The Harry Glorikian Show

Three years after his first appearance, Butterfly Network CEO Joe DeVivo returns to catch Harry up on the roadmap. Butterfly's ultrasound-on-a-chip has evolved from a single handheld device into a foundational semiconductor platform that third parties can build on. The most dramatic example: Midjourney's full-body scanner, which rings 40 Butterfly chips around the body for whole-body tomographic imaging. Joe and Harry dig into what's real today versus what's coming, the physics of ultrasound, the path from demo to FDA clearance, and the business logic of "multiple shots on goal."

In this episode:

The chip as a platform: opening Butterfly's technology to third-party developers (the "Nvidia moment").

Midjourney's full-body scanner: tomography, 400 teraflops of data, and a roadmap toward a one-minute scan with the Apollo chip.

Real-world impact: 1,500 midwives trained in Kenya and South Africa, plus a new FDA-cleared gestational-age AI tool.

Partners beyond Midjourney: vascular robotics, fatty liver diagnosis, and brain-computer interfaces (including "silent speech").

Physics Q&A: why 360-degree imaging solves ultrasound's problems with air and bone.

The hospital shift: capturing "ghost" scans, Compass AI, and at-risk skilled-nursing deployments.

The 10-year vision: imaging that comes to the patient instead of the patient going to imaging.

Chapters:

(00:01) A roadmap from three years ago

(00:31) Midjourney unveils a full-body scanner

(01:31) Joe DeVivo returns

(02:59) What shipped: the chip becomes foundational

(04:52) Opening the platform to third parties

(06:34) Kenya and South Africa: midwives and the FDA-cleared gestational-age app

(11:11) FDA rigor and validating AI

(14:52) Butterfly Garden, Butterfly Embedded, and the nine partners

(16:53) Brain-computer interfaces and silent speech

(22:00) The Midjourney deal: origin and reaction

(24:03) Tomography explained

(28:12) What 40 chips can see and the data challenge

(29:33) The roadmap to a one-minute scan; the Apollo chip

(32:43) AI looking for a physical carrier

(34:31) Prototype to product: milestones to clearance

(38:28) Wellness first, then regulatory clearances

(39:03) The physics of air and bone

(41:45) The investment thesis: multiple shots on goal

(46:26) The business today: Compass AI and health-system deployments

(49:54) Heart-failure monitoring and at-risk skilled nursing

(53:49) The 10-year view: imaging comes to the patient

(57:18) Why early detection matters

(59:50) Closing

About the guest: Joe DeVivo is CEO of Butterfly Network and has spent 35 years in medical devices.

Also mentioned: Harry's book, The Invisible Interface: How AI Turns Intentions into Actions and Who Wins (foreword by Don Norman), available in print and ebook.

🎙️ In this episode, we discuss:

00:00 The Journey of an Innovator

06:27 The Birth of a Smartphone ECG

11:29 Overcoming Resistance in Digital Health

16:20 The Evolution of ECG Technology

23:43 The Importance of Early Detection in Cardiac Care

26:20 Innovations in 12-Lead ECG Technology

29:00 AI and Machine Learning in Cardiac Diagnostics

34:23 Remote Monitoring and Patient Empowerment

38:34 Navigating AI Diagnostics: Sensitivity vs Specificity

41:26 Consumer Wearables vs. Medical Devices

43:14 Future of AI in Cardiology and Personal Health Awareness

🎙️ In this episode, we discuss:

00:00 The Origin Story of Arrive Health

06:04 Rebranding and Evolving Mission

11:50 Real-Time Patient-Specific Drug Costs

18:08 Tackling Prior Authorization Challenges

22:56 Leveraging AI for Healthcare Efficiency

25:36 Understanding Scale and Impact

28:04 Collaboration with Payers and PBMs

30:27 Leveraging AI for Prior Authorization

32:43 Enhancing Access to Medications

36:27 Expanding Beyond Medications

38:19 Reframing Access to Care

40:51 Future Directions and Innovations

44:55 Wisdom for Innovators in Healthcare

🎙️ In this episode we discuss:

