they design for accountability, safety, and harmony between people and machines.What You'll LearnWhy reading code is no longer enough, and how observing real outcomes (not system metrics alone) is the only way to know whether AI is actually serving the people who depend on itWhat "AI values" are, and why companies will soon need shared norms for how people disclose, review, and engage with work produced by agentic systemsHow robots earn trust on a job site by measuring their own uncertainty, asking questions, and communicating their intentions before they actWhy the most valuable place for automation is the dirty, dull, and dangerous work humans were never meant to do, and what that means for keeping people safeWhy physical AI should be built first as a reasoning and communication model that can explain its thinking to people, rather than one that jumps straight to actionHow "harness engineering" moves teams beyond prompt and context engineering, and why orchestrating several frontier models together can outperform any single oneFeatured GuestsChristine Yen, CEO and Co-Founder of Honeycomb. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362645 Dr. Ali Agha, CEO and Co-Founder of FieldAI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362711 Dr. Jaime Lien, Co-Founder & Chief Scientist of Archetype AI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363341 XD Huang, Chief Technology Officer of Zoom. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363454 Inspired by something you heard in this episode? Share your favorite insight about the future of work and tag us on social:LinkedIn: https://www.linkedin.com/showcase/ai-and-the-future-of-work Instagram: https://www.instagram.com/aifutureofwork/ And don't forget to subscribe to AI and the Future of Work for more conversations with the leaders shaping what comes next.Explore the Full HumanX 2026 SeriesThis episode is part of a special three-part series recorded live at HumanX 2026:Episode 1: Special conversation with Stefan Weitz, CEO of HumanX: https://www.buzzsprout.com/520474/episodes/19210355Episode 2: Compilation featuring the CEOs of Scribe, Operative Games, and Dataiku, and the Chief Business Officer of Zensai: https://www.buzzsprout.com/520474/episodes/19257142LIVE EVENT: See how leading enterprises are using agentic AI to give employees back 4–6 productive hours every week. Join PeopleReign CEO Dan Turchin for a live demo on June 25, 2026.Register here: https://go.peoplereign.io/live-demo-how-agentic-ai-is-being-used-by-global-enterprises

Send us Fan MailHow do you scale a Home Services Business past the $10M mark without losing your Company Culture or selling out to Private Equity? In this episode of Let's Vent, we sit down with the Owners of Go Green Plumbing, Heating & Air, Alicia Green and Pete Green to break down the exact operational tips, strategies and ideas they implemented to build an independent trade powerhouse. Connect with out Guests: Go Green Plumbing: https://gogreenplumb.com/Alicia Green: https://www.linkedin.com/in/alicia-green-14bb3495/Pete Green: https://www.linkedin.com/in/pete-green-25496072/ Connect with our sponsor: https://freeagency.aiTime Stamps: 01:10 - Introducing Pete & Alicia Green from Go Green Plumbing02:18 - Pete Green's Transition from Programming to "Chief Technology Officer"03:45 - The Truth About Company Culture: There are Always Ups & Downs05:15 - What Happens When People Don't Fit the Mold?06:13 - Shifting from Professional to Lightheartedness in Tough Times07:45 - The Go Green Hiring Process: Do You Let Your Team Make the Decisions?09:20 - The "Princess Castle" Lego Challenge & Out Of Comfort Zone Testing13:16 - Quick to Hire, Slow to Fire: Should Be The Opposite Way Around? 14:15 - The ROI of Training16:55 - Joining Nextstar Network & Implementing Soft Skills Training17:58 - The Academy Structure: Weekly Breakdown of Trades & Certifications22:38 - 60% of Our Business Wouldn't Exist Without the Training Academy23:45 - The Myth of the Unicorn Employee25:03 - Balancing IQ and EQ: Why Technical Skills and Soft Skills Are 50/5027:50 - The Chaos of Early Training Programs vs. Today's Managed Structure29:15 - Building a Clear Pay Plan and Incentivized Levels32:14 - Advanced Lab Training: Partnering with Ultimate Tech Academy in Arkansas33:20 - The Tax Perspective: Are you Paying More? 34:00 - Facing Private Equity (PE) in the Trades38:12 - The Positive Side of PE: Injecting Business Logic and Real Value into the Trades42:50 - Growing Big with Zero Outside Capital45:15 - Why Cheap Prices Come at the Expense of Employees?47:50 - Built on Community assistance: The Go Green Community Promise Program49:35 - "Owned by Google": Venting About the Real Monopolies Dictated by the Industry53:48 - Where Does the Cash Flow? Canadian Agencies vs. Local Greensboro Wages57:25 - Understanding KPI Pressures and Employee Mass Exits58:35 - Why Technicians Stay for Culture and Run from Structure Changes01:01:40 - The Flaw in Flipping: Why Passing Hands Leads to Volume Loss01:05:43 - Processing the Reality of Multi-Billion Dollar Acquisitions in the Trades01:07:55 - The Challenge to Maintain Massive Service Value Over Time01:10:17 - Will AI Supplement or Completely Replace Modern Jobs?01:12:00 - How To Choose a Software That Actually Helps Reduce Workload?01:12:42 - Why the CTO's Workload Increases When Implementing AI?01:13:55 - The Sandbox Mindset: Starting From a Place of Natural Curiosity01:18:15 - Managing Scope Creep When Coding with Accelerated AI Speed01:21:38 - How Non-Technical Leaders Can Leverage Claude?01:23:59 - The "Twice a Day" Automation Rule: Building Your Operational Task List01:28:46 - The Importance of Context and Direct Communication to Create a Prompt correctly01:31:12 - Ostrich Mentality: Why Ignoring the Automation Wave Will Cost People Their Careers01:31:47 - Focus on Eliminating Time Rather Than Solving the World's Problems01:34:00 - How To Hold People Accountable Without Destroying The Company Culture ?01:34:48 - Facts Over Feelings: Gathering Documentation and Data Before Tough Conversations01:38:25 - Final Thoughts on How to Build a Scalable Organization

