Spatial Computing Explained: AR, VR, Geospatial, Digital Twins & AI World Models | Jake Steinerman

What if the next AI model could be built from models we already have, instead of being trained from scratch?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Damian Borth, a professor of artificial intelligence and machine learning at the University of St. Gallen and CEO of Weight Space Labs, about weight-space learning: the idea of treating neural network weights as data. They explore how researchers can read existing AI models, edit parts of them, and work toward generating new, task-specific models. The promise is faster, less expensive AI model development, but Damian is clear that instant generation at scale is still a research goal.You’ll learn* Why training neural networks demands so much compute* What a model’s weights can tell us* How existing models could become training data* Where model synthesis differs from training from scratch* Why small, specialized models matter for robots* What Damian’s remote-sensing experiments showed about compute* How one AI model might edit another* Why reading models matters for safety and provenance* What limits weight-space learning today* How AI agents might request models as tools* Why private data raises new opportunities and risks* What must improve before on-demand models scaleDamian Borth is a professor of artificial intelligence and machine learning at the University of St. Gallen and CEO of Weight Space Labs. His research and work explore how to learn from the weights of existing neural networks. He describes published work on generating remote-sensing models that performed comparably to models trained from scratch while using less compute. He also discusses work on reading model properties, as well as the limits of current approaches. His team is working toward a foundation model for neural networks at Weight Space Labs.Timestamps00:00 Introduction01:26 Is AI Running Out of Training Data?02:42 How AI Models Learn and Store Knowledge04:06 What Is Weight Space Learning?05:45 Weight Space Learning Use Cases08:39 20x Less Compute: Efficiency Gains12:34 Weight Space Learning Limitations14:47 MIT's Weight Space Programming18:01 How AI Edits Another Model's Weights23:45 Model Analysis, Lineage and AI Security31:41 Risks of Recursive Self-Improving AI34:23 Skills for Working With Neural Weights39:07 Synthetic Data and Model Collapse42:03 Private Data Sharing via Neural Networks48:36 Getting Started With Weight Space Learning50:21 Innovation Q&A RoundConnect with Damian* Website: https://www.weightspacelabs.ai/ * LinkedIn: https://www.linkedin.com/in/damianborth/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the podcastEnjoy the podcast? You can help us keep bringing you interesting stories and conversations.Explore our sponsors and recommended tools:https://www.anhourofinnovation.com/sponsors/Some links are affiliate links, which means we may earn a small commission if you make a purchase or sign up, at no extra cost to you.Interested in sponsoring the podcast?Reach out to us at [email protected] to explore partnership opportunities.

How does your phone know where to place an AR arrow on a real street, and what makes a digital copy of the world useful?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Jake Steinerman, a spatial computing practitioner working in developer relations at Cesium, about the technology that connects digital experiences to physical places. Jake explains how augmented reality can recognize a room, object, or street; how geospatial data and digital twins help people see and monitor real infrastructure; and where AI world models could help build and test simulated scenarios.You’ll learn* What spatial computing means beyond the headset buzzwords* How augmented reality differs from virtual reality and mixed reality* Why you can experience useful AR on a phone, not only through glasses* How an AR object can stay attached to a book, machine, desk, or street* How Google Maps combines location, direction, and visual matching for AR walking directions* Why Jake built a Google Glass concept to detect drowsiness while driving* What can make VR movement uncomfortable and how developers respond* Why virtual training can help people rehearse work on complex equipment* How geospatial data differs from a digital twin* What sensor readings and inspection data add to a 3D model of a bridge or building* How AI has accelerated Jake's prototyping work and what world models aim to simulate* Where a curious builder can start experimenting with VR, AR, and Cesium's geospatial toolsJake Steinerman is an engineer and developer-relations practitioner who has worked across Google Glass, enterprise augmented reality, VR games and creator platforms, Meta's developer ecosystem, and Cesium. His hands-on experience shows what these technologies require behind the scenes: tracking the physical world, connecting models to useful data, and deciding whether a simulation answers a real question.Timestamps00:00 Introduction01:31 What Is Spatial Computing?03:18 AR vs VR vs Metaverse vs Digital Twins05:40 Do You Need a Headset for AR and VR?10:18 From Google Glass to Meta: 10 Years in XR19:39 How Augmented Reality Tracking Works26:20 Drive Safe: Google Glass Drowsiness Detection31:01 Virtual Reality vs Augmented Reality33:17 VR Motion Sickness Explained37:06 VR Training: Do Skills Transfer to Real Life?42:22 Geospatial Data and Digital Twins45:39 Where Geospatial Data Comes From49:06 AI and World Models in Geospatial54:11 How to Start Building in XR and Geospatial57:23 Innovation Q&AConnect with Jake* Website: https://cesium.com/ * LinkedIn: https://www.linkedin.com/in/jasteinerman/ * X: https://x.com/jasteinerman * Other: https://jasteinerman.lovable.app/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the podcastEnjoy the podcast? You can help us keep bringing you interesting stories and conversations.Some links are affiliate links, which means we may earn a small commission if you make a purchase or sign up, at no extra cost to you.Explore our sponsors and recommended tools:https://www.anhourofinnovation.com/sponsors/Interested in sponsoring the podcast?Reach out to us at [email protected] to explore partnership opportunities.

