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Get 50% off Claude Pro, including access to Claude Code, at http://claude.ai/theoriesofeverything As a listener of TOE you can get a special 20% off discount to The Economist and all it has to offer! Visit https://www.economist.com/toe In this episode, I speak with Stephen Wolfram—creator of Mathematica and Wolfram Language—about a “new kind of science” that treats the universe as computation. We explore computational irreducibility, discrete space, multi-way systems, and how the observer shapes the laws we perceive—from the second law of thermodynamics to quantum mechanics. Wolfram reframes Feynman diagrams as causal structures, connects evolution and modern AI through coarse fitness and assembled “lumps” of computation, and sketches a nascent theory of biology as bulk orchestration. We also discuss what makes science good: new tools, ruthless visualization, respect for history, and a field he calls “ruliology”—the study of simple rules, where anyone can still make real contributions. This is basically a documentary akin to The Life and Times of Stephen Wolfram. I hope you enjoy it. Join My New Substack (Personal Writings): https://curtjaimungal.substack.com Listen on Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e SUPPORT: - Become a YouTube Member (Early Access Videos): https://www.youtube.com/channel/UCdWIQh9DGG6uhJk8eyIFl1w/join - Support me on Patreon: https://patreon.com/curtjaimungal - Support me on Crypto: https://commerce.coinbase.com/checkout/de803625-87d3-4300-ab6d-85d4258834a9 - Support me on PayPal: https://www.paypal.com/donate?hosted_button_id=XUBHNMFXUX5S4 SOCIALS: - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs Guests do not pay to appear. Theories of Everything receives revenue solely from viewer donations, platform ads, and clearly labelled sponsors; no guest or associated entity has ever given compensation, directly or through intermediaries. Learn more about your ad choices. Visit megaphone.fm/adchoices
Rising healthcare costs in the U.S. threaten people's access to treatment and services while reducing their ability to afford other necessities. Over the last decade, state policymakers across the political spectrum have responded to this urgent problem by passing legislation, setting up new government offices, and adding regulations to control healthcare spending. One critical element of states' maturing strategies for addressing healthcare costs is high quality, timely, and accessible data. In the latest episode of Mathematica's On the Evidence podcast, Jim Lloyd of the New Jersey Department of Health, Rachel Block of the Milbank Memorial Fund, and Julie Sonier of Mathematica discuss why rising healthcare costs present a complex and urgent issue, how states are responding, and the role of data in supporting solutions that address healthcare cost growth. “We have this healthcare system with much higher costs than other countries around the world, but we also have less access,” Lloyd explains. “There's an opportunity to be able to identify those costs that are contributing to quality, identify those costs that aren't, and then increase access and increase quality, potentially without increasing costs.” A blog summarizing the episode, with quotes from the guests and additional resources for further learning are available at https://mathematica.org/blogs/turning-data-into-solutions-for-reducing-healthcare-cost-growth-in-states
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On the latest episode of Mathematica's On the Evidence podcast, Dr. Agnes Kalibata reflects on her career as a scientist and as the former president of the Alliance for a Green Revolution in Africa (AGRA), an African-led organization that seeks to create an environment where Africa can sustainably feed itself. It does so by focusing on scaling agricultural innovations that help smallholder farmers achieve increased incomes, better livelihoods, and improved food security. Kalibata's 10-year term as AGRA president ended earlier this year. She spoke with Mathematica President and Chief Executive Officer Paul Decker last December. Mathematica supports AGRA's implementation of its 2023–2027 monitoring, evaluation, and learning strategy. On the episode, Kalibata and Decker discuss locally led development and the role of data in helping to understand how a program, such as AGRA's Seed Systems, can be more effective. Find a full transcript of the conversation here: https://mathematica.org/blogs/increasing-the-resilience-of-african-smallholder-farmers Learn more about Mathematica's work supporting AGRA as AGRA implements its 2023–2027 monitoring, evaluation, and learning strategy: https://mathematica.org/news/measuring-agras-impact-transforming-agricultural-systems-and-improving-climate-resilience
What's the secret to building unshakeable trust with your customers—especially when you're not face-to-face and your product passes through layers before it ever reaches the end user? That question has been top of mind for me, and it's exactly why I was so excited to sit down with Lisa Schwartz, Chief Operating Officer of Mathematica, on the latest episode of the Delighted Customers podcast. If you've ever wondered how trust really forms—not just in simple transactions, but in complex relationships where intermediaries stand between your company and your customers—you're not going to want to miss this conversation. The little things we do, and the way we handle nuanced moments, can echo throughout an entire organization and set the tone for customer loyalty and business success. I invite you to join me and Lisa as we explore the real-world power of trust. Lisa brings together an incredible mix of deep research, operational leadership, and street-smart experience (from her PhD in Developmental Psychology to her days as a bartender, practicing personalization long before it was a business buzzword). I learned so much from her perspective—she simply “gets it,” blending science, practical application, and genuine emotional intelligence in a way that makes it easy to apply to any customer relationship, no matter your industry or selling channel. Here are three powerful questions we tackle together on the show: How can you demonstrate credibility and reliability when you don't actually control the front-line customer interactions? What are best practices for creating intimacy and lowering self-orientation in situations where direct access to the end user isn't possible? What kinds of small gestures truly move the needle in building lasting customer partnerships and loyalty? If these are questions you wrestle with—or you want to elevate trust inside and outside your organization—I hope you'll listen in. Subscribe to Delighted Customers on Apple Podcasts and Spotify, or find us on your favorite podcast platform. Your feedback and support mean the world to me, and I can't wait for you to experience what Lisa has to share! Meet Lisa Schwartz Lisa Schwartz, Ph.D., is the Chief Operating Officer of Mathematica, a leading research and data consulting firm committed to improving public well-being through evidence-based solutions. With academic roots in developmental psychology (PhD, University of Maryland, College Park), Lisa spent years progressing from project leadership to executive management at Mathematica. Since 2019, she has driven the company's customer experience strategy across all divisions, spearheading initiatives that blend data-driven objectivity with a client-centric approach. Lisa's expertise lies in translating academic research into actionable, scalable business practices, all while championing relational trust as the cornerstone of every client journey. Catch Part 2 of 2 with Lisa on Episode #139! Connect with Lisa Schwartz on LinkedIn. Show Notes and References Learn more about Mathematica: mathematica.org Explore the Gottman Institute's work on emotional bank accounts: gottman.com Read about the Trust Equation from “The Trusted Advisor”: trustedadvisor.com Meet Lisa Lisa Schwartz brings 20 years of research and leadership experience to her role as COO at Mathematica, where she guides operational strategy and advances customer experience initiatives. A passionate proponent of evidence-based solutions, Lisa is recognized for blending the objectivity of research with the empathy required for impactful client relationships.