Coming up with AI ideas isn't the struggle for most teams. The real challenge is to make those ideas stick. In this episode, Shashank Kadetotad, Global Senior Director of Enterprise Data Science and AI at Mars, breaks down what helps companies move from interesting pilots to real business impact. He explains why adoption matters just as much as the technology itself, how culture and leadership shape success and why the best AI solution is not always the most complex one.  You'll get practical advice on involving the right users early, setting clear success and failure criteria for pilots and deciding when to build versus buy. Shashank shares lessons from leading AI work inside major organizations and offers a grounded view of what it takes to scale responsibly. If your team is trying to get more value from AI, this conversation will give you a clearer and more useful way to think about the work.  Leader Generation is hosted by Tessa Burg and brought to you by Mod Op. About Shashank Kadetotad: Shashank Kadetotad is the Global Senior Director of Enterprise Data Science and AI at Mars, where he leads the deployment of AI and advanced analytics across global consumer goods operations. With a background that spans Amazon operations, retail and CPG forecasting, and AI leadership across multiple Fortune 500 companies, he has built and scaled enterprise AI platforms that power decisions in supply chain, marketing, and finance. Shashank is recognized for his work on generative AI and multi-agent architectures, with multiple provisional patents focused on applying AI to product innovation, analytics, and consumer engagement. A frequent industry speaker, he is known for making complex AI topics accessible to business leaders while keeping the focus on responsible, high-impact AI in retail and CPG. He can be reached on LinkedIn. About Tessa Burg: Tessa is the Chief Technology Officer at Mod Op and Host of the Leader Generation podcast. She has led both technology and marketing teams for 15+ years. Tessa initiated and now leads Mod Op's AI/ML Pilot Team, AI Council and Innovation Pipeline. She started her career in IT and development before following her love for data and strategy into digital marketing. Tessa has held roles on both the consulting and client sides of the business for domestic and international brands, including American Greetings, Amazon, Nestlé, Anlene, Moen and many more. Tessa can be reached on LinkedIn or at Tessa.Burg@ModOp.com.