Your watch records months of health data. Why can so little of it help at a doctor's visit?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Marco Benitez, co-founder and CEO of ROOK and a biomedical engineer, about the missing connection between wearable data and useful healthcare. Marco explains why a doctor often sees a snapshot, while a watch tracks sleep, activity, and other patterns between visits.You'll learn* Why one readiness score or step count is not the whole health picture* How wearable data differs from the snapshot collected during a clinic visit* Why health information is scattered across watches, labs, medical devices, and health records* What an integration layer such as ROOK does, and what it does not do* How normalization, standardization, and deduplication affect data quality* Why device-specific validation matters before a metric informs medical care* What clinicians need from relevant trends or alerts instead of a flood of raw readings* Where wearables may fit into chronic-disease management and behavior change* Why a device alone does not prevent or treat illness* How AI depends on clean inputs and can still create false confidence* What insurance incentives might offer, and the consent and fairness concerns* Why Marco believes software that makes data useful matters more than another sensorMarco Benitez is the co-founder and CEO of ROOK and a biomedical engineer working at the intersection of wearables, health data, and digital health infrastructure. His team builds connections and data-processing tools for platforms. His experience helps listeners understand the difficult step between measuring health and making that information genuinely useful in care.Timestamps00:54 Introduction01:02 Wearable Health Data: Why It Matters02:48 Wearable Data Misconceptions05:11 ROOK's Health Data API Story09:00 Health Data Tools for Doctors10:23 Normalizing Health Data11:52 Wearable Data Accuracy and FDA Clearance14:34 What Doctors Want From Wearables17:34 Preventive Healthcare With Wearables19:14 Wearables for Chronic Disease23:00 Wearables and Health Insurance28:34 Wearable Health Tech Worldwide31:58 AI in Health Data32:47 How ROOK Uses AI35:11 Future of Wearables37:51 Optimism for Digital Health40:00 Innovation Q&AConnect with Marco* Website: https://tryrook.io/ * LinkedIn: https://www.linkedin.com/in/marcobzg/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the podcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.MeetGeek: Record, transcribe, summarize, and share insights from every meeting. https://get.meetgeek.ai/yjteozr4m6ln Amplemarket: Step into the future of sales: Human + AI. Empower reps, uncover opportunities, and grow revenue.https://grow.amplemarket.com/04e068165684-affiliateDatabox: Turn business performance data into clear answers your team can understand, explain, and act on – instantly.https://join.databox.com/vhw0wbr9qg9oFor inquiries about sponsoring An Hour of Innovation, email [email protected]

You can talk to an AI “hologram”, but what is it actually doing, and when is it useful?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Raffi Kryszek, a Chief Product and AI Officer at Proto Hologram, about the technology behind conversational digital people and the practical question of whether a humanlike AI interface helps people get things done. Raffi explains how the company's spatial displays and operating system developed from live remote appearances into a platform that can also present prerecorded experiences, interactive applications, and AI personas. They discuss how a spoken question becomes an answer, why the source of information matters as much as the avatar, and what changes when an assistant appears in a physical space instead of a chat window.You'll Learn:* What people are actually seeing when they call something an AI hologram* How a live remote person, a recording, and a conversational AI persona differ* Why Proto's operating system matters beyond the display hardware* How speech input, a language model, a knowledge source, and an avatar work together* Where digital people are being tried in public help, healthcare, retail, training, events, and advertising* Why a visible assistant can be easier to find at the moment someone needs help* How shared holographic displays differ from individual AR or VR experiences* What questions to ask about data retention, third-party services, model control, and guardrails* Which future interface ideas Raffi expects, and which remain speculativeRaffi Kryszek is a Chief Product and AI Officer at Proto Hologram, working on holographic displays and the software that brings live people and conversational AI personas into physical spaces. His perspective comes from building and deploying the technology across several kinds of customer settings. His examples help separate a compelling visual demo from an AI interface that solves a real