01:06 The founding story of Retina AI

03:56 Why ophthalmology is uniquely suited for AI solutions

06:27 Recent Series B funding and what it means for the company

08:31 How AI integrates into real-world clinical workflows

12:04 AI alerts and notifications for clinical decision support

16:36 Working with pharmaceutical companies on clinical trials

19:15 Predicting disease progression for untreated patients

25:42 The transition from traditional AI to newer approaches

29:28 Expanding beyond eye care with the Ikerian rebrand

32:06 Using the eye as a window to detect other diseases

37:44 How physicians have responded to AI diagnostic tools

41:09 Predictions for AI in healthcare and eye care by 2028

Chapters

00:00 Introduction and Company Updates

02:49 The Digital Transformation of Ultrasound Imaging

06:00 Advancements in Technology and Market Growth

09:03 AI Integration in Medical Imaging

14:50 Impact on Global Health and Humanitarian Efforts

20:55 Challenges in Mainstream Adoption of Handheld Ultrasound

29:43 Strategic Sales Approaches in Medical Devices

34:11 Finding Product-Market Fit

36:12 Simplicity in Medical Technology

39:26 Unexpected Use Cases and Market Adoption

45:24 Future Innovations in Handheld Ultrasound

51:58 The Importance of Patient Data Ownership

00:00 Introduction and Overview of Caristo Diagnostics

09:08 The Technology Behind Carry Heart

18:00 Clinical Implications and Risk Assessment

27:27 Actionable Steps for Patients

30:34 Optimizing Cardiovascular Drug Dosing

32:31 AI in Cardiovascular Medicine

33:50 Leveraging Historical Data for Risk Prediction

36:25 AI's Role in Molecular Pathway Analysis

39:03 GLP-1 and Cardiovascular Outcomes

41:56 Targeted Therapies in Cardiovascular Treatment

42:45 Building Trust in New Technologies

49:16 Regulatory Approvals and Future Prospects

54:15 Expanding Applications Beyond Cardiology

57:16 Looking Ahead: The Future of Caristo Diagnostics

In this episode of The Harry Glorikian Show, host Harry Glorikian welcomes back Jeff Elton, CEO of Concert AI, to discuss the latest advancements in AI-driven healthcare solutions. They reflect on the recent JP Morgan Healthcare Conference, highlighting the optimism surrounding AI's role in transforming drug development and oncology. Jeff shares insights into Concert AI's innovative data ecosystems, partnerships, and the introduction of Kera, an AI platform designed to enhance clinical decision-making. The conversation also explores the challenges and opportunities in the evolving landscape of healthcare technology, emphasizing the importance of collaboration and adaptability in the face of rapid change.

Takeaways:

The JP Morgan Healthcare Conference indicated a positive outlook for the industry.

AI is becoming a central theme in healthcare discussions.

Concert AI is developing a comprehensive data ecosystem for oncology.

The introduction of agentic AI models is set to revolutionize data processing.

Collaboration with NVIDIA is enhancing Concert AI's capabilities.

Kera is a significant advancement in AI-driven healthcare solutions.

The future of drug development will rely heavily on AI and data analytics.

Healthcare organizations must adapt to the rapid pace of technological change.

Building partnerships is crucial for addressing healthcare fragmentation.

The integration of AI in clinical trials can significantly reduce timelines.

Chapters

00:00 The Annual Healthcare Pilgrimage

03:19 Optimism in the Pharma Industry

06:07 The Rise of AI in Healthcare

10:03 Concert AI's Evolution and Innovations

15:10 2024: A Standout Year for Concert AI

18:55 Balancing Growth and Innovation

22:33 Scaling Across Therapeutic Areas

26:26 The Future of Collaborations in Healthcare

28:37 Integrating Immune Status and Data Collaboration

31:04 Introducing Kera AI: The Future of Data Management

35:24 Innovations in Clinical Trials and Data Solutions

40:16 Rethinking Drug Development: Digital Twins and AI

42:36 Navigating Market Shifts and Talent Challenges

54:02 The Future of Concert AI and Healthcare Solutions

Harry's guest this week is Raffi Krikorian, chief technology officer and managing director at Emerson Collective, the social change organization founded by Laurene Powell Jobs. Krikorian is the former vice president of engineering at Twitter (now X), where he was responsible for getting rid of the Fail Whale and making the company’s backend infrastructure more reliable; the former director of Uber's Advanced Technology Center in Pittsburgh, where he oversaw the launch of the world's first fleet of self-driving cars; and then the chief technology officer at the Democratic National Committee, where he helped rebuild the party's technology infrastructure after the Russian hacking debacle of 2016. At Emerson Collective, Krikorian built the technology organization, leads the development of data products, and works to upgrade the back offices of the non-profits Emerson works with. On top of all that, he recently launched a podcast called Technically Optimistic, where he’s taking a deep dive into the way AI is challenging us all to think differently about the future of work, education, policy, regulation, creativity, copyright, and many other areas. The show is a must-listen for anyone who cares about how we can build on AI to transform society for the better while minimizing the collateral damage. Harry talked with Krikorian about why he moved to Emerson Collective, why and how he started the podcast, and what he really thinks about what government should be doing to prepare for the waves of social change AI will bring.