In this episode of The Geek in Review, we welcome Greg Dickason, Chief Technology Officer at LexisNexis, for a wide-ranging conversation on agentic legal AI, Lexis+ AI Protégé, and the movement from AI chat toward AI work. Dickason frames the shift through a simple contrast: earlier legal AI answered questions, while agentic workflows take on multi-step assignments, conduct research, create drafts, verify citations, and move legal professionals closer to finished work product. For law firms and legal departments trying to understand where AI goes next, this episode places agentic AI squarely inside legal workflow, legal research, drafting, and risk management.A major theme of the conversation is trust. Dickason explains how Shepard's Verify extends the familiar Shepard's signal beyond traditional research screens and into uploaded work product. Rather than asking lawyers to rely on AI-generated text without a verification layer, LexisNexis is building citation checking into the workflow, giving lawyers a path to confirm whether cited authority exists, whether authority is still good law, and how later courts treated the cited case. For lawyers worried about hallucinated citations, AI-generated briefs, and unreliable authority, this verification layer becomes part of the product architecture, rather than an afterthought.The discussion also explores the relationship between LexisNexis and Anthropic, along with the rise of legal AI skills. Dickason describes a market where model choice, orchestration, and legal skills increasingly matter as separate layers. Anthropic, OpenAI, Google, and other model providers offer impressive foundations, yet legal work needs more than general-purpose intelligence. Large law workflows require legal content, expert reasoning, matter-specific playbooks, and firm-defined processes. Dickason notes the ability to upload firm playbooks as skills, giving firms a path to bring their own way of working into Protégé.Security receives equal billing with accuracy. As firms place client documents into AI vaults and connect work product to legal AI platforms, Dickason explains bring your own key, or BYOK, through a practical office-and-locked-cabinet analogy. The point is control: client content sits encrypted, access depends on the user's key, and access stops when the key is withdrawn. He also discusses legal chunking, indexing, vector stores, retrieval-augmented generation, and knowledge graphs as part of building AI systems suited for legal documents, rather than generic file handling.The episode closes with a broader view of legal AI's impact on junior associates, legal training, and access to law. Dickason does not predict the end of junior lawyers. Instead, he sees AI helping junior lawyers become senior faster through mock trials, mock depositions, and richer training environments. He also warns of risks from agent volume, security vulnerabilities, and legal systems struggling to keep pace with AI-enabled industries. The message is pragmatic and optimistic: agentic legal AI will change legal work, yet the winners will be those who combine trusted content, secure systems, verification, workflow design, and human judgment.Listen on mobile platforms:  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Apple Podcasts⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ |  ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spotify⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠YouTube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠Substack⁠[Special Thanks to ⁠⁠Legal Technology Hub⁠⁠ for their sponsoring this episode.]⁠⁠⁠⁠⁠Email: geekinreviewpodcast@gmail.comMusic: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Jerry David DeCicca⁠⁠⁠⁠⁠⁠⁠⁠⁠Transcript:

Fabrice Bernhard is the co‑founder and Chief Technology Officer of Theodo Group, a global technology consulting firm he co‑founded in Paris in 2009. Under his technical leadership, Theodo has grown rapidly by combining Lean principles with modern software engineering to help organizations build scalable, resilient digital capabilities. Fabrice is a recognized thought leader in Lean Tech, advocating for the application of Toyota Production System principles to software development and technology organizations. He is a frequent speaker and writer on continuous improvement, learning cultures, and human‑centered technology, and is a co‑author of The Lean Tech Manifesto. His work focuses on enabling teams to deliver value faster while empowering people through better systems and smarter use of technology.Link to claim CME credit: https://www.surveymonkey.com/r/3DXCFW3CME credit is available for up to 3 years after the stated release dateContact CEOD@bmhcc.org if you have any questions about claiming credit.

Most enterprises are renters, not owners, of their technology and AI. Raffi Krikorian, Chief Technology Officer of Mozilla, explains why dependence on a handful of closed model providers means losing control over model behavior, pricing, and your own data.In CXOTalk episode 920, Krikorian lays out where open-source AI actually wins in the enterprise, how lock-in happens quietly, and what CIOs and CTOs should do about it now. Krikorian draws on his experience building infrastructure at Twitter and running the self-driving division at Uber to ground the discussion in real engineering and economic tradeoffs, not hype.YOU'LL DISCOVER✅ Why 85% of enterprises believed they could switch AI vendors, but only about 30% actually could when they tried✅ The "renters vs. owners" framing and what it means to control your AI destiny✅ Why Krikorian wants data "protected by architecture, not legal handshakes"✅ How Pinterest reportedly saved on the order of $10 million in a single quarter by switching from closed to open models✅ Why IT is becoming "the HR team for agents," and the read/write "dangerous triangle" of agentic permissions✅ The case for recording your prompts and running your own evaluations instead of trusting public benchmarks✅ Why roughly 70% of enterprise GPUs sit idle, and the missing "LAMP stack for AI" that could put them to work✅ How closed "validation machines" can quietly steer answers toward sponsored outcomes⏱️ TIMESTAMPS (estimated, verify before publishing)0:00 Renters vs. owners: who controls enterprise AI2:26 The risks of depending on closed model makers6:23 How lock-in happens and where open source fits9:53 Regression testing and building your own evals13:24 Pricing instability and the post-IPO cost question23:31 Governance: IT as HR for AI agents32:38 Can a small organization own its AI stack end-to-end?38:47 Validation machines, trust, and sponsored answers43:39 Keeping humans at the center, not in the loop47:23 Can open source beat big tech in AI?51:39 Inside Mozilla.ai: Otari, CQ, Octanus, Thunderbolt55:21 The "rebel alliance" strategy

