Why is controlling a quantum hardware becoming one of the biggest challenges in scaling quantum computers?

In this episode, we speak with Yonatan Cohen, co-founder and CTO of Quantum Machines, a company developing advanced control systems for quantum computers. Cohen explains how quantum control sits at the interface between quantum hardware and classical computing, and why this hybrid architecture will become increasingly important as quantum processors scale.

We explore how quantum computers are controlled using precise microwave signals and pulse sequences, the limitations of conventional arbitrary waveform generators, and how Quantum Machines uses FPGA-based pulse processing units to generate waveforms in real time. We also discuss why low-latency classical processing and real-time feedback are essential for calibrating quantum processors, correcting errors, and implementing increasingly complex quantum algorithms.

Cohen explains what changes when moving from small quantum processors to thousands or millions of qubits, including the challenges of data movement, power consumption, control-channel density, and latency. We also discuss quantum error correction, feed-forward operations, hybrid quantum-classical architectures, and the role of CPUs, GPUs, and FPGAs in stabilizing large-scale quantum systems.

We also discuss the origins of Quantum Machines, the company's approach to quantum control, and why building scalable quantum computers requires much more than simply increasing the number of qubits.

Whether you're interested in quantum computing, quantum control, quantum error correction, computer architecture, FPGA technology, or the future of fault-tolerant quantum computers, this episode provides a deep technical look at the control infrastructure required to make large-scale quantum computing possible.

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Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
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Website: https://www.632nm.com

Timestamps:
00:00 - Intro and Reads
02:37 - Quantum Machines and Hybrid Architecture
06:04 - Why Do Classical Computers Need Quantum Processors?
10:02 - State of the Art Controllers
20:02 - Meeting Itamar
24:01 - FPGAs for Quantum
29:29 - Repurposing FPGAs
35:22 - Remote Direct Memory Access (RDMA)
41:29 - What If We Had Perfect Controllers?
43:26 - Adaptive and Embedded Calibrations
47:15 - Picks and Shovels of Quantum Computing
49:14 - Progress in Different Qubits
53:25 - Keeping Up with Quantum News and Research
56:51 - Core Advantages of Quantum Machines
1:00:06 - Managing Larger Teams
1:02:12 - Discovering New Physics with Quantum Machines
1:14:31 - Reinforcement Models in Quantum
1:16:45 - Yonatan’s Intro to Quantum Computing
1:21:24 - Realtime Correction vs Post Processing
1:32:10 - Channel Numbers and Interfering Signals
1:39:38 - Connecting Multiple Modules
1:46:46 - Early Believers in Quantum Machines
1:51:05 - What Would Yonatan Do With Unlimited Resources?

#quantumcomputing #quantumphysics #computerscience #fpga #coding

How did we go from knowing almost nothing about genes to sequencing the entire human genome?

In this episode, we speak with Nobel Prize-winning molecular biologist Walter Gilbert, whose discoveries helped lay the foundation for modern genomics. Gilbert recounts his remarkable journey from theoretical physics into biology, where he helped discover messenger RNA, uncovered the molecular mechanisms of gene regulation, invented one of the first practical methods for sequencing DNA, and later co-founded Biogen, one of the world's first biotechnology companies.

We explore the race to understand how genes work, the search for the elusive lac repressor, how a chance experiment led to the invention of DNA sequencing, and why Gilbert believed decades in advance that sequencing the human genome would transform biology into an information science. He explains the origins of the Human Genome Project, the rise of computational biology, and why today's era of AI-driven genomics was already visible in the earliest DNA sequence databases.

We also discuss the RNA World hypothesis, how life may have begun with self-replicating RNA molecules, the evolution of gene regulation, exon shuffling, the origins of protein domains, recombinant DNA technology, the birth of the biotechnology industry through Biogen, and how scientific revolutions often emerge from unexpected experiments.

