In this second and final part of Jerry Cuomo’s conversation with Dr. Lara Jehi of Cleveland Clinic, the discussion moves from why quantum computing might matter in medicine to what it could take to turn that potential into something real.

The conversation is part of the Wild Ducks Thinking Quantum series, as Jerry continues exploring the ideas behind his upcoming book, Think Quantum.

Lara begins with the thinking behind Cleveland Clinic’s Discovery Accelerator and the decision to invest in both AI and quantum computing. She describes a strategy built around three horizons: what an organization needs to do today, what may be holding it back, and what it needs to start building now for the future it believes is coming.

From there, Jerry and Lara tackle one of the biggest questions surrounding quantum computing: What’s real today, and where does the hype get ahead of reality?

Lara points to the rapid progress her team is seeing in quantum chemistry. She describes work with IBM and RIKEN that advanced from simulations involving only a handful of atoms to a system containing roughly 12,600 atoms in a surprisingly short period of time. It still isn’t enough to transform drug discovery today, but Lara argues that the rate of progress is itself something worth paying attention to.

The conversation also turns to the risks that come with more capable quantum computers, particularly cybersecurity and the possibility that encrypted information collected today could someday be decrypted. For healthcare, where protecting patient information has always been essential, preparing for a post-quantum world is already part of the technology discussion.

Jerry then asks Lara to look toward medicine itself. She sees some of the greatest potential in quantum chemistry and drug discovery, where developing a single drug can take more than a decade and cost more than a billion dollars. They also explore quantum sensing, including new ways of measuring what is happening on or inside the human body, and the possibilities for quantum technology in medical imaging.

The episode closes with Lara’s advice for students, early-career professionals, and anyone curious about what comes next: experiment, don’t be afraid to fail, and stay open to where the next opportunity might come from. Her own path into research didn’t begin until well into her medical training, a reminder that there isn’t just one route into a new field.

If you’d like early access to draft chapters, updates, and behind-the-scenes material from Jerry’s upcoming book, Think Quantum, visit wildducks.us and join the free early access list.

Key learning moments

• Hype versus reality: Quantum computing still has significant limitations, but the pace of progress can matter as much as where the technology stands today.
• Quantum in medicine: Drug discovery, sensing, and imaging are three areas Lara believes could benefit from advances in quantum technology.
• Getting involved: Experiment, learn from failure, and stay open to unexpected paths into research and quantum computing.

In this first part of a two-part conversation, Jerry Cuomo sits down with Dr. Lara Jehi of Cleveland Clinic, where one of the world’s first quantum computers dedicated to healthcare and life sciences sits right on campus.

This conversation is part of the Wild Ducks Thinking Quantum series, as Jerry continues exploring the ideas behind his upcoming book, Think Quantum.

Lara is a practicing neurologist and epilepsy specialist who has watched medicine become increasingly computational. She explains how that evolution led her from treating patients to working at the intersection of medical research, artificial intelligence, and quantum computing.

The discussion gets practical quickly. Lara describes why medical research can present a particularly difficult problem for AI: researchers may have thousands of biological features to analyze but relatively few patients to learn from. In one of her projects, that means roughly 20,000 genetic features and a cohort of only 150 patients. She explains why traditional AI can struggle with that imbalance and where quantum computing might help.

Jerry and Lara also explore why quantum shouldn’t be viewed as a replacement for AI or classical computing. Instead, Lara describes a hybrid approach where researchers choose the right computational tool for each part of the problem and combine them into a larger workflow.

Along the way, they talk about where medical research data comes from and what it takes to bring physicians, computer scientists, chemists, and engineers together. Lara argues that successful multidisciplinary teams share a few important traits: curiosity, tenacity, a willingness to take risks, and the ability to learn from failure.

You may also hear a hint that Lara makes an appearance in Jerry’s upcoming book, Think Quantum. Like Think Blockchain and Think AI, the book takes a student-friendly, builder-first approach to understanding complex technology through hands-on examples and experiments.