The Credit Repair Cloud State of the Union from Credit Repair Expo 2026 reveals the full roadmap, including AI-assisted disputing, the new Credit Hero Marketplace, mobile client app, and the tools built to help credit repair business owners get more clients and scale faster. Join Our FREE Start Repairing Credit Challenge: HERE Daniel Rosen takes the Credit Repair Expo stage with Keenan Jones, the new CEO of Credit Repair Cloud, and Tanmay Andhe, Chief Technology Officer, to walk through what's live in your account right now and what's coming next. From the Secure Client Access mobile app and PDF attachments to faster re-imports and CRC Billing with zero revenue share, this is everything credit repair specialists need to know about the platform that powers their business. You'll also hear how the CRC Marketing Hub gives you a built-in white-label of GoHighLevel for free, how Credit Hero Score has grown into the highest-paying credit monitoring in the industry, and what rent reporting will mean for your clients' scores. Daniel and Keenan share real numbers from the community: 20,000 Credit Heroes, 181 million point increases, and $229 million processed inside the system. Then they unveil the Credit Hero Marketplace, a new way for consumers and affiliates like mortgage brokers, realtors, and loan officers to discover and connect with you. Plus a look at AI-assisted disputing, custom client game plans, and where the platform is headed over the next year. If you run a credit repair business, this is the inside view. Tune in!  P.S. Join the #1 event to grow your credit repair business: http://creditrepairexpo.com/   Key Takeaways: 00:00 Intro  01:36 The Numbers Behind 20,000 Credit Heroes  05:26 What's Live Now. The Secure Client Access Mobile App  06:56 PDF Attachments and Faster Re-Imports  08:34 CRC Billing. Keep 100% of Your Revenue  11:06 How to Sell and Onboard Clients While You Sleep  11:52 The CRC Marketing Hub Explained  22:24 Credit Hero Score. What's New and What's Coming  26:06 Rent Reporting. A New Way to Boost Client Scores  28:28 Introducing the Credit Hero Marketplace  32:04 AI-Assisted Disputing. The Future of Credit Repair  34:42 New Awards to Celebrate Every Milestone  40:34 Final Thoughts Additional Resources: Grow Your Business Faster With CRC Billing Activate the FREE CRC Marketing Hub Get the highest payout with Credit Hero Score Join the Credit Hero Marketplace Share your feedback - we're listening Become a Credit Repair Cloud affiliate Get a free trial to Credit Repair Cloud Get my free credit repair training   How Credit Repair Millionaires Get Clients on Autopilot Make sure to subscribe so you stay up to date with our latest episodes.

In this podcast episode, Dr. Jonathan H. Westover talks with Shea Belsky about neurodiversity in the workplace.Shea Belsky is an autistic self-advocate. He is a Tech Lead II at HubSpot, and the former Chief Technology Officer of Mentra. Shea brings several unique perspectives to the discussion on neurodiversity: He is the manager of neurodivergent & neurotypical employees, has reported to neurodivergent & neurotypical managers, and has advocated for the needs and wellbeing of all who seek to be heard and understood in the workplace. Shea has championed neurodiversity for organizations like Novartis, the College Autism Summit, Northeastern University, in addition to being featured in Forbes and the New York Post. He also hosts his own podcast, Autistic Techie, empowering neurodivergent self advocates to feel more confident in the workplace and ready to take on the day to day challenges of their job. He's excited to share his perspectives on neurodiversity and how to be a meaningful ally and advocate!https://www.amazon.com/Brainstorm-Guide-Neurodivergent-Talent-Future/dp/1394388772https://autistic-techie.com/https://www.linkedin.com/in/sheabelsky/See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.