Note: This is Part 1 of a 2-part series What does it take to create an onboarding experience so powerful that clients can't imagine working with anyone else? For executives and customer experience leaders, the onboarding process is much more than an administrative formality—it's the first date, the pivotal moment when a client decides whether to pursue a deeper relationship or walk away. In this episode of the Delighted Customers podcast, Mark Slatin sits down with Lisa Schwartz, COO of Mathematica, to unpack the psychology and structure behind onboarding experiences that build trust, foster loyalty, and drive business results. Lisa draws from her unique blend of research expertise and executive experience to reveal why onboarding is critical for long-term client engagement and how intentional, personal touches can transform a standard process into lasting advocacy. Why listen to Lisa Schwartz? With a PhD in psychology from the University of Maryland and two decades at Mathematica, Lisa bridges academic rigor with operational excellence. She's led the company's customer experience transformation since 2019, skillfully adapting evidence-based practices to real-world client relationships. Lisa's passion for humanizing business, her practical analogies, and her research-backed strategies ensure takeaways for leaders seeking meaningful change in their organizations. Here are three provocative questions Lisa addresses in this insightful conversation: Why does the typical “welcome email” fall drastically short of what true onboarding should accomplish? What are the most common myths and pitfalls organizations fall into when designing onboarding experiences? How can customer experience leaders use psychological principles—like trust building and emotional “deposits”—to foster client relationships that last for years? Don't miss out! Listen to Lisa's episode of the Delighted Customers podcast and subscribe to get every new insight. Find the show on Apple Podcasts and Spotify, or on any of your favorite podcast platforms. Meet Lisa Schwartz Lisa Schwartz, Ph.D., is the Chief Operating Officer of Mathematica, a leading research and data consulting firm committed to improving public well-being through evidence-based solutions. With academic roots in developmental psychology (PhD, University of Maryland, College Park), Lisa spent years progressing from project leadership to executive management at Mathematica. Since 2019, she has driven the company's customer experience strategy across all divisions, spearheading initiatives that blend data-driven objectivity with a client-centric approach. Lisa's expertise lies in translating academic research into actionable, scalable business practices, all while championing relational trust as the cornerstone of every client journey. Catch Part 2 of 2 with Lisa on Episode #139! Connect with Lisa Schwartz on LinkedIn. Show Notes and References Learn more about Mathematica: mathematica.org Explore the Gottman Institute's work on emotional bank accounts: gottman.com Read about the Trust Equation from “The Trusted Advisor”: trustedadvisor.com Meet Lisa Lisa Schwartz brings 20 years of research and leadership experience to her role as COO at Mathematica, where she guides operational strategy and advances customer experience initiatives. A passionate proponent of evidence-based solutions, Lisa is recognized for blending the objectivity of research with the empathy required for impactful client relationships.
Stephen Wolfram is a British-American computer scientist, physicist, and entrepreneur best known for founding Wolfram Research and creating Mathematica and the computational knowledge engine Wolfram|Alpha. A child prodigy, he published scientific papers in physics by the age of 15 and earned his Ph.D. from Caltech at 20. He later developed A New Kind of Science, proposing that simple computational rules can explain complex phenomena in nature. Wolfram has been a pioneer in symbolic computation, computational thinking, and AI. His work continues to influence science, education, and technology.In our conversation we discuss:(00:00) What was the first version of AI?(23:38) What triggered the current AI revolution?(34:19) Did OpenAI base its initial algorithm on Google's work?(46:47) What is the technological gap between now and achieving AGI?(1:15:59) Do you fear an AI-driven world you can't fully understand?(1:35:15) What do we need to unlearn if AI can replicate human abilities?(1:47:39) What happens when there aren't enough jobs due to automation?(1:54:01) How is AI reshaping people's views on wealth?(2:25:48) The future of automating software developmentLearn more about Stephen WolframWebsite: https://www.stephenwolfram.com/index.php.enWikipedia: https://en.wikipedia.org/wiki/Stephen_WolframWatch full episodes on: https://www.youtube.com/@seankimConnect on IG: https://instagram.com/heyseankim
On the latest episode of Mathematica's On the Evidence podcast, M-KOPA Chief Executive Officer Jesse Moore talks about increasing access to financial and digital services for unbanked workers in Africa by leasing out smartphones. He and Paul Decker, the president and chief executive officer of Mathematica, discuss the needs of everyday earners in Africa who work regular but informal jobs that make it difficult to build credit and open a bank account. They also discuss the role of data in informing an organization's business strategy as well as assessing its social impact on customers. Find a blog summarizing highlights from the conversation, plus the full transcript here: mathematica.org/blogs/how-a-fintech-company-helps-workers-in-africa-access-credit-and-savings-with-smartphones
This episode features audio from an in-person roundtable discussion at the 2024 Association for Public Policy Analysis and Management Fall Research Conference. The roundtable focused on the five-year anniversary of The Foundations for Evidence-Based Policymaking Act and a recent report from the Government Accountability Office (GAO) on federal agencies' ability to assess their capacity to collect and use evidence. The panelists also discussed what needs to happen next to further strengthen the use of evidence in the federal government. The roundtable featured remarks from Erika Rissi, Nick Hart, Melinda Buntin, Rachel Snyderman, and Paul Decker. Rissi is the chief evaluation officer of the National Science Foundation, where she is also the Head of its Evaluation and Assessment Capability Section. Hart is the president and CEO of the Data Foundation. Buntin is a professor at the Johns Hopkins Bloomberg School of Public Health and the Carey Business School. Snyderman is the managing director of the Bipartisan Policy Center's Economic Policy Program. Decker is the president and chief executive officer of Mathematica. You can also read a short blog by Decker summarizing key themes from the roundtable here: https://mathematica.org/blogs/advancing-and-enhancing-evidence-based-policymaking Listen to a past episode of On the Evidence featuring a discussion about the five-year anniversary of the Evidence Act with experts from government, think tanks, research organizations, and academia: https://mathematica.org/blogs/building-on-the-evidence-act-to-increase-the-positive-impact-of-federal-policymaking Listen to a past episode of On the Evidence featuring Robert Shea, an expert on performance improvement in government who served on the bipartisan U.S. Commission on Evidence-Based Policymaking, a group whose recommendations informed the Evidence Act: https://mathematica.org/blogs/robert-shea-on-the-federal-governments-progress-in-using-evidence-to-improve-programs-and-policies
Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Do you foresee Notebook Assistant breaking out of the notebook in the future? It could be a great general voice assistant which knows about me personally and works like Iron Man's Jarvis. - Men on Mars by 2030? 16:28 Can you talk about the future of your Physics Project? - What's the future of an observer? - In many models of the universe, there are always small variations that lead to a division by zero, which leads the programmer to put in a fix. Could black holes be that fix in our universe? - What is your prediction for the future of science and technology in 2025? - What is an area physics might leak into that will be unexpected in the future? - Will you ever write another book like A New Kind of Science? - Dr. Wolfram could choose a dozen of his blog posts and publish them as a book and it would make a terrific book. - How might LLMs enhance future scientific development? What direction do you envision for tools like Mathematica, given that LLMs can interact with humans without requiring them to know how to program? - What is your opinion on ethical frameworks being applied to AI tools? What sort of ethics do you think should be applied when considering machine learning/AI tool research?
Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: For the new Notebook Assistant, what is the process for making a new product like that? - When making a new product, is it harder to create something brand new with no competition or easier when there are competing products to compare? - Good product; tbh I signed up and took it for a test drive yesterday. Great to chat and work Mathematica for a newbie like me; excellent progress in a short time. - I bought a Wolfram subscription for my daughter who is in Year 7. However, it seems it is not very straightforward in usability for a 12-year-old who can use in her study intuitively. - Would you consider enhancing or introducing new tools for a younger audience like my daughter? At least provide feature of ask random question in plain English and get concise answer with graphics to study science (chemistry, physics, biology). - Do you ever watch funny cat videos? - What do you think about Nvidia's CEO Jensen's approach to sending all through emails and having like 60 people directly report to him all day with email reports, and he is managing the whole company? - I would love to see software development discussions from the ground up. Sort of a Live Software Engineering series to complement the content of Live CEOing. E.g. building the WordCloud function. I like seeing the design reviews during Live CEOing, but I'm always wondering how the functions actually get implemented in code and how software developers approach programming Wolfram Language functions. - Do you have a cat? - How many meetings would you say you attend a day? How do you get the most out of them? - Apparently there is a small island inhabited by a throng of cats. They survive because the local fish jump out of the water onto the beach. - I saw a TikTok saying if you eat eggs raised on farms with cats on there, you can kick the allergy!! - Based on a random week earlier last month, you average about 12 meetings a week when they're "normal sized." - What are your tips for consistently practicing self-discipline?
In the same way a doctor uses data to diagnose and treat a patient, states' public health agencies use data to measure and address health in their communities. In the United States, states have the autonomy to decide their own data policies, which influences the amount, quality, and timeliness of public health data they produce. On the heels of the worst global pandemic in a century—and at a time when technology is significantly changing the way that information flows to public health agencies—a new report from the Pew Charitable Trusts offers a first-of-its-kind glimpse into the patchwork of state data policies and practices that together form our modern system for the nation's public health data. The latest episode of Mathematica's On the Evidence podcast features a discussion about the report's implications with Lilly Kan of the Centers for Disease Control and Prevention, Annie Fine of the Council of State and Territorial Epidemiologists, Mary Beth Kurilo of the American Immunization Registry Association, and Monica Huang of Mathematica. A full transcript of the episode is available at mathematica.org/blogs/modernizing-state-public-health-data-policies-and-practices Read a blog by The Pew Charitable Trusts' Margaret Arneson and Kathy Talkington about key takeaways from the report: https://www.pewtrusts.org/en/research-and-analysis/articles/2024/12/12/states-must-modernize-public-health-data-reporting-new-report-finds-promising-practices Read the full report from the Pew Charitable Trusts, which was supported with research by Mathematica: https://www.pewtrusts.org/en/research-and-analysis/reports/2024/12/state-public-health-data-reporting-policies-and-practices-vary-widely Read a LinkedIn article from Kathy Talkington of The Pew Charitable Trusts discussing key takeaways from the report: https://www.linkedin.com/pulse/public-health-data-reporting-strengths-shortcomings-kathy-talkington-gcdne/?trackingId=qNW27JNuSXq2Uf67iWKD9g%3D%3D Take an online quiz to test how much you know about public health data reporting: https://www.pewtrusts.org/en/research-and-analysis/articles/2024/12/12/how-much-do-you-know-about-public-health-data-reporting
On the latest episode of Mathematica's On the Evidence podcast, Lauren Supplee, the deputy assistant secretary for planning, research, and evaluation at the Administration for Children and Families, sat down for a wide-ranging conversation about the use of evidence in social policy. Supplee reflected on this year's White House blueprint on social and behavioral science in government, which included Head Start as an example of a government program for children and families that benefited from decades of social policy research overseen by the Administration for Children and Families. On the episode, Supplee also discussed the role of research in informing improvements to Head Start over time, how the Foundations for Evidence-Based Policymaking Act is changing the use of evidence in the federal government, and insights from Supplee's blog series on boosting the use of research evidence. Find a full transcript of the conversation here: https://mathematica.org/blogs/opres-lauren-supplee-on-boosting-the-use-of-social-policy-research Read the White House Office of Science and Technology blog announcing its Blueprint for the Use of Social and Behavioral Science to Advance Evidence-Based Policymaking: https://www.whitehouse.gov/ostp/news-updates/2024/05/15/applying-social-and-behavioral-science-to-federal-policies-and-programs-to-deliver-better-outcomes/ Read Lauren Supplee's blog about measuring whether and how evidence is used: https://www.acf.hhs.gov/opre/blog/2024/01/how-do-we-measure-whether-and-how-evidence-used Read Supplee's blog about cultivating more “knowledge brokers” in social policy research who translate complex data into action-ready insights: https://www.acf.hhs.gov/opre/blog/2024/07/can-we-all-develop-superpowers-knowledge-brokers Read Supplee's blog about establishing systems to support the use of evidence: https://www.acf.hhs.gov/opre/blog/2024/04/evidence-action-how-do-we-establish-systems-support-evidence-use Read a blog by Colleen Rathgeb, the former director of policy at the Office of Head Start and current associate deputy assistant secretary for the Office of Early Childhood Development, about research showing the need for full-day, year-round Head Start programs: https://www.acf.hhs.gov/archive/blog/2015/02/presidents-fy-2016-budget-head-start Explore the ELOF 2 Go mobile app, the free online tool Supplee references that supports teachers who want to access and learn more about the Head Start Early Learning Outcomes Framework (ELOF): https://play.google.com/store/apps/details?id=com.ohs.elof2go&hl=en_US&pli=1 Watch the video series referenced by Supplee that shares the perspectives and experiences of those who are involved in obtaining and using data from the American Indian and Alaska Native Head Start Family and Child Experiences Survey: https://www.acf.hhs.gov/opre/training-technical-assistance/overview-aian-faces-video-series
