The Future of Everything

Biology is not typically considered a mathematically intensive science, says Noah Rosenberg, an expert in genetics, but all that is about to change.Math, statistics, data and computer science have coalesced into a growing interest in applying quantitative skills to this traditionally qualitative field.The result will be better and more accurate models of life, ranging from genetic inheritance to the entirety of human society. The yield will be a greater understanding and, quite possibly, revolutionary interventions into disease, ecology, demography, and even evolution itself. The tools of mathematical biology have never been more apparent, Rosenberg says, as mathematical models of the spread of infectious disease have been central around the world in the response to the COVID-19 pandemic.With applications in health care, forensic genetics, and human evolution, the tools of mathematical biology are proving more relevant and more needed than ever, as Noah Rosenberg tells Stanford Engineering’s The Future of Everything podcast, with host bioengineer Russ Altman. Connect With Us:Episode Transcripts >>> The Future of Everything WebsiteConnect with Russ >>> Threads / Bluesky / MastodonConnect with School of Engineering >>>Twitter/X / Instagram / LinkedIn / Facebook

Slowly but surely, the highly centralized, industrial electric grid that supplies power to the vast majority of American homes and business is changing.Our existing system of massive power plants and huge networks of high-voltage wires is giving way to a much leaner, decentralized system of small-scale power generation on a more personal, neighborhood- or residence-level scale.In other words, we’re going from an “infrastructure-centric” model to a “human-centric” one, says grid expert Ram Rajagopal. He says that the new grid will be much smarter, more inclusive and better able to adapt to the individual needs of users, helping them to schedule power-intensive tasks, like laundry or charging of electrical vehicles, to off-peak times of the day.  Before that day can come, however, Rajagopal says we’ll need new sorts of sensors and algorithms that will provide much more data about who, how and when people are using power, as he tells listeners to Stanford Engineering’s The Future of Everything podcast with host 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

The world’s once linear — take it, treat it, use it, dispose it — model of freshwater usage is changing fast.Despite two-thirds of Earth being covered in water, just 2.5% of it is fit for human consumption. And that share is dwindling by the day, says civil and environmental engineer and expert in water treatment and distribution systems Meagan Mauter. With a rapidly increasing population and climate change disrupting traditional weather and distribution patterns, access to freshwater is headed for, if not already amid, a worldwide crisis.Avoiding calamity will require industrial scale desalination and other technologies that can separate precious freshwater from other less desirable substances in the water, but also a shift to a more circular model where every drop of water is treasured and reused.Doing that, Mauter says, will demand doing away with not only inefficient practices but also the very notion of “waste” water, as she tells us in this episode of Stanford Engineering’s The Future of Everything podcast with host 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

Humankind has long harnessed the wind to its advantage. From ancient mariners to millers grinding grist, the wind has been an ally for millennia, but only now do engineers have at their disposal advanced computer simulations to better understand the details of wind flow and to optimize designs.Catherine Gorle is one such engineer who has made it her career to design better built environments able to improve walkability, temper extreme winds, shuffle air pollution far away and dissipate heat islands arising from so much sun-beaten concrete in our cities.Once, that work had to take place in wind tunnels, but now transpires through advanced computer simulations that both speed her work and add critical detail to her understanding of the close interrelationship between wind and human society. Join us as Catherine Gorle tells host bioengineer Russ Altman all about the future of wind on this episode 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

Anthony Kinslow II discusses the clean-energy divide, focusing on racial and socio-economic disparities. Solutions include energy audits for minority communities and diverse federal appointments. The podcast explores systemic issues and potential pathways to a more equitable energy future.

Electrical engineer Kunle Olukotun has built a career out of building computer chips for the world. These days his attention is focused on new-age chips that will broaden the reach of artificial intelligence to new uses and new audiences—making AI more democratic. The future will be dominated by AI, he says, and one key to that change rests in the hardware that makes it all possible—faster, smaller, more powerful computer chips. He imagines a world filled with highly efficient, specialized chips built for specific purposes, versus the relatively inefficient but broadly applicable chips of today. Making that vision a reality will require hardware that focuses less on computation and more on streamlining the movement of data back and forth, a function that now claims 90% of computing power, as Olukotun tells host Russ Altman on 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

Julie Owono is a lawyer, executive director of Internet Sans Frontières and a fellow at the Stanford Center on Philanthropy and Civil Society. She wants the world to know that the internet is the not the same for every person, everywhere. Born in Cameroon, and having grown up in Russia, she understands firsthand that every nation sets and maintains its own content standards.Owono has dedicated her career to establishing and securing basic digital rights, but also to developing standards by which social media giants—like Facebook, Google and Twitter—can distinguish hate speech from free speech. In many ways, Owono says, the global internet is a local endeavor.Owono tells Stanford Engineering’s The Future of Everything podcast and host Russ Altman that this dynamic means local voices will be critical to fairly determining standards of speech and, by extension, to charting the future of the global internet. You can 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

Words are a window into human psychology, society, and culture, says Stanford linguist and computer scientist Dan Jurafsky. The words we choose reveal what we think, how we feel and even what our biases are. And, more and more, computers are being trained to comprehend those words, a fact easily apparent in voice-recognition apps like Siri, Alexa and Cortana.Jurafsky says that his field, known as natural language processing (NLP), is now in the midst of a shift from simply trying to understanding the literal meaning of words to digging into the human emotions and the social meanings behind those words. In the social sciences, our great digital dialog is being analyzed to tell us who we are. And, by looking at the language of the past, language analysis promises to reveal who we once were. Meanwhile, in fields such as medicine, NLP is being used to help doctors diagnose mental illnesses, like schizophrenia, and to measure how those patients respond to treatment.The next generation of NLP-driven applications must not only hear what we say, but understand and even reply in more human ways, as Dan Jurafsky explains in his own words to host Russ Altman 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

When Riitta Katila looks at old photos or movies about the space program of the 1960s, she sees one common thread among the people depicted there — homogeneity. The engineers and technicians who first put humans on the moon were, almost without exception, white and male.While society has come a long way in the decades since, Katila, who is an expert in technology strategy and organizational learning, says there’s still a long way to go. She notes that companies need innovation not only to reach the top, but to stay there. And now more than ever, innovative companies should be hiring, promoting, and listening to a broader range of voices.The good news is that innovation can be taught. It’s like a recipe, says Katila, who encourages entrepreneurs — even those who have already built successful companies — to seek out mentors who can help them navigate the future. More important, those same entrepreneurs need to proactively identify mentors who can empower their team members to think like innovators too, as Katila tells Stanford Engineering’s The Future of Everything podcast, hosted by bioengineer Russ Altman. You can 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

As the silicon chip embarks upon its second half-century of dominance in computing and communications, the field is confronting fundamental boundaries that threaten to halt that progress in its tracks.The transistor cannot get much better or smaller and the copper wires that connect them cannot carry much more data than they do now. But, says electrical engineer David Miller, an alternative technology that uses light instead of electricity has the potential to transmit vastly more data than present technologies. It’s known as photonics.“A silicon chip these days looks like six Manhattan grids stacked atop one another,” Miller says of the challenge facing today’s technology. Photonics holds the promise of more powerful computing by beaming tiny packets of photons through light-bearing conduits that carry 100,000 times more data than today’s comparable wires, and it can do it using far less energy, too.Before that day can arrive, however, Miller says photonic components need to become much smaller and less expensive to compete with the sheer scale advantages silicon enjoys, and that will require investment. But, for once, a way forward is there for the asking, as Miller tells bioengineer Russ Altman, host 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