The Future of Everything

Microbiologist Justin Sonnenburg wants you to know that you – and all humans, really – are not alone. Inside each of us live uncountable bacteria without whom we could not survive. Nowhere is this symbiosis more vital, Sonnenburg says, than in the digestive tract – the gut – where trillions of bacterial collaborators help digest the foods that nourish us. Sonnenburg studies what makes this complex relationship work and how modern life is altering this important chemistry. He says the gut microbiome should be thought of as another organ. When it drifts out of balance, the effects ripple through our metabolism, our immune systems, and our nervous systems. Sonnenburg goes on to explain how dietary choices – like eating more fermented foods and fiber – can rebuild the microbiome, and why the field’s next frontier could help alleviate chronic disease. “It really is a full-body impact that our microbes are having,” Sonnenburg 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: Justin Sonnenburg
Learn more about the Sonnenburg Lab
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Chapters:
(00:00:00) Introduction
Russ Altman introduces guest Justin Sonnenburg, a professor of microbiology and immunology at Stanford University.
(00:03:08) Path into Microbiome Research
How Sonnenburg became interested in the friendly microbes that live in and on the body.
(00:04:26) Bacteria as Partners
What are gut bacteria and how do they function in our bodies?
(00:06:23) Full-Body Effects
How gut microbes affect metabolism, immunity, and the brain.
(00:08:27) Industrialized Microbiomes
What does it mean that the gut microbiome has been “industrialized”?
(00:12:08) Feeding the Microbiome
Why is fiber important for gut health?
(00:15:59) Fiber Response
Study results from Stanford reflecting individual responses to fiber.
(00:17:14) Fermented Foods
How foods like yogurt, kimchi, sauerkraut, and kombucha can support microbiome diversity.
(00:20:36) Microbiome Therapeutics
How diet and microbial interventions could improve health.
(00:23:00) Food, Equity, and Access
Why microbiome health may require practical tools that work beyond major diet changes.
(00:24:02) Sharing Microbes
How social environments, diet, and exposure may influence the microbes people acquire.
(00:25:30) Precision Health
How the microbiome could help tune immunity, metabolism, and disease treatment.
(00:27:32) Women’s Health
Why reproductive health and women’s health are promising areas for microbiome research.
(00:28:33) Stanford Microbiome Research
How Stanford researchers are building interdisciplinary tools, tests, and therapies for microbiome science.
(00:30:36) Future In a Minute
Rapid-fire Q&A: microbiome health, daily decisions, and reversing Western disease trends.
(00:33:04) Conclusion

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As kids head back to school this month, we're re-releasing a conversation with cognitive scientist Michael Frank on the future of language learning. Michael studies the similarities and differences in how children and AI systems learn language. He’s working to understand what accounts for the “data gap” between how efficiently children learn language from relatively little input, compared to how much data AI systems need. His goal is to build better scientific models of human language acquisition and to inform how AI systems might learn in more human-like ways. Whether you’re parenting an infant or toddler who is learning to talk or you're simply curious about how language learning unfolds for people across languages and cultures, this one's a great 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.

Episode Reference Links:

Stanford Profile: Michael Frank

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Chapters:

(00:00:00) Introduction

Russ Altman introduces this episode with Michael Frank, a professor of biology, psychology and linguistics at Stanford University.

(00:02:05) AI and Child Language Learning

How AI language learning and child language learning differ.

(00:05:23) WordBank and Big Data

How large language databases are helping researchers study child language development across cultures.

(00:08:04) Learning Across Languages

How children learn many different languages through broadly similar developmental processes.

(00:08:57) Babbling and Early Speech

How babies begin exploring the sounds and signs of their language.

(00:10:04) Multimodal Learning

How SAYCam & BabyView capture multimodal language learning

(00:13:12) Language as a Social Tool

How social cues help children break the code of language.

(00:15:12) Learning from Others

How children track uncertainty and seek help from social partners.