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In this episode, we chatted with Yvette Standberry, former Head of Innovation at Mathematica, about her journey as a Catalyst leader. Yvette shares how her commitment to "learning by doing" shaped her success. She shared the importance of recognizing patterns across systems to create efficiencies and how learning to tell compelling stories helps bring stakeholders on board at the right time. She emphasizes the importance of empowering others in the change process, cautioning that Catalysts can burn out if they try to carry all the weight themselves. Her wisdom reminds us that it's never "all about me"—true change happens when we treat stakeholders like customers, listening deeply to their needs and co-creating the future with them. For one of her favorite inspirational Catalysts, Yvette chose Maria Montessori, because she loves that inter-age group focused, learning by doing and through peers – all of which she is building into her next endeavor. Original music by Lynz Floren.
The latest episode of Mathematica's On the Evidence podcast features Jeffery Marino, the director of California's Office of Data and Innovation (ODI). For the podcast, Mathematica's President and Chief Executive Officer Paul Decker spoke with Marino about ODI's CalAcademy for training state employees in areas such as plain language and human-centered design, California Governor Gavin Newsom's executive order on generative artificial intelligence, facilitating interagency data sharing agreements, and data-driven storytelling about government's impact in people's lives. They also discussed Marino's career trajectory: he majored in English literature in college, became a data journalist, and now leads ODI, a department within California's Government Operations Agency encouraging collaboration across state agencies to improve digital services for all Californians. Find the full transcript of the interview: https://www.mathematica.org/blogs/embedding-data-and-innovation-across-california-state-government Learn more about ODI's CalAcademy: https://innovation.ca.gov/who-we-are/calacademy/ Read California Governor Newsom's executive order on generative AI: https://www.gov.ca.gov/wp-content/uploads/2023/09/AI-EO-No.12-_-GGN-Signed.pdf Listen to an On the Evidence interview with Jennifer Pahlka, author of Recoding America: Why Government is Failing in the Digital Age and How We Can Do Better, which is referenced in the discussion between Decker and Marino: https://mathematica.org/blogs/jennifer-pahlka-on-government-in-the-digital-age Explore a playlist of interviews between Mathematica's Paul Decker and fellow leaders of evidence-driven organizations: https://soundcloud.com/ontheevidence/sets/evidence-leadership?si=ea534d2c041c44e99c289a8d4dffa664&utm_source=clipboard&utm_medium=text&utm_campaign=social_sharing
The latest episode of Mathematica's On the Evidence podcast features an interview with Katherine Michelmore, an associate professor of public policy at the University of Michigan's Gerald R. Ford School of Public Policy and the 24th recipient of the David N. Kershaw Award and Prize. Michelmore's research has focused on temporary expansions of tax credits during the COVID-19 pandemic, which is part of a growing body of evidence informing state and federal policy proposals to make permanent some or all of those changes. On the episode, Michelmore talks about her experiences interacting with the media and policymakers about the subject of her research, using a novel source of data from a private mobile app to study the impacts of an expanded Child Tax Credit on households, and questions she would like to pursue in the future related to tax credits that support working parents and their children. Find the full transcript at mathematica.org/blogs/kershaw-award-winner-katherine-michelmore-on-how-expanded-tax-credits-benefited-family-well-being Check out the Spotify playlist with interviews with the 2020, 2021, 2022, and 2023 winners of the Kershaw Award: https://open.spotify.com/playlist/1Qz9HKUOxBhj33neIpPEUd?si=9oBu3VV2QJig8nUgKVVUKg&nd=1&dlsi=c61b4fd6357f426d Going to the 2024 APPAM Fall Research Conference? On the Evidence will be there, too. Find us at the Mathematica booth. Send us a message at jwogan@mathematica-mpr.com to let us know you're coming. Read a working paper co-authored by Michelmore on the effects of the temporary expansion of the CTC on the economic well-being of families, including a reduction in food insecurity: https://www.nber.org/papers/w30533 Read an article co-authored by Michelmore on the effects of the temporary expansion of the CTC on housing affordability and the living arrangements of families: https://read.dukeupress.edu/demography/article/61/4/1069/389197/The-Effects-of-the-2021-Child-Tax-Credit-on Read an article co-authored by Michelmore on the effects of the temporary expansion of the CTC on short- and long-term child development, including the likely improvement of children's health: https://journals.sagepub.com/doi/10.1177/00027162241264412 Read a working paper co-authored by Michelmore on the effects of the temporary expansion of the childless EITC: https://www.nber.org/papers/w32571
Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: What are your top picks for "startup ideas for Mathematica users"? - What's the future looking like for entrepreneurial business ventures and technology ones in particular, given what's happening with tools, capital, etc.? More solopreneurs? More big VC? Neither? - In business, do you think it is better to try and start a business with a totally new idea that hasn't been done before or to reinvent an old idea your way? - How do you advise young people with a similar all-consuming, intrinsic compulsion as yours, be it in their quest for knowledge/understanding or otherwise, and going about their careers/lives? - If you're debating the efficiency of algorithm design with your team, how do you navigate conflicting feedback? - Do you have an innately good memory or do you use memory tricks? - Did you ever play an instrument? - How do you develop speed reading and improve memory for a student or anyone who wishes to be better off intellectually? - What financial advice would you offer to someone developing a new business idea with limited capital? - When you run a business that provides a web service to international users, are you bound to comply with the laws of all countries from where the service is accessed? - Learning to ask better questions seems to be arguably more relevant than ever before. How do you learn to ask better questions?