problem, and understand the limits that still matter.Timestamps00:00 Introduction01:22 AI Holograms vs Chatbots03:11 Proto Holograms: From Presence to AI05:01 How Hologram Displays Work08:00 Scaling Holographic Displays10:40 Live Holograms, Video and AI Avatars14:35 How Conversational AI Avatars Work21:08 AI in Healthcare, Retail and Education26:43 Virtual Try-On and AI Fashion31:16 Celebrity Holograms and Live Events33:01 Holograms vs Augmented Reality37:22 AI Avatar Privacy and Data Security40:06 AI Guardrails and Enterprise Control43:34 The Future of Human-AI Interfaces47:16 AI Agents and Portable Devices48:37 Haptics, Neural Interfaces and Robotics51:24 An Optimistic Future for AI52:56 Innovation Q&AConnect with Raffi* Website: https://protohologram.com/ * LinkedIn: https://www.linkedin.com/in/raffi-kryszekConnect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.Kit: Email marketing that automates your growth. https://partners.kit.com/xqcc7ca2ahlmGoogle Workspace: A collaborative way of working in the cloud, from anywhere, on any device.https://referworkspace.app.goo.gl/A7wHRiverside: AI-powered platform that lets you record, edit, repurpose, and distribute studio-quality content as easily as if you had a crew behind you. https://riverside.partnerlinks.io/frjgalhip1rz For inquiries about sponsoring An Hour of Innovation, email [email protected]

In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Jeff Keyes, Field CTO at Allstacks and a product and go-to-market leader, about why AI can help teams build the wrong thing faster, how product teams should measure AI ROI, and why more code, tickets, PRs, and features do not automatically mean better products.You’ll learn:* Why many companies measure AI productivity with the wrong scoreboard* Why lines of code, PR count, and feature volume can be misleading AI ROI metrics* How AI-generated user stories can become the same weak requirements with more text* Why product managers need to focus on customer value, not just output* How Microsoft Office’s ribbon redesign shows the importance of prioritizing what users actually use* Why on-time and on-budget delivery does not prove a product created value* How the product manager’s job changes when AI speeds up execution* What AI slop looks like in product management, product marketing, and engineering* How to use AI better by organizing ideas, ranking themes, and applying frameworks* The difference between product management and product marketing* Why startups may need product marketing earlier than they think* How teams can define a North Star and use evidence to test whether AI is actually helpingJeff Keyes has worked across product management, product marketing, and engineering. His work focuses on helping teams build better products, connect product decisions to customer value, and use evidence instead of output metrics to understand whether they are actually improving.Timestamps00:00 Introduction01:17 AI ROI: Value Over Output05:34 Why Leaders Prioritize Speed16:12 How AI Is Reshaping Product Management22:01 The Expanding Product Manager Role24:54 What AI Slop Means for Product Teams29:22 A Better Workflow for LLMs32:10 Product Management vs. Product Marketing37:30 Aligning Product and Product Marketing41:09 Building Product Marketing Skills43:49 Using AI for Better Execution48:05 Augmented Intelligence and Critical Thinking49:52 Innovation Q&AConnect with Jeff* Website: https://www.allstacks.com/ * LinkedIn: https://www.linkedin.com/in/jeffdkeyes Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.MeetGeek: Record, transcribe, summarize, and share insights from every meeting. https://get.meetgeek.ai/yjteozr4m6ln Amplemarket: Step into the future of sales: Human + AI. Empower reps, uncover opportunities, and grow revenue.https://grow.amplemarket.com/04e068165684-affiliateDatabox: Turn business performance data into clear answers your team can understand, explain, and act on – instantly.https://join.databox.com/vhw0wbr9qg9o For inquiries about sponsoring An Hour of Innovation, email [email protected]

AI coding agents can build impressive demos, but real products are much harder.In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Tammuz Dubnov, CTO and co-founder of AutonomyAI, about how AI coding agents are changing product delivery, why vibe coding often breaks inside real production codebases, and what product teams need to understand before handing more work to agents.You’ll learn:* Why building a small AI-generated app is different from changing a legacy production product* How AI-generated PRs can look functional but fail engineering review* Why the harness around an AI coding agent matters as much as the model* Whether vibe coding will remain a skill or disappear into better platforms* How AutonomyAI helps product teams turn intent into tickets, sketches, presentations, and pull requests* Why code is the source of truth