Finally, Gilbert reflects on creativity in both science and art, explaining why, after a lifetime of pioneering discoveries, he left the laboratory to pursue digital abstract art.

Whether you're interested in DNA sequencing, the Human Genome Project, molecular biology, biotechnology, computational biology, the origin of life, RNA World, gene regulation, genomics, or the history of modern biology, this episode offers a firsthand account from one of the scientists who helped build the field.

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Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
02:34 - Jim Watson and Beginning Biology
06:58 - Lac Repressor
15:27 - Picking Good Problems
17:57 - Developing the First Generation of Sequencing
31:09 - The Birth of the Human Genome Project
40:00 - Origins of Life
43:35 - RNA World Hypothesis
54:45 - Experiments vs Theory in Biology
59:07 - Inspiration from Other Discoveries
1:12:08 - Starting Biogen
1:22:24 - Balancing Industry and Academia
1:27:45 - Advice for CEOs
1:32:48 - Perspectives on Art and Science
1:37:49 - Walter’s Journey through Art
1:44:55 - Walter’s Artistic Process and Inspirations
1:50:32 - The Role of Theory in Biology
1:55:51 - Frontiers and Guidance in Science
1:59:37 - Should Everyone Get Sequenced?

#biology #dnasequencing #originsoflife #genetics #humangenomeproject

How do bacteria power one of the most sophisticated molecular machines in nature?

In this episode, we speak with Dr. Michael Manson, one of the pioneers of bacterial motility research, whose nearly 50-year career has helped uncover how the bacterial flagellar motor works. From the first experiments proving that bacterial flagella rotate to the latest breakthroughs in cryo-EM and single-molecule biology, Manson tells the story of how scientists finally solved the mechanism behind a real working biological motor.

We explore how bacteria move through chemotaxis using a biased random walk, why E. coli alternates between running and tumbling, and how individual molecules can control the direction of a spinning flagellum. Manson explains the experiments that showed proton motive force powers the flagellar motor, how the motor’s rotor and stator generate torque, why it can reverse direction almost instantly, and how bacteria adapt to changing environments by dynamically adjusting their molecular machinery.

We also discuss ATP synthase, proton gradients, molecular motors, bacterial genetics, cryo-electron microscopy, ion channels, self-assembling protein complexes, nanomachines, and the history of the discoveries that transformed modern microbiology.

Whether you’re interested in the bacterial flagellar motor, molecular biology, biophysics, microbiology, ATP synthase, chemotaxis, molecular machines, or the fundamental physics of life, this week we go deep into one of biology’s most remarkable inventions.

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Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro and Reads
02:42 - Biased Random Walk
10:27 - Manson's Work with Howard Berg
13:24 - Proton Motive Force and Flagellum
29:07 - Rotors and Stators of Flagella
37:20 - Mot Proteins
57:34 - CheY and Changing Direction
1:11:48 - Biology and Intelligent Design
1:26:52 - Reversing Proton Flow
1:29:59 - Life at Low Reynolds Number
1:39:15 - Mysteries in the 90s and 2000s
1:48:34 - Applications of Understanding the Nanomotor
1:58:33 - Flagellar Motor Crash Course
2:01:46 - Bacterial Learning and Adaptation
2:05:56 - Giving Up on Birds
2:14:09 - Caltech
2:21:38 - Advice for Young Scientists
2:30:02 - Origins of Life
2:31:19 - What's Left for the Flagellar Motor?

PART 2:
2:33:33 - Building the Nanomotor
2:39:29 - Other Types of Flagella
2:47:06 - MotA and MotB
3:07:17 - Reusing Motors Across Biology
3:10:13 - Benefits of Being Small
3:12:34 - CheY and Changing Direction
3:19:39 - How Physics Shapes Evolution

Why are so many companies betting on neutral atoms to build the first useful quantum computers?