In honor of Employee Ownership Month in October, Mathematica's On the Evidence podcast features a special episode with Paul Decker, Mathematica's president and chief executive officer, and Jim Bonham, the president and chief executive officer of The ESOP Association. On the episode, Decker and Bonham discuss the Employee Stock Ownership Plan (ESOP) as an evidence-based tool that benefits employees, consumers, and communities across the nation. An ESOP is a retirement vehicle for employees that many companies use to increase employee engagement and retain talent over time. As Decker and Bonham discuss on the episode, an ESOP can be more than a nice perk companies offer their employees. Business leaders and policymakers across the political spectrum have applauded the potential of ESOPs to strengthen the middle class and keep jobs in local communities. Research even shows ESOPs help reduce gender and racial wealth gaps. On the episode, Decker and Bonham discuss the benefits of ESOPs and challenges facing ESOPs going forward. A full transcript of the episode is available at https://www.mathematica.org/blogs/supporting-workers-and-strengthening-communities-through-employee-ownership Read the study from Institute for the Study of Employee Ownership and Profit Sharing within the School of Management and Labor Relations at Rutgers University that found ESOPs help narrow gender and racial wealth gaps: https://smlr.rutgers.edu/sites/smlr/files/Documents/News/rutgerskelloggreport_april2019.pdf Read an article in The Star-Ledger about the benefits of employee stock ownership plans for reducing wealth inequality and ensuring the longevity of a business, which describes Mathematica's experience with becoming an ESOP and quotes Paul Decker: https://www.nj.com/opinion/2024/09/nj-business-owners-need-a-succession-plan-and-workers-need-savings-we-can-solve-both-problems-opinion.html Learn more about Mathematica's history as an employee-owned company: https://mathematica.org/blogs/employee-ownership-is-at-the-heart-of-mathematica
Mieka Sanderson, Deputy Director for Public Health AmeriCorps, discusses the latest Notice of Funding Opportunity; Amy Wodarek O'Reilly, Principal Managing Consultant at Mathematica Policy Research, tells us Mathematica's role as an Implementation Center; ASTHO's upcoming webinar focuses on how to best navigate the rulemaking process; and applications are now open for ASTHO's Diverse Executives Leading in Public Health program. AmeriCorps Web Page: FY 2025 AmeriCorps State and National Grants ASTHO Web Page: Public Health Infrastructure Partners Launch National Implementation Center Program to Support Data Modernization PHIG Partners Web Page: Wave 1 (2024) Expression of Interest ASTHO Webinar: Navigating the Rulemaking Process ASTHO Web Page: Diverse Executives Leading in Public Health
A new episode of Mathematica's On the Evidence podcast explores recent research that experimented with a new approach to equitable data collection that also equips individuals and their organizations with new skills and resources. The Robert Wood Johnson Foundation contracted with Mathematica and its partner UBUNTU Research and Evaluation to learn how grassroots organizations in the housing justice movement had used grant funds for community power building. Through a fellowship program established by Mathematica and UBUNTU, researchers provided training in evaluation to fellows selected from staff at grassroots organizations while learning from those staff about the impact of the foundation's investment. The research also provided early evidence that the foundation's investment helped local grassroots organizations become more effective in achieving their affordable housing goals. On the episode, researchers and program fellows discuss the impact of the foundation's investment and how the fellowship model helped strengthen organizations' internal capacity to learn from campaigns and make evidence-informed changes. Find a full transcript of the episode at mathematica.org/blogs/how-evaluation-can-support-housing-justice-and-community-change Learn more about the housing justice and community power building evaluation conducted by Mathematica and UBUNTU on behalf of the Robert Wood Johnson Foundation: https://www.ubunturesearch.com/hjet Explore the interactive graphic that illustrates a new framework for community power building in the housing justice movement: https://mathematica.org/features/the-house-that-justice-built Learn more about the recent (open source) book Drew Koleros edited on updating theories of change for the field of evaluation, which includes sections that are relevant for evaluating community power building: https://www.routledge.com/Theories-of-Change-in-Reality-Strengths-Limitations-and-Future-Directions/Koleros-Adrien-Tyrrell/p/book/9781032669588?srsltid=AfmBOooKlrBZhZa5lb2HnU1K2Nw-IjWyQQ660RW0qfWxzw9P3FUTYpMU
Stephen Wolfram answers questions from his viewers about the history of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Recent thoughts on history - Was SMP or Mathematica inspired by LISP and what are the pros and cons of LISP-like languages? - Was the decision to have Mathematica untyped unlike something like Lean (proof checker) a good decision for usability or would you do it differently today? - Type-checking always felt like dimensional analysis. - Was your idea to use "transformations on symbolic expressions" a sudden insight after reading, say, Schönfinkel on combinators, or did it follow from working out atoms of computation, something else? - What is the history of lazy evaluation? - Have you come up with any new theories of human reasoning from working on Mathematica and computation?