(00:18:05) ManyBabies

How a global research consortium studies child development across cultures and communities.

(00:20:11) Global Development Research

Why large-scale international collaboration is valuable but difficult to fund.

(00:21:36) Pragmatics

How children learn to infer meaning beyond the literal words people say.

(00:23:21) AI, Intent, and Common Sense

Why pragmatics matters for building AI systems that understand human intent.

(00:24:21) Reading to Children

Why books can support language learning through shared attention and rich social interaction.

(00:26:38) Early Language Exposure

Why it is never too early to interact with babies through language.

(00:27:53) Multilingual Children

How children can learn multiple languages with few negative consequences.

(00:30:35) Conclusion

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Jackelyn Hwang is an expert on the social dynamics of cities. In one line of research, she combines AI and Google Street View to measure quality-of-life factors – such as trash, blight, new construction, and the pace of recovery from climate disasters – to analyze gentrification, racial equity, and overall resident well-being. Her work has shown, for instance, that predominantly Black neighborhoods are last and slowest to gentrify and that displaced Black residents often end up in worse neighborhoods. She recently worked with policymakers at the housing department of Oakland, California, on anti-displacement and anti-homelessness programs and is now working with policymakers across the Bay Area to strengthen neighborhoods. We are clearing a path to more stable communities for everyone, Hwang 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.

Episode Reference Links:

Stanford Profile: Jackelyn Hwang

Learn more about Jackie's work on housing instability in Oakland

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Jackie Hwang, a professor of sociology at Stanford University.

(00:02:53) Path into Urban Sociology

How Hwang’s experiences near Philadelphia shaped her interest in cities, inequality, and neighborhood change.

(00:04:56) The 21st-Century American City

How gentrification, immigration, crime, education, housing, and climate change are reshaping cities.

(00:08:03) Defining Gentrification

How sociologists understand gentrification as a class-based transformation of neighborhoods.

(00:10:02) Studying Gentrification

Why race, segregation, and neighborhood inequality complicate simple stories of urban renewal.

(00:11:50) Displacement and Instability

Why gentrification does not always increase moving rates, but still affects where people end up.

(00:14:48) Policy and Anti-Displacement

How Hwang’s research informs local policy, housing strategy, and homelessness prevention.

(00:18:10) Measuring Neighborhood Change

How technology can help researchers study changing neighborhoods at scale.

(00:18:55) Google Street View and Cities

How Street View opened new ways to observe gentrification and neighborhood conditions.

(00:20:36) Computer Vision for Urban Research

How AI and computer vision are being used to analyze neighborhood conditions.

(00:21:53) What Neighborhoods Reveal

How visible signs like trash, blight, vacant lots, and construction signal neighborhood change.

(00:23:10) Eye Tracking and Perception

How researchers study what people notice in neighborhoods and how those cues affect stress.

(00:24:09) Climate Change and Recovery

How disasters can widen neighborhood inequality through uneven rebuilding and abandonment.

(00:26:14) Neighborhoods and Wellbeing

How better measurements of neighborhood conditions could guide interventions for safer, more stable communities.

(00:28:00) Future In a Minute

Rapid-fire Q&A: affordable housing, neighborhood change, and better urban data.

(00:29:32) Conclusion





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Today, we're re-releasing my conversation with psychiatrist Anna Lembke on the future of addiction. Whether its substances, screens, or work itself, addiction in some form touches nearly all of our lives either directly or through someone we care about. Anna breaks down the dopamine mechanisms behind addiction of all kinds, from opioids to social media to, in her own case, romance novels, and shares what actually works in recovery, including exercise and structured abstinence. Whether you're thinking about screen habits, substance use, or just how to build healthier routines, this one's 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.

Episode Reference Links:

Stanford Profile: Anna Lembke

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Chapters:

(00:00:00) Introduction

Russ Altman introduces Anna Lembke, a professor of psychiatry and behavioral sciences at Stanford University.

(00:01:52) Defining Addiction

Why addiction involves compulsive use despite harm, even when the behavior seems ordinary.

