The Future of Everything

It has been said that batteries hold the key to a sustainable future.But so-called “clean energy” does not come without environmental costs. For instance, says Stanford geoscientist Jef Caers, the batteries in a single Tesla contain some 4.5 kilograms — about 10 pounds — of cobalt, in addition to plenty of lithium and nickel, too. With some 300 million cars in the U.S. right now, a full transition to electric vehicles would be impossible without new resources. But, finding new deposits and getting them safely out of the ground is an expensive and environmentally fraught proposition. Half of all cobalt reserves and most of current production come from just one unregulated country, Congo. To close the gap using environmentally and labor-regulated resources, Caers says we need AI to rapidly explore countries with stricter safeguards.To help, geoscientists like Caers are turning to data science and artificial intelligence to quickly identify new resources, to get the most out of those we already know about and to improve refining processes to leave as small an environmental footprint as possible. Their success, he says, could be key to America’s environmental future and its long-term energy independence. Learn more on this episode of Stanford Engineering’s The Future of Everything podcast, hosted by Stanford bioengineer Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Evan Reed and a team of scientists recently identified a promising solid material that could replace highly flammable liquid electrolytes in lithium-ion batteries.The trick? Reed didn’t discover the material the old-fashioned way, using trial and error to narrow down a list of candidates. Instead, he used computers to do the legwork for him. He says that until recent advances in computer science, the seemingly never-ending search for new materials was more like a quest for unicorns. Breakthrough materials must possess that rarest of combinations: precise physical characteristics with few if any downsides.It's exacting and time-consuming work, Reed says, but computers are accelerating the pace of discovery. He now believes the future of materials science lies at the heart of a computer algorithm, as he tells listeners in this episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Renée DiResta is research manager at the Stanford Internet Observatory, a multi-disciplinary center that focuses on abuses of information technology, particularly social media. She’s an expert in the role technology platforms and their “curatorial” algorithms play in the rise and spread of misinformation and disinformation.Fresh off an intense period keeping watch over the 2020 U.S. elections for disinformation as part of the Election Integrity Partnership, DiResta says the campaign became one of the most closely observed political dramas in American history.She says that whether it comes from the top down or the bottom up, bad information can be spotted and beaten, but overcoming falsehoods in the future will require vigilance and a commitment to the truth. She explains more on Stanford Engineering’s The Future of Everything podcast, with host Russ Altman. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Once the bathwater is drained, the toilet flushed or the laundry done, few give a passing thought to the wastewater that leaves our homes. But chemical engineer Will Tarpeh might change your mind, if you give him the chance.Tarpeh says that that water is a literal mine of valuable chemicals. Chemicals like nitrogen, phosphorus and potassium make great fertilizers. Lithium can be used in lithium ion batteries. And even pharmaceuticals could be recovered and reused. In fact, Tarpeh points out that if we could harvest all the world’s urine, it could supplant 20–30% of our nitrogen needs — and in some places can be cheaper to do than existing production and transport methods.Waste, Tarpeh says, is just a state of mind. His “pipe dream,” he says, is to develop next-generation treatment plants on the neighborhood or even household scale able to extract the valuable chemicals in water most would rather send down the drain. Tarpeh tells bioengineer Russ Altman all about it in this the latest episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Bioengineer Kwabena Boahen builds highly efficient “neuromorphic” supercomputers modeled on the human brain. He hopes they will drive the artificial intelligence future. He uses an analogy when describing the goal of his work: “It’s LA versus Manhattan.”  Boahen means structurally. Today’s chips are two dimensional — flat and spread out, like LA. Tomorrow’s chips will be stacked, like the floors of the skyscrapers on a New York block. In this analogy, the humans are the electrons shuffling data back and forth. The shorter distances they have to travel to work, and the more they can accomplish before traveling home, will drive profound leaps in energy efficiency. The consequences could not be greater. Boahen says that the lean chips he imagines could prove tens-of-thousands times less expensive to operate than today’s power hogs. To learn how it works, listen in as Kwabena Boahen describes neuromorphic computing to fellow bioengineer Russ Altman in the latest episode of Stanford Engineering’s The Future of Everything podcast. Listen and subscribe here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

In a world where a drug takes years and billions of dollars to develop, just one in 20 candidates makes it to market. Daphne Koller is betting artificial intelligence can change that dynamic.Twenty years ago, when she first started using artificial intelligence to venture into medicine and biology, Koller was stymied by a lack of data. There wasn’t enough of it and what there was, was often not well suited to the problems she wanted to solve. Fast-forward 20 years, however, and both the quantity and quality of data, and the tools for studying biology, have advanced so dramatically that the adjunct professor of computer science at Stanford founded a company, insitro, that uses machine learning (a subspecialty of ​artificial intelligence) to explore the causes and potential treatments for some very serious diseases.She tells bioengineer Russ Altman about the lessons she’s learned along the way, and the challenges and rewards of getting diverse teams of experts from many fields to speak the same language. It’s all on this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