The latest episode of Mathematica's On the Evidence podcast focuses on the potential for health data interoperability to improve people's health and well-being. Improved data interoperability is part of a broader push in the public and private sectors to use digital technology to make greater volumes of data available faster, at lower cost, and in higher-quality formats. These advances would make data easier to access, especially when needed to prevent or address urgent problems. In health care, the digital transformation in data could keep people healthier by improving the speed and quality of care patients receive. The episode features a discussion that originally aired as a webinar hosted by Mathematica's Health Data Innovation Lab, which examined strategies and tools for achieving greater data interoperability. During the webinar, Mathematica's Steve Linthicum moderated a conversation between Dr. Abel Kho of the Institute for Artificial Intelligence in Medicine at Northwestern University, Steven Gruner of HealthWare Systems, and Nicholai Mitchko of InterSystems. A full transcript of the episode is available at mathematica.org/ontheevidence Learn more about Mathematica's Health Data Innovation Lab: https://www.mathematica.org/sites/health-data-innovation-lab Watch the previous webinar hosted by Mathematica's Health Data Innovation Lab on data governance: https://www.mathematica.org/blogs/event-takeaways-using-data-governance-to-improve-health-outcomes Watch the previous webinar hosted by Mathematica's Health Data Innovation Lab on artificial intelligence: https://www.mathematica.org/news/health-ai-event-recap-its-all-about-the-data
Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Can you tell us more about your book collection (or your artifact or art collection)? - How does a "dashboard/portal" webpage as you show sometimes, with lists and links to your projects, and such tools, fit in your workflow and daily routines? - Stephen, are you also the CTO of Wolfram Research? What are the characteristics of a good CTO? - Do you find video calls draining? - What is the Wolfram software continuity plan in the event something happens to you? You are so instrumental in the development of this software, so your absence would be a hard gap to fill. - Did you have a mentor while creating your business? Do you find mentors useful? - Faces distract from logic because we spend too long assessing people's emotions. - Just wanted to share my personal Mathematica "story." I learned to know Mathematica way back when it was running on DOS in text mode and switched into graphics mode when I wanted to plot something. Later I switched to an early Windows version. Back then Macs were too expensive for me, but I loved that Mathematica was a free integral part of Macs! - Could you share your methods for generating and keeping track of ideas? Do you have favorite techniques for being productive?
Cecilia Rouse is the former dean of the Princeton School of Public and International Affairs and the current president of the Brookings Institution. For the first two years of the Biden administration, she was the chair of the Council of Economic Advisers—the first Black American to chair the council in its 75-year history. In August, she joined Mathematica's On the Evidence podcast for a conversation with Mathematica's President and Chief Executive Officer Paul Decker about leadership, the use of evidence in public policy, and the role of research organizations in improving public well-being. During the interview, Rouse talks about what she learned from her government posts about the role of research in informing policy decisions, how she thinks about the role of academic institutions in conducting policy research and training future public servants, how economics and related professions are doing at diversifying their workforces, and what she has learned about leadership. A full transcript of the episode is available at https://mathematica.org/blogs/cecilia-rouse-on-the-use-of-evidence-in-public-policy Listen to Rouse's January 2024 interview with the Brookings Institution's podcast, The Current, which posted shortly after she became the Brookings president: https://www.brookings.edu/articles/meet-cecilia-rouse-new-brookings-president/ Listen to Paul Decker's previous interviews about leadership and evidence-based decision making: https://staginginter.mathematica.net/search#q=paul%20decker&sort=relevancy&f:BlogSeries=%5BOn%20The%20Evidence%2DPodcast%5D&f:BlogSeries:operator=and
Thirty years ago, President Bill Clinton signed bipartisan legislation creating what is now known as AmeriCorps, a federal agency for national service and volunteerism. Since then, the agency estimates that more than 1.3 million AmeriCorps members and hundreds of thousands more AmeriCorps Seniors volunteers have provided billions of hours of service across each of the 50 states and U.S. territories. To commemorate the 30th anniversary of AmeriCorps, On the Evidence hosted a discussion about the role of data and research in helping AmeriCorps and its grantees deliver on their respective missions. The episode features Dr. Mary Hyde of AmeriCorps, Scott Richman of Mathematica, and Stephanie Garippa and Diana Gioia of Maggie's Place, an AmeriCorps grantee. On the episode, they discuss the important but complex task of measuring the impact of AmeriCorps, given that it seeks to not only spur higher levels of civic engagement and national service, but to simultaneously help its service members, partnering organizations, the communities in which both operate, and society as a whole. They talk about the kinds of evidence that AmeriCorps and grantees like Maggie's Place collect, how that evidence is used to drive impact, and how the role of evidence in guiding AmeriCorps' work has evolved over time. Read the 2023 AmeriCorps State of the Evidence Report: https://www.mathematica.org/publications/americorps-2023-state-of-the-evidence-report Find the full transcript for the episode at https://www.mathematica.org/blogs/how-americorps-uses-data-to-support-communities-through-national-service-and-volunteerism