for product work* How agents can use analytics, customer signals, and team knowledge to suggest product improvements* Where PMs should have authority and where engineers still need to own technical decisions* How autonomous product delivery can maintain analytics, accessibility, bugs, and product friction* Why PMs remain responsible for deciding what belongs in the product* How faster feature creation changes prioritization, review queues, and product judgment* What PMs and engineers can try now if they want to use AI agents more effectivelyTammuz Dubnov is the CTO and co-founder of AutonomyAI, a platform helping product teams turn intent into delivery inside production-grade codebases. His work focuses on AI agents, product development workflows, autonomous product delivery, and helping product teams move from ideas to working software while keeping the right human judgment and engineering safeguards in place.Timestamps00:00 Introduction01:16 AI in Production Codebases03:01 What Impressive AI-Built Features Look Like05:49 Why Agent Harnesses Matter08:22 The Future Beyond Vibe Coding10:29 Autonomy AI: From Intent to Delivery14:06 A PM Workflow: Idea to Pull Request17:16 Turning Team Knowledge into Product Signals22:18 Guardrails for Safe Product Changes26:42 Faster Iteration and Team Collaboration30:35 Autonomous Product Delivery34:32 Human Judgment and PM Skills39:13 Prioritizing in a Faster Building Cycle42:41 Where Teams Should Start with Agents44:22 The Product Team of the Future46:36 Innovation Q&AConnect with Tammuz* Website: https://autonomyai.io/ * LinkedIn: https://www.linkedin.com/in/tammuzdubnov/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.Kit: Email marketing that automates your growth. https://partners.kit.com/xqcc7ca2ahlmGoogle Workspace: A collaborative way of working in the cloud, from anywhere, on any device.https://referworkspace.app.goo.gl/A7wHRiverside: AI-powered platform that lets you record, edit, repurpose, and distribute studio-quality content as easily as if you had a crew behind you. https://riverside.partnerlinks.io/frjgalhip1rz For inquiries about sponsoring An Hour of Innovation, email [email protected]

Many product managers assume leadership is the next step after doing great execution work, but the transition is not that simple.In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Yue Zhao, product leadership coach and creator of The Uncommon Executive, about how product managers can prepare for leadership, why strong PMs sometimes struggle after being promoted, and how AI is changing product decision-making.You’ll learn:* How to know whether you are truly ready for product leadership* Why readiness is often visible in how other people seek your judgment* Why the habits that make someone a great PM can become leadership liabilities* How to broaden your scope before you have the leadership title* How to influence adjacent teams, senior leaders, and cross-functional partners* Whether courses, certifications, and brand-name programs actually help* What questions to ask before accepting your first product leadership role* How startup product leadership differs from product leadership in a large company* Why new leaders should not underestimate relationship-building and roadshows* Which decisions a product leader should make and which decisions the team should own* How to communicate hard changes without hiding the real context* Why AI makes product judgment, alignment, evals, and bottleneck thinking more importantYue Zhao is a product leader, executive coach, and creator of The Uncommon Executive. She helps product managers and leaders grow into broader leadership roles, make better decisions, build influence across organizations, and adapt to the changing expectations of product leadership in the age of AI.Timestamps00:00 Introduction01:12 When You’re Ready for Product Leadership03:15 Why Some Product Managers Struggle to Become Leaders06:33 How to Build Leadership Skills10:33 Are Leadership Courses Worth It?14:14 Questions to Ask Before Taking the Role20:22 Startup vs. Big-Company Leadership25:29 Your First Six Months as a Leader28:03 Decision-Making: What Leaders Should Own32:14 How to Deliver Bad News35:32 How AI Is Changing Product Leadership42:23 AI Skills and Finding the Real Bottleneck46:24 Will AI Replace Product Managers?48:36 Final Advice for Aspiring Leaders50:27 Innovation Q&AConnect with Yue* Website: https://theuncommonexecutive.com/ * LinkedIn: https://www.linkedin.com/in/yuezhao/ * Substack: https://news.theuncommonexecutive.com/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.MeetGeek: Record, transcribe, summarize, and share insights from every meeting. https://get.meetgeek.ai/yjteozr4m6ln Amplemarket: Step into the future of sales: Human + AI. Empower reps, uncover opportunities, and grow revenue.https://grow.amplemarket.com/04e068165684-affiliateDatabox: Turn business performance data into clear answers your team can understand, explain, and act on – instantly.https://join.databox.com/vhw0wbr9qg9o For inquiries about sponsoring An Hour of Innovation, email [email protected]

