The Future of Everything

Professor of ophthalmology Daniel Palanker is a physicist who has combined his skills in optics and electronics to create PRIMA – the Photovoltaic Retinal Implant. Inserted beneath the retina, it restores vision to patients blinded by retinal degeneration, allowing them to read and write – and with the next-generation software, to recognize faces. PRIMA’s photovoltaic pixels act like tiny solar panels, converting light into electricity to stimulate the remaining retinal neurons. Better yet, the growing field of brain-computer interfaces may have implications beyond ophthalmology. “Unlike medicine, where the road ends with curing a disease or restoring lost function, the prospects for brain-machine interfaces may be infinite,” Palanker tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Daniel Palanker, a professor of ophthalmology and electrical engineering at Stanford University.

(00:03:17) Path into Ophthalmology

How Palanker’s background in physics and optics led him to vision research.

(00:04:33) How Vision Works

A primer on the eye, retina, photoreceptors, and the neural code of sight.

(00:08:50) Retinal Degeneration

How diseases like macular degeneration and inherited retinal disorders damage vision.

(00:13:18) The PRIMA Implant

How a photovoltaic retinal implant converts light into electrical stimulation.

(00:15:05) Augmented Reality Glasses

How camera-equipped glasses amplify and project images to power the implant.

(00:17:42) From Reading to Face Recognition

Why grayscale vision is the next step toward recognizing faces.

(00:20:18) Implanting the Device

How the wireless chip is placed under the retina and powered by light.

(00:21:45) Replaceable Vision Technology

How future generations of implants could be swapped in for higher resolution.

(00:22:28) Limits of Resolution

Why geometry and proximity to neurons determine how small pixels can get.

(00:24:00) Moving to 3D Electrodes

How pillar-shaped electrodes help neurons move closer to the implant.

(00:26:28) Clinical Path Forward

The status of European trials, FDA discussions, and future patient access.

(00:28:10) Safety and Real-World Use

What trials reveal about surgical risks, durability, and patients using implants at home.

(00:30:11) Future In a Minute

Rapid-fire Q&A: neural coding, brain-machine interfaces, and restoring vision.

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Engineer Aaron Lindenberg is an expert in the ways atoms and electrons move through materials. He uses X-ray “flash photography” to make movies of atoms moving at ultrafast speeds to predict the fundamental limits of electronics in future consumer devices, solar cells, and AI chips. He estimates we are “many orders of magnitude away” from the physical limits of both speed and energy efficiency in our electronics. Today’s computers are at least a thousand times slower than they could be, Lindenberg tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Aaron Lindenberg, a professor of Material Science & Photon Science at Stanford University.

(00:03:26) Path into Materials Science

How a biology problem inspired Lindenberg’s interest in atomic-scale dynamics.

(00:05:34) What Materials Scientists Study

Understanding how atoms, electrons, and ions create useful material properties.

(00:06:44) Seeing Atoms in Motion

How X-ray scattering and diffraction reveal atomic structure and dynamics.

(00:08:59) Femtosecond Timescales

Why ultra-fast measurements are needed to capture atomic motion.

(00:10:25) Making Atomic Movies

How researchers use snapshots to study materials as they change.

(00:13:08) Speed Limits in Materials

What determines how fast a material can switch between states.

(00:15:32) Faster and More Efficient Devices

Why electronics still have room to improve in speed and energy use.

(00:17:43) The Energy Cost of Switching

How fundamental energy limits shape future computing devices.

(00:19:10) Speed, Energy, and Reliability

The trade-offs that govern how materials perform in real devices.

(00:21:29) Solar Cells at the Atomic Scale

How materials convert light into electricity inside a solar cell.

(00:23:40) Capturing Energy Before It Becomes Heat

Why ultra-fast dynamics matter for improving solar cell efficiency.

(00:26:13) Randomness in Materials

How stochastic atomic motion affects material performance.

(00:28:20) Measuring Dynamic Complexity

Why nanoscale materials do not behave the same way every time.

(00:30:26) AI for Materials Research

How AI helps in Lindenberg's research

(00:32:56) Future In a Minute

Rapid-fire Q&A: science, collaboration, and future materials.

(00:36:13) Conclusion

 

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Commencement season is here and, as many students are closing one chapter and stepping into the next, it's a nice moment to ask: what did learning really look like for these students, and how might it change for the next generation? With those questions in mind, we’re re-releasing a conversation with Computer Science Professor Chris Piech on the future of computer-aided education. Chris studies how computers can and will help students learn. His message isn't that teachers are obsolete — far from it. He shares that the future of education certainly involves AI, but that we must never lose the human element. Whether you're a new grad, a lifelong learner, or an educator wondering what's coming next, this one is well worth another listen.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Chris Piech

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Chris Piech, a professor of computer science from Stanford University.

(00:01:44) Teaching People to Code

What programming is and why learning to code can be challenging.

(00:02:54) Motivation in Learning

Why joy and motivation are central challenges in education.

(00:03:54) Recent Learners as Teachers

How near-peer teachers helped scale a Stanford coding course to thousands 

(00:07:10) AI and Computer Programming

How generative AI is changing coding for students and professionals.

(00:09:24) The Joy of Programming

How AI tools can expand what learners are able to create.