If you’d like early access to draft chapters, updates, and behind-the-scenes material as the book evolves, visit wildducks.us and join the free early access list.

Key learning moments

1. Hybrid computing: Quantum, AI, and classical computing can work together, each handling the parts of a problem that best fit its strengths.
2. The medical data challenge: Thousands of biological features combined with small patient populations can push traditional AI toward overfitting.
3. Building multidisciplinary teams: Curiosity, tenacity, risk-taking, and learning from failure can provide common ground across very different scientific disciplines.

In this second part of Jerry Cuomo’s conversation with Scott Crowder from the IBM Quantum team, the discussion shifts from the foundations of quantum computing toward the growing signs of practical, real-world impact.

If you haven’t yet listened to part one, you may want to start there first: Click to watch it here.

Recorded inside IBM Research in Yorktown Heights, New York, this episode explores what quantum computing could mean for software engineers, students, cybersecurity professionals, and the broader technology industry as quantum systems continue to mature.

Jerry and Scott discuss the growing push toward post-quantum cryptography, what Scott learned from speaking before Congress about the “Quantum Age,” and why the future value of quantum computing may depend as much on software, algorithms, and applications as the hardware itself.

The conversation also explores the emerging “skills gap” in quantum computing, including why domain expertise and strong mathematical foundations may become increasingly valuable as organizations begin experimenting with real-world quantum workflows.

Along the way, Jerry pauses the podcast to try something live: using generative AI to produce a working quantum program that connects to a real IBM quantum computer and visualizes qubit coherence times.

The episode closes with a look at practical applications beginning to move beyond research demonstrations, including chemistry simulation, optimization problems, and hybrid quantum-classical computing systems already being explored today.

You may also hear a few hints that Jerry has started work on his latest book in the Think series, Think Quantum. Much like Think Blockchain and Think AI, the book takes a student-friendly, builder-first approach to understanding complex technology through code, experiments, and hands-on examples.

If you'd like early access to draft chapters, updates, and behind-the-scenes material as the book evolves, visit wildducks.us and join the free early access list.

In this first part of a two-part conversation, Jerry Cuomo sits down with Scott Crowder from the IBM Quantum team inside IBM Research in Yorktown Heights, New York, with an actual IBM Quantum System hanging in the background.

If you haven’t yet listened to the earlier episode introducing the ideas behind Thinking Quantum, you may want to start there first: ⁠ click here.

Scott helps frame where we are in the evolution of quantum computing, comparing today’s moment to the vacuum tube era of the 1940s, when the foundations were forming but the future applications were still unfolding. The discussion explores how quantum systems fit alongside classical computing, why QPUs are different from CPUs and GPUs, and how hybrid quantum-classical systems are likely to evolve.

Jerry and Scott also get into Shor’s algorithm, the long road from factoring the number 15 in a classroom example to breaking real-world cryptography, and why organizations should already be preparing for a post-quantum security world.

Along the way, they cover quantum hardware, logical qubits, error correction, Q-Day, and the practical realities behind today’s systems, all through the lens of builders, software engineers, and students trying to understand where this technology may actually fit.

You may also hear a few hints that Jerry has started work on his latest book in the Think series, Think Quantum. Much like Think Blockchain and Think AI, the book takes a student-friendly, builder-first approach to understanding complex technology through code, experiments, and hands-on examples.

If you'd like early access to draft chapters, updates, and behind-the-scenes material as the book evolves, visit wildducks.us and join the free early access list.

In this episode of the Wild Ducks Podcast, Jerry Cuomo and a group of AI-generated student avatars introduce the core ideas behind quantum computing, including superposition, entanglement, interference, decoherence, and quantum hardware. Along the way, listeners explore how quantum systems differ from classical computers and why researchers believe they may eventually help solve problems involving cryptography, chemistry, optimization, and artificial intelligence.