When Stanford bioengineer Markus Covert first decided to create a computer model able to simulate the behavior of a single cell, he was held back by more than an incomplete understanding of how a cell functions, but also by a lack of computer power. His early models would take more than 10 hours to churn through a single simulation and that was when using a supercomputer capable of billions of calculations per second.Nevertheless, in his quest toward what had been deemed "a grand challenge of the 21st century," Covert pressed on and eventually published a paper announcing his success in building a model of just one microbe: E. coli, a popular subject in biological research. The model would allow researchers to run experiments not on living bacteria in a lab, but on a simulated cell on a computer.After all was said and done, however, the greatest takeaway for Covert was that a cell is a very, very complex thing. There were fits and starts and at least one transcendent conceptual leap — which Covert has dubbed “deep curation” — needed to make it all happen, but he found a way. As Covert points out, no model is perfect, but some are useful. And that is how usefulness, not perfection, became the goal of his work, as he tells fellow bioengineer Russ Altman in this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

COVID-19 is changing how many scientists, like Stanford sleep expert Rafael Pelayo, MD, view their field. First off, the shift to telemedicine is providing Pelayo, author of the new book How to Sleep, an unprecedented glimpse into the sleep environments of his patients. “I’m making house calls for the first time,” he says.Second, surprisingly, some of his patients, unburdened of long commutes, say they are sleeping and dreaming more than ever. But, others are not so fortunate, reporting increased trouble sleeping and more nightmares. Pandemic-induced or not, the consequences of lost sleep are universal and readily apparent in the country’s diminished productivity, in the rates of stroke, heart attacks and car accidents, and in the pervasive irritable mood many can’t seem to escape.To get a better night’s sleep, Pelayo says, put the screens away, consider that continuous positive airway pressure (CPAP) machine if you snore (it could save your life, he says), and find a way to create a personal sleep environment even if you share a bed with someone you love.Join us as Rafael Pelayo and our host, Stanford bioengineer, Russ Altman, talk sleep on this episode of Stanford Engineering’s The Future of Everything podcast. Listen here, and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Marietje Schaake was a Member of the European Parliament from 2009 to 2019 and now serves as the international policy director at Stanford University’s Cyber Policy Center and international policy fellow at Stanford’s Institute for Human-Centered Artificial Intelligence. As she has watched democracy evolve in the age of instantaneous global communication and hyperconnected social media, she has grown concerned about the resilience of democracy as technology disrupts the status quo. While the technologies—and the often-unregulated companies who created them—claim to be well-meaning, she says democracy is under attack from propagandists and bad actors using these transformative tools in troubling ways. The business models based on surveillance and advertising were never designed with preserving democracy in mind. We now find ourselves at a decisive moment for the future of elective government, she says. America and other democratic nations can expose the meddlers and their techniques or succumb to their approaches. The solutions, she says, begin at the grassroots and with the tech companies. We need real-time and independent monitoring and research to better expose manipulations and to allow for evidence-based policy making. Join Stanford Engineering’s The Future of Everything podcast for an insider’s sobering look at democracy in the digital age. Listen here, and subscribe here to the podcast.  Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Andrew Huberman is a Stanford neurobiologist and ophthalmologist keenly interested in the biology of stress and ways to manage stress.He’s developed and tested a number of stress-relieving techniques — from specific patterns of breathing to visual tools — and uses virtual reality to help humans control their stress in adaptive ways. He is also testing how people can access better sleep using stress-relief tools. Much of this work is done in collaboration with David Spiegel, MD, associate chair of psychiatry and behavioral sciences at Stanford Medicine.Huberman studies how the nervous system takes in and processes information and uses it to drive reflexive and deliberate behavior. In that regard, humans are largely visual animals. The vast majority of the information we collect about the world comes through the eyes, and those circuits are tied directly to our most primordial “fight or flight” systems. Light, and how our brains process light energy, is closely tied to our stress mechanisms. Our most immediate reaction to stress, he notes, is for our pupils to dilate, which changes how we see the world — literally — in a way that allows us to better respond to threats. Breathing and vision can also be used to control stress.Huberman tells us all about it in this episode of Stanford Engineering’s The Future of Everything podcast, hosted by Stanford bioengineer Russ Altman. Listen and subscribe to the podcast here. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.