(00:12:41) Experiments with Teaching

What experiments reveal about one-on-one teaching & AI support.

(00:14:39) Rethinking Assessment

The value Piech sees in computational assessment.

(00:16:38) Fairness in Grading

Why AI grading raises questions about bias, context, and real-world use.

(00:20:59) Feedback & Assessment

How computers can evaluate creative and less structured assignments.

(00:22:21) Dream Grader

A system that interacts with student projects to understand and assess them.

(00:25:30) Beyond the Classroom

How assessment tools can also support medical testing.

(00:26:52) Measuring Vision More Precisely

Using adaptive testing to improve eye exams and track subtle changes.

(00:27:57) Generative Grading

What is generative grading and how can it actually function and be useful?

(00:29:44) Teachers and AI Together

Why the future of grading may depend on combining teacher insight with AI support.

(00:31:33) Conclusion

 

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Food security expert David Lobell is immersed in the data of agriculture. He uses satellite imagery, yield data, and advanced computational modeling to analyze the roughly 500 million farms worldwide to increase productivity and ensure global food security – now and in the future. Though food is often taken for granted, feeding a hungry world is our greatest environmental challenge, he says. Lobell goes on to explain how data can do much more than increase yields – it also cuts costs, prevents conflicts, reduces emissions and deforestation, and improves nutrition. Smart farming is key to food security and avoiding the problems that stem from hunger, Lobell tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: David Lobell

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest David Lobell, a professor of Earth System Science at Stanford University 

(00:03:01) Path into Food Security

How Lobell’s interest in math and the environment led him to agriculture.

(00:04:31) Understanding Farming Systems

How farming differs across smallholder and large-scale operations.

(00:06:13) Agriculture’s Biggest Challenges

Improving productivity in developing regions &  reducing agriculture’s environmental impact.

(00:08:15) Farm Potential

How researchers estimate potential outputs & the barriers to better outcomes

(00:11:03) Using Satellites to Study Farms

How satellites help researchers understand what is happening in agriculture internationally.

(00:16:13) What Satellites Can Measure

Tracking crops, planting dates, harvest timing, yields, and management practices.

(00:18:23) Identifying Crops from Space

How seasonal patterns, biomass, and reflectance help distinguish crops.

(00:20:01) Why Food Matters

How food security connects to political stability, conflict, climate, and the environment.

(00:23:58) Cover Crops and Tradeoffs

Why a promising sustainability practice can sometimes reduce productivity.

(00:26:06) Crop Rotation Insights

How different rotations affect yields depending on local conditions.

(00:27:35) Personalized Farming

The importance of balancing large data with local information and implementation

(00:31:47) Future In a Minute

Rapid-fire Q&A: smarter farming, food access, and the future.

(00:33:01) Conclusion

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Fungi are “nature’s biological recycling machines,” says guest Vayu Hill-Maini, a former chef turned bioengineer. That is, they take waste and turn it into good things. Hill-Maini now melds his scientific and culinary skills to create new foods, but also medicines, faux leather, pigments and other valuable products from mushrooms and molds. He uses CRISPR gene editing technology to “domesticate” these fungi – removing off-flavors and increasing nutritional content to make new-age cheeses, burgers, salami, and more. “We call it the DBTL cycle – design, build, taste, learn,” Hill-Maini tells host Russ Altman about his creative process on this episode of Stanford Engineering’s The Future of Everything podcast.

Have a question for Russ? Send it our way in writing or via voice memo, and it might be featured on an upcoming episode. Please introduce yourself, let us know where you're listening from, and share your question. You can send questions to thefutureofeverything@stanford.edu.

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Stanford Profile: Vayu Hill-Maini

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Vayu Hill-Maini, a professor of bioengineering at Stanford University.

(00:03:33) From Chef to Bioengineer

How Hill-Maini’s culinary background led him to study food through science.

(00:05:23) Building a Lab with a Kitchen

Why his Stanford lab combines bioengineering research with culinary experimentation.

(00:07:32) What Are Fungi?

A primer on yeasts, molds, mushrooms, and their role in food and medicine.

(00:10:22) Domesticating Fungi

How humans have shaped fungi over thousands of years.

(00:14:23) Mushrooms as a Food Source

The nutrients, proteins, vitamins, and beneficial molecules found in fungi.

(00:16:21) Fungi as Biological Recyclers

Using fungi to turn food waste, agricultural waste, and other materials into useful products.

(00:18:22) Making Waste-Based Foods Desirable

Why taste, emotion, and culinary design matter for sustainable foods.

(00:20:22) Engineering Delicious Fungi

Using genetics and CRISPR to improve flavor, nutrition, and usability.

(00:22:50) Gentle Genetic Tweaks

Making small changes to reduce off-flavors or enhance useful traits.

(00:23:46) Design, Build, Taste, Learn

How the lab moves between kitchen and bench science to improve foods.

(00:24:06) Chefs in the Lab

How culinary collaborators help guide research and creativity.

(00:28:58) Fungi-Based Materials

The potential to create textiles, leather alternatives, and building materials.

(00:31:03) Future In a Minute

Rapid-fire Q&A: sustainability, students, and the promise of fungi.

(00:33:25) Conclusion

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