In this episode, we speak with Mark Saffman, professor at the University of Wisconsin–Madison and one of the pioneers of neutral atom quantum computing. Over the past two decades, Saffman has helped transform Rydberg atoms from a theoretical idea into one of the leading architectures for scalable, fault-tolerant quantum computing.

We explore the physics of optical tweezers and Rydberg blockade, how neutral atoms perform quantum logic and create entanglement, and why this platform offers unique advantages in connectivity and scalability. Saffman also discusses the engineering challenges of improving gate fidelity, implementing quantum error correction, and scaling from small laboratory experiments to processors containing millions of qubits.

We also discuss the origins of companies like Infleqtion, the rapid growth of the neutral atom ecosystem, and what it will take for quantum computers to solve meaningful scientific and industrial problems.

Whether you're interested in quantum computing, atomic physics, quantum error correction, computer architecture, or the future of information processing, this episode provides a deep technical look at one of the most promising paths toward practical quantum computers.

Follow us for more technical interviews with the world’s greatest scientists:
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Follow our hosts!
Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro and Reads
02:45 - Neutral Atoms vs Superconductors and Ions
07:30 - Rydberg Atoms
12:49 - Practical Considerations for Rydberg Atoms
19:04 - From Atomic Physics to Quantum Gates
29:49 - Increasing Trap Loading
38:27 - Evolution of Rydberg Gates
45:05 - Limits of Rydberg Fidelity
49:49 - Scaling Neutral Atom Arrays
53:47 - Atomic Species and QEC
1:03:38 - History of Infleqtion
1:10:27 - Mark’s Outlook on the Future
1:15:08 - Caltech and Peter Shor
1:20:00 - Advice for Young Scientists

#quantumphysics #quantumcomputing #physics #computerscience

Why are some of the world's largest technology companies betting on silicon photonics?

In this episode, we speak with John Bowers, professor at UC Santa Barbara and one of the pioneers of silicon photonics, about the technologies that are transforming AI infrastructure and modern data centers. Bowers explains why moving data has become one of the central challenges in computing, how optical communication is overcoming the limitations of traditional electrical interconnects, and why light is increasingly being used to connect processors, servers, and entire data centers.

We explore the origins of silicon photonics, from early optical communications research to the development of integrated photonic devices that can be manufactured using semiconductor processes. Bowers discusses the engineering challenges of combining lasers with silicon, the breakthroughs that enabled heterogeneous integration, and how decades of research helped turn silicon photonics into a commercial technology deployed at global scale.

We examine the growing demands of artificial intelligence, where the movement of information between processors has become just as important as computation itself. Bowers explains why bandwidth, power consumption, and interconnect density are emerging as critical bottlenecks for AI systems, and how optical links are enabling the next generation of large-scale computing architectures.

We also discuss data center networking, optical interconnects, co-packaged optics, heterogeneous integration, semiconductor manufacturing, photonic integrated circuits, telecommunications, AI hardware, and the future of warehouse-scale computing. Throughout the episode, Bowers provides an inside look at how advances in photonics are reshaping the infrastructure that powers modern computing.

Whether you're interested in silicon photonics, optical communications, semiconductor engineering, computer architecture, AI hardware, data center design, networking, integrated photonics, electrical engineering, or the future of computing, this episode provides a deep technical exploration of one of the most important technologies behind the AI revolution.

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Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin-168b94130/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:19 - Why Data Centers Need Photonics
05:28 - Bowers's Interest in Physics
10:09 - Lessons From Bell Labs
12:58 - Semiconductor Lasers
18:31 - Teaching Entrepreneurship
23:21 - Heterogeneous Integration
29:40 - Why Silicon Photonics Needed Better Light Sources
32:00 - Heterogeneous Integration vs Direct Growth
44:04 - The Packing Problem in Photonics
47:49 - Narrow Linewidth Lasers
51:31 - Data Centers in Space
59:19 - Lessons from the Telecom Bubble
1:02:17 - Recent Breakthroughs in Photonics
1:04:32 - What is a Frequency Comb?
1:07:07 - Solitons and Microcombs
1:14:48 - Optical Computing and AI
1:19:09 - How Bowers Starts Companies
1:21:56 - Was Bowers Late to Any Trends?
1:22:51 - What would Bowers Build with Unlimited Resources?
1:24:38 - Creating Bell Labs for AI
1:26:35 - Competition, Endurance, and Personality
1:30:41 - The Best Problems for Young Scientists to Tackle
1:37:47 - Advice for Researchers Who Want to Keep Real Depth