Jerry also introduces his upcoming book, Think Quantum, now available for free early access at wildducks.us. Early readers can receive draft PDF chapters, project updates, GitHub resources, and release announcements as the book continues to evolve over the coming months.

The student avatars and voice performances featured in this episode were created using Synthesia.io and generative AI tools as part of the educational storytelling experience.

In this second half of their conversation, host Jerry Cuomo and Phil Gilbert pick up where they left off—moving from the craft of design to the culture that makes design thrive.

Phil shares how his work at IBM revealed that the real challenge wasn’t design talent, but organizational mindset. He explains how he and his team turned culture change into a product—earning buy-in across 300,000 employees and proving that true transformation happens when people choose to adopt new ways of working.

They also discuss the creation of the IBM Garage, the power of design thinking at scale, and how these lessons inspired Phil’s new book, Irresistible Change: A Blueprint for Earning Buy-In and Breakout Success.

Key Takeaways from Part 2 (on Culture & Change):

1. From Design to Culture — Great design can’t flourish without a culture that values empathy, collaboration, and curiosity.
2. Culture as a Product — Phil treated culture change like a product launch: define the audience, prove value, and earn adoption.
3. Outcomes Over Inputs — Change succeeds when it’s tied to measurable outcomes, not training programs or slogans.
4. The IBM Garage — A model for co-creation that brings design thinking to life with real clients and teams.
5. Earning Buy-In — Sustainable transformation is built on trust, participation, and shared purpose—not mandates.

In essence, Part 2 shows how Phil applied design principles to reshape an entire organization, culminating in the lessons captured in Irresistible Change.

#WildDucksPodcast #PhilGilbert #DesignThinking #CorporateCulture #IrresistibleChange #JerryCuomo #Leadership #Innovation

In this first of a two-part conversation, host Jerry Cuomo sits down with Phil Gilbert — entrepreneur, design leader, and the mind behind IBM’s modern design movement.

Phil takes us back to his startup roots in the 1980s, when helping professionals adopt personal computers sparked a lifelong passion for design as a force for clarity and connection. Along the way, he reflects on the thinkers who influenced him — from Alan Cooper’s persona-based design to Richard Buchanan’s “Wicked Problems in Design Thinking.”

Phil reminded us that great design scales quality, solves real human problems, and sometimes means knowing when to break the mold. Whether designing products or the organizations that design great products, this formula has proven to be a winner.

Key Takeaways from Part 1 (on Design):

1. Design as a Way to Scale Quality — Design isn’t decoration; it’s a method for making complex systems more usable, reliable, and human-centered at scale.

2. The Alan Cooper Moment — Persona-based design reframed how to build products around real people, not requirements.

3. Wicked Problems, Not Simple Fixes — Inspired by Buchanan’s 1992 paper, Phil saw design thinking as a way to address messy, evolving challenges.

4. Design Beyond Products — The same mindset that shapes great software can redesign organizations and cultures through empathy and experimentation.

5. Breaking the Mold — From early PCs to the iPhone, Phil shows that great design sometimes means knowing when to break consistency to create transformation.

In essence, Part 1 traces Phil’s evolution from software builder to design thinker, showing how design became his lifelong tool for meaningful, human-centered change.

Stay tuned for Part 2, where Jerry and Phil continue the story — exploring how design principles shape companies and inspire Phil’s new book, Irresistible Change.

#WildDucksPodcast #PhilGilbert #DesignThinking #Innovation #IrresistibleChange #JerryCuomo

In this episode of Wild Ducks, Jerry reconnects with his first programming teacher, Brent Hailpern, to explore how a simple course on Karel the Robot sparked a lifelong passion for software. They reflect on the early days at IBM’s TJ Watson Research Center, the art of programming, and today’s rise of AI code assistants. Join them for a thoughtful and lively discussion on how the tools may change, but the core discipline of coding endures.