(00:03:31) Romance Novels and Harm

How Lembke’s own reading habit became a case study in subtle addiction.

(00:05:49) Dopamine and the Addicted Brain

What repeated dopamine spikes do to reward pathways and withdrawal symptoms.

(00:08:34) Seeing the Problem

How naming a compulsive habit can make it visible and open the door to change.

(00:10:34) Addiction Medicine Today

How the opioid epidemic changed medical training and addiction awareness.

(00:12:48) Russ Altman’s “Addictions”

Russ details his own dopamine habits for the audience.

(00:14:37) Exercise and Hormesis

Why movement, effort, and discomfort can help restore healthier dopamine patterns.

(00:17:22) Dopamine Fasting

The self-intervention Dr. Lembke used & her potential cross-addictions.

(00:21:22) Vulnerability to Addiction

Why genetic risk, family history, and drug of choice shape addiction vulnerability.

(00:22:53) The Opioid Epidemic

How prescription opioids, heroin, and fentanyl shaped three waves of crisis.

(00:24:51) Fentanyl and Overdose Risk

Why counterfeit pills and fentanyl exposure can be lethal even for new users.

(00:26:28) Treating Opioid Addiction

Why medications like methadone and buprenorphine help restore stability.

(00:28:17) The Future of Addiction

Why Lembke sees addiction as a long-term challenge across drugs, media, and food.

(00:29:22) Conclusion

 

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Psychologist Russ Poldrack is a mind reader of sorts, but not in the traditional sense of the word. Instead, he makes movies of blood flow in the brain using functional MRI to draw insights into the function of specific regions of the brain to decipher how they control behavior. In one example, Poldrack has shown how people with obsessive-compulsive disorder have enhanced “salience networks” that turn on when surprising things happen. This finding could have “very profound” outcomes in diagnosis and treatment, Poldrack tells host Russ Altman in this wide-ranging exploration of the implications and the ethics of functional neuroimaging on 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.

Episode Reference Links:

Stanford Profile: Russ Poldrack

Poldrack Lab website: http://poldracklab.org

The MyConnectome project: https://www.myconnectome.org/

Stanford Center for Open and Reproducible Science: https://datascience.stanford.edu/cores

Connect With Us:

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Chapters:

(00:00:00) Introduction

Russ Altman introduces guest Russ Poldrack, a professor of psychology and of psychiatry and behavioral science at Stanford University.

(00:03:15) Path into Neuroimaging

How Poldrack moved from cognitive psychology into functional MRI research.

(00:04:18) Functional MRI

How MRI can be used to track brain activity.

(00:06:59) Mapping Brain Activity

How tasks and behaviors are linked to patterns of brain activation.

(00:08:02) Resting Functional MRI

How resting scans revealed large-scale brain networks.

(00:09:00) Brain Networks and Behavior

How the brain controls stopping, switching, and habits.

(00:10:34) Layers of Brain Organization

Why neuroimaging studies the brain across multiple scales.

(00:13:04) Individual Brain Differences

How shared brain networks vary across individuals.

(00:13:34) Scanning Himself

Why Poldrack repeatedly scanned his own brain.

(00:15:47) Mapping One Brain Deeply

How repeated scans revealed reliable individual brain patterns.

(00:18:59) Neuroimaging and Mental Health

How brain network differences may relate to depression and OCD.

(00:21:42) Reproducibility in Brain Imaging

How larger and deeper data sets improve reliability.

(00:24:51) Analytic Variability

Why the same data can produce different conclusions.

(00:26:39) Multiverse Analysis

How testing many analyses helps identify stable findings.

(00:27:55) Open Science

How data sharing and standards improve transparency.

(00:30:29) Privacy and Brain Data

How researchers protect participants when sharing neuroimaging data.

(00:32:17) Future In a Minute

Rapid-fire Q&A: neuroimaging, reproducibility, and AI in science.

(00:33:22) Conclusion

 

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