For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast 

Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! 

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Generative AI is going to change how we do things across the entire economy, including the fields Harry covers on the show, namely healthcare delivery, drug discovery, and drug development. But we’re still just starting to figure out exactly how it’s going to change things. For example, AI is already speeding up the process of discovering new biological targets for drugs and designing molecules to hit those targets—but whether that will actually lead to better medicines, or create a new generation of AI-driven pharmaceutical companies, are still unanswered questions. 

One thing that’s for sure is that generative AI isn’t magic. You can’t just  sprinkle it like pixie dust over an existing project or dataset and expect wonderful things to happen automatically. In fact, just to use the data you already have, you have to you may have to invest a lot in the new infrastructure and tools needed to train a generative model. And that’s the part of the puzzle Harry focuses on in today's interview with David Buniatyan. He’s the founder of a company called ActiveLoop, which is trying to address the need for infrastructure capable of handling large-scale data for AI applications. He has a background in neuroscience from Princeton University, where he was part of a team working on reconstructing neural connectivity in mouse brains using petabyte-scale imaging data. At ActiveLoop, David has led the development of Deep Lake, a database optimized for AI and deep learning models trained on equally large datasets.

Deep Lake manages data in a tensor-native format, allowing for faster iterations when training generative models. David says the company’s goal is to take over the boring stuff. That means removing the burden of data management from scientists and engineers, so they can focus on the bigger questions—like making sure their models are training on the right data—and ultimately innovate faster.

For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast 

Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! 

Here's how to do that on Apple Podcasts:

1. Open the Podcasts app on your iPhone, iPad, or Mac. 

2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.

3. Scroll down to find the subhead titled "Ratings & Reviews."

4. Under one of the highlighted reviews, select "Write a Review."

5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 

6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.

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If you learned that radiologists looking at CT scans for the traditional signs of coronary artery disease catch only 20 percent of the people who actually have a high risk of a heart attack, and if you learned that there’s a new AI-based test that can catch subtle signs of inflammation in the other 80 percent of patients—well, you’d probably want to get that test yourself, right? Harry's guests this week, Frank Cheng and Keith Channon, are from a UK-based company that has developed just such a test. Cheng is the company's CEO, and Channon is co-founder and chief medical officer. And under their leadership, Caristo has introduced a test called CariHeart that applies machine learning to the data in a three-dimensional CT scan of the heart. It looks for otherwise invisible signs of inflammation in the fat tissue around the major coronary arteries, and then it predicts the chances that the patient will suffer a heart attack in the next eight years. Doctors can use that information to decide whether a patient needs to take a cholesterol-lowering drug like a statin or an anti-inflammatory drug like colchicine. 

Caristo’s test is being used on an experimental basis in the UK, and it hasn’t yet been approved for use in the US. But it’s a leading example of the way AI, put together with fundamental advances in our understanding of human biology, is really beginning to change the practice of medicine. Cheng and Channon say Caristo’s test isn’t intended to put cardiologists or radiologists out of work—it’s designed to help them be more effective. And given that cardiovascular disease is the number one cause of death around the world, any technology that can help catch signs of coronary artery disease earlier could save a lot of lives.

For a full transcript of this episode, please visit our episode page at http://www.glorikian.com/podcast 

Please rate and review The Harry Glorikian Show on Apple Podcasts or Spotify! 

Here's how to do that on Apple Podcasts:

1. Open the Podcasts app on your iPhone, iPad, or Mac. 

2. Navigate to The Harry Glorikian Show podcast. You can find it by searching for it or selecting it from your library. Just note that you'll have to go to the series page which shows all the episodes, not just the page for a single episode.

3. Scroll down to find the subhead titled "Ratings & Reviews."

4. Under one of the highlighted reviews, select "Write a Review."

5. Next, select a star rating at the top — you have the option of choosing between one and five stars. 

6. Using the text box at the top, write a title for your review. Then, in the lower text box, write your review. Your review can be up to 300 words long.

7. Once you've finished, select "Send" or "Save" in the top-right corner. 

8. If you've never left a podcast review before, enter a nickname. Your nickname will be displayed next to any reviews you leave from here on out. 

9. After selecting a nickname, tap OK. Your review may not be immediately visible.

On Spotify, the process is similar. Open the Spotify app, navigate to The Harry Glorikian Show, tap the three dots, then tap "Rate Show." Thanks!