#photonics #datacenter #siliconphotonics #computerscience #artificialintelligence

How can a flatworm regenerate a complete head after being cut in half?

In this episode, we speak with Michael Levin, developmental biologist and director of the Allen Discovery Center at Tufts University, about the emerging field of developmental bioelectricity. Levin explains how voltage gradients, ion channels, and gap junctions form a layer of biological control that operates alongside genetics and biochemistry to regulate embryonic development, regeneration, and anatomical patterning.

We explore the experimental foundations of bioelectricity research, including the use of voltage-sensitive dyes, ion channel manipulation, and computational models to read and write electrical information in living tissues. Levin discusses how bioelectric signals help establish left-right asymmetry in embryos, coordinate communication across developing tissues, and encode large-scale anatomical information that individual cells cannot possess on their own.

The conversation examines classic and surprising experiments from the field, including the creation of two-headed planarian worms, the induction of ectopic eyes in frog embryos, and the restoration of normal development after severe genetic and environmental disruptions. Levin explains how bioelectric circuits can act as a control architecture for morphogenesis, allowing tissues to make collective decisions about growth, form, and regeneration.

We also discuss voltage gradients, membrane potentials, gap junction networks, developmental pattern formation, regenerative medicine, collective cellular intelligence, and the relationship between electrophysiology and gene regulation. Throughout the episode, Levin argues that understanding development requires looking beyond genes alone to the dynamic electrical communication networks that coordinate living systems across scales.

Whether you're interested in developmental biology, embryology, regeneration, electrophysiology, bioelectricity, morphogenesis, systems biology, ion channels, pattern formation, or the future of regenerative medicine, this episode provides a deep technical exploration of how electrical signals help shape living organisms.

Follow us for more technical interviews with the world’s greatest scientists:
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Follow our hosts!
Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Michael Dubrovsky: https://www.linkedin.com/in/michael-dubrovsky/
Xinghui Yin: https://www.linkedin.com/in/xinghui-yin-168b94130/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:40 - Early Interest in Bioelectricity
05:22 - External Electric Stimulation
19:54 - Two-Headed Planarians
31:40 - Designing Bioelectric Experimental Methods
56:37 - Different Model Organisms
1:07:34 - TAME Theory
1:24:16 - Xenobots and Advice for Young Scientists

#planaria #morphology #neuroscience #biology #bioelectricity

Are quantum computers changing the way we discover cancer treatments?

In this episode, Misha and Yudong spoke with Fred Chong, Seymour Goodman Professor at the University of Chicago, about the future of quantum computer architecture and how quantum algorithms could eventually help solve real-world problems in medicine, optimization, and scientific computing.

Chong explains the transition from the NISQ era toward fault-tolerant quantum computing, why hardware-aware software design remains essential, and how compiler architectures, error correction, and quantum system design all interact across the full computing stack. The conversation explores the challenges of building scalable quantum machines, the tradeoffs between superconducting qubits, trapped ions, and neutral atoms, and why many quantum systems may ultimately function as specialized accelerators alongside classical computers.

We also discuss quantum optimization algorithms like QAOA and how Chong’s group is applying them to cancer biomarker discovery and treatment prediction. By analyzing complex multimodal biological data, including DNA, mRNA, and pathology imaging, these methods aim to uncover patterns that are difficult for conventional machine learning systems to identify without overfitting.