Twenty years ago, the U.S. Congress created a new federal agency that represented a bold experiment in international aid. That agency, the Millennium Challenge Corporation (MCC), strove to reduce global poverty through grant-making to low- and lower-middle-income countries that demonstrated a commitment to good governance, economic freedom, and investing in their citizens. Part of what made MCC distinct in the international development space was its evidence-based approach, which focused on evaluating impacts and fostering a culture of learning and accountability to improve the effectiveness of aid. For this episode of Mathematica's On the Evidence podcast, and in recognition of the agency's 20th anniversary, Alicia Phillips Mandaville of MCC joins Jeff Bernson of Mathematica to discuss the agency's past, present, and future. Among other topics, Phillips Mandaville and Bernson discuss how MCC approaches country ownership and locally led development, how the agency's evidence-based approach to learning has evolved over time, and what MCC has learned about how to reduce poverty in developing countries. A full transcript of the episode is available at mathematica.org/blogs/twenty-years-of-insights-from-the-millennium-challenge-corporation-on-reducing-poverty. Visit MCC's 20th anniversary page, which reflects further on the agency's impacts over two decades: https://www.mcc.gov/about/priority/20th-anniversary/
Our guest for this episode of Mathematica's On the Evidence podcast is Dr. Aaron Carroll, a pediatrician, health researcher, and science communicator who recently assumed the post of president and chief executive officer at AcademyHealth, the leading national organization for convening and sharing information across health services researchers, policymakers, and health care practitioners. On the Evidence spoke with Carroll ahead of his organization's Health Datapalooza conference in mid-September. This year, the event is focused on data-driven solutions that address critical public health challenges. The conference's theme reflects a collaboration between AcademyHealth and the Centers for Disease Control and Prevention (CDC) to facilitate greater coordination and learning across health care and public health data systems. Mathematica is a member organization of AcademyHealth and a sponsor of the 2024 Health Datapalooza. In the episode, Carroll discusses what he has learned about effective science communication from blogging for The Incidental Economist, hosting the Healthcare Triage podcast, authoring several books, publishing research in peer-review journals, and contributing regularly to The New York Times. The interview covers a range of other topics as well, including the implications of climate change and artificial intelligence on health care and health services research; the need for greater interoperability among health and social services data systems; and the value of solutions for addressing the social determinants of health. Visit our website for a transcript of this episode: https://mathematica.org/blogs/aaron-carroll-on-the-future-of-health-services-research Watch the Healthcare Triage series on health and climate change: https://www.youtube.com/playlist?list=PLkfBg8ML-gInVPCl7zVMWvRX3SVwTRhgc Read Carroll's guest essay in The New York Times about lessons from other countries that could improve health care in the U.S.: https://www.nytimes.com/2023/06/13/opinion/health-care-reform.html Learn more about Mathematica's interdisciplinary climate practice: https://www.mathematica.org/sp/climate-change/climate-action Read a blog series by Mathematica staff about improving the quality and usability of social determinants of health data: https://www.mathematica.org/blogs/to-address-the-social-determinants-of-health-start-with-the-data Listen to a podcast about a federally-funded initiative to improve the collection of information from patients about their health-related social needs: https://www.mathematica.org/blogs/lessons-from-a-national-health-initiative-that-helps-address-social-needs Learn more about Mathematica's public health data modernization work, including recent projects for the Pew Charitable Trusts on public health data policies and practices in states, the Robert Wood Johnson Foundation on transforming public health data systems to advance equity, and operation of a Public Health Data Modernization Implementation Center for the CDC and Public Health Infrastructure Grant National Partners: https://www.mathematica.org/sp/public-health Learn more about Mathematica's Health Data Innovation Lab, which connects health care industry professionals with data scientists, social scientists, and technologists to address complex challenges within a health care organization or tackle broader issues related to fragmented care, social determinants of health, and health care inequality: https://staginginter.mathematica.net/sites/health-data-innovation-lab
In the United States, conversations about solutions to climate change often revolve around reducing fossil fuel emissions from human activities. But many believe regenerative agricultural practices and other nature-based solutions—which use soil and plants and try to either prevent or capture emissions—should complement policies and programs to reduce emissions from vehicles and power plants. As the nature-based climate solutions mature, public and private organizations that invest in them will need ways to measure their impact. In an interview with Mathematica's On the Evidence podcast, Dr. Jenny Soong, a soil biogeochemist within Mathematica's interdisciplinary climate practice, explains how better measurement, better data collection, and better web-based decision support tools could ensure the effective implementation of regenerative agriculture and other nature-based climate solutions. Find a full transcript of the episode at mathematica.org/ontheevidence. Learn more about Mathematica's interdisciplinary climate practice: https://www.mathematica.org/sp/climate-change/climate-action
Conrad Wolfram wants to transform the way we teach math — by taking advantage of computers. The Mathematica creator convinced the Estonian government to give his radical curriculum a try — so why is the rest of the world so resistant? SOURCE:Conrad Wolfram, strategic director and European cofounder/C.E.O. of Wolfram Research, and founder of computerbasedmath.org. RESOURCES:"In California, a Math Problem: Does Data Science = Algebra II?" by Amy Harmon (The New York Times, 2023).The Math(s) Fix: An Education Blueprint for the AI Age, by Conrad Wolfram (2020)."The Movement to Modernize Math Class," by Yoree Koh (The Wall Street Journal, 2020)."Math Rebels Invade Estonia With Computerized Education," by Klint Finley (Wired, 2013)."Do Left-Handed People Really Die Young?" by Hannah Barnes (BBC News, 2013)."Teaching Kids Real Math With Computers," by Conrad Wolfram (TED Talk, 2010). EXTRAS:"Bringing Data to Life," by People I (Mostly) Admire (2023)."Steven Strogatz Thinks You Don't Know What Math Is," by People I (Mostly) Admire (2023)."Mathematician Sarah Hart on Why Numbers are Music to Our Ears," by People I (Mostly) Admire (2021)."America's Math Curriculum Doesn't Add Up," by People I (Mostly) Admire (2021).