AI companies are racing to build bigger data centers, but the real bottleneck may be electricity.In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Rob Gramlich, founder and president of Grid Strategies, about AI data centers, U.S. electricity demand, the electric grid, transmission bottlenecks, power generation, and who should pay for the infrastructure needed to support the AI boom.You’ll learn:* Why electricity and grid connections are becoming a bottleneck for AI data centers* Why U.S. electricity demand could grow by 166 gigawatts by 2030* How the electric grid works across generation, transmission, and distribution* Why the U.S. has three major grid systems instead of one simple national grid* Why data centers can be built faster than grid infrastructure* Why utilities move slowly and what can happen if they connect things incorrectly* Whether AI data centers can bring their own power* Why near-term onsite power is mostly natural gas, solar, and batteries* Why new nuclear power is unlikely to solve the next five years of demand* Whether AI data centers could raise household electricity bills* Who should pay for transmission, substations, transformers, and grid upgrades* Why communities oppose AI data centers over rates, water, land, noise, taxes, and jobs* What policy changes could speed up generation and transmission buildout* Whether AI demand could help modernize the grid or strain it furtherRob Gramlich is the founder and president of Grid Strategies, a consulting firm focused on transmission, power markets, and grid modernization. His work examines electricity demand growth, grid infrastructure, generation, interconnection, and the policies needed to expand the power system. Rob brings a practical expert view on what AI data centers mean for utilities, communities, energy markets, and the future of the electric grid.Timestamps00:00 Introduction01:11 The Growing Demand for Electricity in AI02:34 Understanding Data Centers and Their Power Needs04:13 The Structure of the Electrical Grid08:43 Challenges in Building Data Centers12:25 Innovation Speed in Power Generation and Usage13:29 On-site electricity generation for data centers14:52 Future of coal electricity generation15:49 Innovations for effective usage of electricity17:23 Solar electricity generation19:45 Who should pay for infrastructure and grid upgrades?21:14 Controversies Surrounding AI Data Centers25:02 Mini Data Centers and Mini Nuclear Power Plants27:49 Realistic Solutions for Power Demand28:58 Government Support and Policy Changes30:18 Demand for gas, oil, and solar panels32:35 Challenges in Meeting Future Demand35:49 Optimistic outlook for the future of the grid37:29 Innovation Q&AConnect with Rob* Website: https://gridstrategiesllc.com/ * LinkedIn: https://www.linkedin.com/in/rob-gramlich-2a4b594/ * X: https://x.com/RobGramlichDC * National Load Growth Report 2025: https://gridstrategiesllc.com/wp-content/uploads/Grid-Strategies-National-Load-Growth-Report-2025.pdfConnect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.Kit: Email marketing that automates your growth. https://partners.kit.com/xqcc7ca2ahlmGoogle Workspace: A collaborative way of working in the cloud, from anywhere, on any device.https://referworkspace.app.goo.gl/A7wHRiverside: AI-powered platform that lets you record, edit, repurpose, and distribute studio-quality content as easily as if you had a crew behind you. https://riverside.partnerlinks.io/frjgalhip1rz For inquiries about sponsoring An Hour of Innovation, email [email protected]

What if AI’s best use is not replacing people, but helping groups think together?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Louis Rosenberg, CEO and Chief Scientist of Unanimous AI, about collective intelligence, swarm intelligence, AI-mediated group decision-making, and why human-AI collaboration may be a better path than removing people from critical decisions.You’ll learn:* What collective intelligence means and how it differs from polls, surveys, and votes* Why the “wisdom of crowds” is useful but limited without deliberation* What fish schools, bird flocks, and bee swarms reveal about group intelligence* Why humans deliberate well in small groups but struggle at large scale* How AI agents can connect many small conversations into one large deliberation* How swarm-based systems can surface strong minority opinions instead of majority bias* Evidence from IQ tests, radiology, forecasting, and group problem-solving* Why human-AI “coagents” improved group forecasting accuracy* Why humans and AI have complementary strengths in decision-making* How Thinkscape can connect people across countries, languages, and perspectives* Why