Along the way, Fred shares stories from the early days of supercomputing at Thinking Machines, the origins of his quantum research career, the founding of Super.tech, and his perspective on where quantum computing is genuinely making progress versus where hype still dominates the conversation.

Topics include quantum computing, QAOA, fault-tolerant quantum computing, quantum error correction, quantum compilers, NISQ systems, neutral atoms, superconducting qubits, quantum architecture, cancer biomarkers, biomedical optimization, hybrid quantum-classical systems, and the future of quantum software and hardware co-design.

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Follow our hosts!
Mikhail Shalaginov: https://www.linkedin.com/in/mikhail-shalaginov/
Yudong Cao: https://www.linkedin.com/in/yudong-cao-25b6a929/

Subscribe:
Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269
Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR
Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:34 - From Jurassic Park to Quantum Computing
10:13 - Modernizing NISQ Research
13:45 - Designing Around Quantum Hardware
20:30 - Variational Quantum Algorithms
23:07 - Quantum Computers for Cancer Research
30:35 - How Q4Bio Began
37:20 - Will We Need QEC in the Future?
40:25 - What Quantum Computers Can Learn from Classical Architecture
43:08 - Would Fred Return to Classical Computing?
46:11 - Quantum Software and Quantum Compilers
55:19 - Starting Super.tech
1:01:43 - Classical Analogs to Quantum Hardware
1:12:21 - Advice for Young Scientists
1:17:43 - Is AI Impacting Quantum Research?
1:22:38 - Importance of Formal Verification
1:30:40 - QLDPC Codes
1:35:48 - Fred’s Beginnings in Computer Science
1:42:48 - Chicago vs Silicon Valley
1:46:27 - Do We Need More Quantum Software Companies?
1:53:17 - Future of Quantum Computing and Cryptography

#quantumcomputing #quantumalgorithms #cancerresearch #computerscience

How do you measure something as small as a single electron or map quantum behavior at the nanoscale?

In this episode, Misha spoke with Amir Yacoby, professor at Harvard University, about the cutting edge of quantum sensing and the experimental tools redefining how we probe the quantum world.

Yacoby explains how physicists build ultra-sensitive detectors, from single-electron transistors to quantum dots and NV centers in diamond, that can measure charge, spin, and magnetic fields with extraordinary precision. These tools make it possible to study both strongly correlated systems, like those exhibiting the fractional quantum Hall effect, and isolated quantum systems used as qubits.

We explore how accidental discoveries in the lab can evolve into entirely new sensing techniques, including momentum-resolved tunneling and nanoscale imaging methods. The conversation also highlights how quantum sensors are enabling researchers to bridge two regimes: complex many-body systems and controllable quantum devices, opening the door to new insights in topological physics and quantum information processing.

Whether you're interested in quantum measurement, nanoscale imaging, or the future of quantum technologies, this episode offers a detailed look at how new instruments are driving discovery at the frontiers of physics.

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Xinghui Yin: https://x.com/XinghuiYin

Subscribe:

Apple Podcasts: https://podcasts.apple.com/us/podcast/632nm/id1751170269

Spotify: https://open.spotify.com/show/4aVH9vT5qp5UUUvQ6Uf6OR

Website: https://www.632nm.com

Timestamps:
00:00 - Intro
01:23 - The Process of Creating Quantum Tools
11:28 - Graduate School at Weizmann
14:51 - From Aerospace to Condensed Matter
26:53 - Starting at Harvard
39:44 - Working at Bell Labs
47:42 - Diamond NV Centers
1:00:52 - Spin Waves
1:16:10 - SQUIDs
1:29:57 - State of the Art Sensors
1:33:08 - Motivations for Building Better Sensors
1:36:52 - Fabrication Challenges
1:40:14 - New Sensors
1:45:49 - Majoranas
1:53:25 - Finding New Applications for Sensors
1:57:16 - The Use of AI in Physics
1:58:55 - Advice for Young Scientists