Louis believes critical decisions should keep humans inside the deliberationLouis Rosenberg is the CEO and Chief Scientist of Unanimous AI and a longtime technologist and researcher working across augmented reality, virtual reality, AI, swarm intelligence, and collective intelligence. His work explores how technology can connect human groups into smarter systems while preserving human values, judgment, and participation.Timestamps00:00 Introduction01:14 Collective Intelligence and AI05:20 Human Deliberation vs. Swarm Intelligence12:55 The Role of AI in Enhancing Collective Intelligence19:20 How Swarm Intelligence Works23:33 IQ Test Experiment27:18 Study at Stanford with Medical Doctors30:20 Collective Superintelligence: Humans and AI Agents37:29 Harnessing Diverse Perspectives for Better Outcomes43:52 Global Deliberation: Bridging Cultural Divides52:39 The Future of Human and AI Collaboration55:44 Innovation Q&AConnect with Louis* Website: https://unanimous.ai/ * LinkedIn: https://www.linkedin.com/in/louis-rosenberg/ * X: https://x.com/LouisBRosenberg Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.MeetGeek: Record, transcribe, summarize, and share insights from every meeting. https://get.meetgeek.ai/yjteozr4m6ln Amplemarket: Step into the future of sales: Human + AI. Empower reps, uncover opportunities, and grow revenue.https://grow.amplemarket.com/04e068165684-affiliateDatabox: Turn business performance data into clear answers your team can understand, explain, and act on – instantly.https://join.databox.com/vhw0wbr9qg9o For inquiries about sponsoring An Hour of Innovation, email [email protected]

AI can save time, but what happens to the skills you stop practicing?In this episode of An Hour of Innovation podcast, Vit Lyoshin speaks with Jolie Dobre, author of Sustaining Human Intelligence: Keeping People Smart, Connected and Innovative in an AI-Driven Workforce, about how AI changes human thinking, professional expertise, team creativity, and organizational learning.You’ll Learn:* Why AI can make organizations more productive while making people less capable* Cognitive offloading, skill decay, and the “ironies of automation”* Why generative AI is different from GPS, calculators, and search engines* How to decide what work is safe to delegate to AI* Why junior employees may lose the practice needed to become experts* Why polished AI output can hide real competence* How AI can create premature consensus inside teams* Why “human in the loop” can provide a false sense of security* What healthy friction with AI looks like in real workflows* How AI products should communicate uncertainty, evidence, and alternatives* Why Jolie never delegates first-stage ideation to AIJolie Dobre is an author and UX/design professional focused on sustaining human intelligence in AI-driven workplaces. Her book explores how AI interfaces, workflows, and organizational culture can be designed so people stay smart, connected, and innovative while benefiting from AI.Timestamps00:00 Introduction01:02 AI’s impact on human intelligence03:49 Effects of AI on critical thinking and creativity06:20 What work is generally safe to delegate to AI10:27 Organizational culture and the importance of diversity in thinking13:11 The challenge of entry-level skill development15:58 Strategies for responsible AI integration in organizations19:19 The importance of maintaining expertise and competence visibility24:04 Research evidence on AI's impact on cognition25:34 Using AI to enhance learning and development28:06 The myth of human-in-the-loop as a safety net33:26 Designing AI tools that support human decision-making35:19 The importance of deliberate practice and friction with AI39:33 Practices for working effectively with AI tools41:18 Personal strategies for AI-enhanced creativity42:35 The book release details44:53 Innovation Q&AConnect with Jolie* Website: https://human-centereddesign.com/ * Book: https://www.amazon.com/dp/B0HD9VZ5W3?lv=shuf&bestFormat=true * LinkedIn: https://www.linkedin.com/in/jolie-dobre-2623951/ Connect with Vit* Substack: https://anhourofinnovation.substack.com/* LinkedIn: https://www.linkedin.com/in/vit-lyoshin/ * X: https://x.com/vitlyoshin * Website: https://vitlyoshin.com/ Support the PodcastIf you enjoy the podcast, you can support it by exploring the tools below.These are affiliate links, meaning the show earns a small commission at no extra cost to you.Kit: Email marketing that automates your growth. https://partners.kit.com/xqcc7ca2ahlmGoogle Workspace: A collaborative way of working in the cloud, from anywhere, on any device.https://referworkspace.app.goo.gl/A7wHRiverside: AI-powered platform that lets you record, edit, repurpose, and distribute studio-quality content as easily as if you had a crew behind you. https://riverside.partnerlinks.io/frjgalhip1rz For inquiries about sponsoring An Hour of Innovation, email [email protected]