Listen on Spotify: https://open.spotify.com/show/4gL14b9... Donald Hoffman vs. Stephen Wolfram Stephen Wolfram is a renowned computer scientist, physicist, and the creator of Mathematica and the Wolfram Alpha computational engine, known for his groundbreaking work on cellular automata and computational theory. Donald Hoffman is a cognitive scientist and author, acclaimed for his revolutionary theories on consciousness and perception, suggesting that our senses provide a user interface rather than a direct window to reality. Join TOEmail at https://www.curtjaimungal.org Links Mentioned: Donald's book - https://www.amazon.com/Observer-Mecha... Stephen's TOE ep - https://www.youtube.com/watch?v=0YRlQ... Donald's TOE ep - https://www.youtube.com/watch?v=CmieN... Support TOE: - Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Crypto: https://tinyurl.com/cryptoTOE - PayPal: https://tinyurl.com/paypalTOE - TOE Merch: https://tinyurl.com/TOEmerch Follow TOE: - *NEW* Get my 'Top 10 TOEs' PDF + Weekly Personal Updates: https://www.curtjaimungal.org - Instagram: https://www.instagram.com/theoriesofeverythingpod - TikTok: https://www.tiktok.com/@theoriesofeverything_ - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 - Pandora: https://pdora.co/33b9lfP - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything
The latest episode of Mathematica's On the Evidence podcast coincides with June 19, which is celebrated by many around the United States as Juneteenth, a federal holiday commemorating the end of slavery in this country. Recently, one way staff at Mathematica have honored this important moment in U.S. history is by joining together in person and virtually on June 18th to read aloud and discuss a speech by Frederick Douglass titled “What to the Slave is the Fourth of July?” Douglass gave the speech in front of a predominately white abolitionist audience about 11 years before President Abraham Lincoln issued the Emancipation Proclamation, declaring more than three million enslaved people living in the Confederate states to be free. The speech focuses on the contradiction of celebrating liberty at a time when millions remained in slavery. It both celebrates the ideals of the country's founding and laments how the country has fallen short of those ideals. This episode of On the Evidence features an interview with Sheldon Bond, the deputy director of Mathematica's labor and employment area, who also acts as a co-lead for the company's Black Employee Resource Group. Mathematica's Black and Disability employee resource groups work with the Princeton Public Library to organize the readings of Frederick Douglass's speech. The episode also features clips from last year's Juneteenth event, with passages read by Mathematica's Rachel Miller, Sarah Lieff, Gloria Jackson, Stacie Feldman, Rachael Jackson, A'lantra Wright, Kirsten Miller, Boyd Gilman, and Dawnavan Davis. A full transcript from the episode is available here: mathematica.org/blogs/on-juneteenth-reflecting-on-our-collective-equity-journey Read Sheldon Bond's My Mathematica blog about how, as a natural introvert, he has learned to communicate, connect, and build relationships in the context of a growing company with an increasingly hybrid work culture: https://www.mathematica.org/blogs/my-mathematica-sheldon-bond
The Creative Process in 10 minutes or less · Arts, Culture & Society
“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“It's interesting to me that there are things that people have an intuitive sense of and have for a long, long time had an intuitive sense of that sometimes in science, there's been a tendency to say, "Oh, no, no, no. We have a particular way of thinking about things in science and that doesn't fit with it. So let's lock it out," so to speak. So an example of that, well, for example, animism; you mentioned this question of where are their minds? Is it reasonable to think of the weather as having a mind of its own? Is it reasonable to think of the forest as having a mind, so to speak? Well, in these kind of computational terms, yes, it does become reasonable to think about those things. Now if you say then, one comes to that idea from a place of formalized science, but nevertheless, it relates to sort of intuitions that people have had for a long time about that come from that didn't come from that particular kind of branch formalized thinking.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“It's interesting to me that there are things that people have an intuitive sense of and have for a long, long time had an intuitive sense of that sometimes in science, there's been a tendency to say, "Oh, no, no, no. We have a particular way of thinking about things in science and that doesn't fit with it. So let's lock it out," so to speak. So an example of that, well, for example, animism; you mentioned this question of where are their minds? Is it reasonable to think of the weather as having a mind of its own? Is it reasonable to think of the forest as having a mind, so to speak? Well, in these kind of computational terms, yes, it does become reasonable to think about those things. Now if you say then, one comes to that idea from a place of formalized science, but nevertheless, it relates to sort of intuitions that people have had for a long time about that come from that didn't come from that particular kind of branch formalized thinking.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I have grown up in the kind of Western scientific tradition, so to speak. And what's interesting to see is that some of the questions that we get to ask now have sort of grown out of the Western scientific tradition, are things that have also been asked in quite different traditions. , when I was a kid, people would talk about sort of at a religious level, they would talk about souls and so on. And one would say, "Well, that just can't be anything scientific." I mean, you know, what does a soul weigh? Anything that exists must have a weight; that sounded reasonable from the point of view of the narrow way of thinking about science at the time. Now that we understand this idea of computation, we understand that there can be a thing that is real and meaningful, but it doesn't have a weight. It is merely an abstract thing, a computational thing. And when we think about souls, that's, I think, the idea that what is going for is this kind of computational representation, this computational engram of what's in a brain, for example. And we now have a much better understanding of what that sort of engram, what that abstract, it has no physical weight or anything like that. It's just an abstract thing that can be rendered in a brain.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“My mother was a philosophy professor in Oxford, and when I was a kid, I would always say, if there's one thing I'll never do when I'm grown up, it's philosophy, because how can one be serious about a field where people are still arguing about the same things that they were arguing about 2,000 years ago, and there's no kind of apparent progress. But actually, the exciting thing has been that both in my kind of work in building computational language, and in my work in understanding the computational foundations of physics, that it turns out that a bunch of those things that people have been arguing about for a couple of thousand years, we can actually say some real things about.It's a funny thing because I've spent my life sort of building this big tower of science and technology and, every so often, something comes out of that tower that people say, "This is a cool thing, we're really going to be excited about this particular thing." For me, the whole tower is the thing that's really important. And in the future, that's what the tower that I've tried to build is certainly the most significant thing I've been able to do. And it's something that, you know, I've been able to see now over the course of half a century or so, kind of how various ideas I've had and directions I've gone have actually played out.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
“My mother was a philosophy professor in Oxford, and when I was a kid, I would always say, if there's one thing I'll never do when I'm grown up, it's philosophy, because how can one be serious about a field where people are still arguing about the same things that they were arguing about 2,000 years ago, and there's no kind of apparent progress. But actually, the exciting thing has been that both in my kind of work in building computational language, and in my work in understanding the computational foundations of physics, that it turns out that a bunch of those things that people have been arguing about for a couple of thousand years, we can actually say some real things about.It's a funny thing because I've spent my life sort of building this big tower of science and technology and, every so often, something comes out of that tower that people say, "This is a cool thing, we're really going to be excited about this particular thing." For me, the whole tower is the thing that's really important. And in the future, that's what the tower that I've tried to build is certainly the most significant thing I've been able to do. And it's something that, you know, I've been able to see now over the course of half a century or so, kind of how various ideas I've had and directions I've gone have actually played out.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
“I think one very big example of this phenomenon is the computational irreducibility. This idea that even though you know the rules by which something operates, that doesn't immediately tell you everything about what the system will do. You might have to follow a billion steps in the actual operation of those rules to find out what the system does.There's no way to jump ahead and just say, "the answer will be such and such." Well, computational irreducibility, in a sense, goes against the hope, at least, of, for example, mathematical science. A lot of the hope of mathematical science is that we'll just work out a formula for how something is going to operate. We don't have to kind of go through the steps and watch it operate. We can just kind of jump to the end and apply the formula. Well, computational irreducibility says that that isn't something you can generally do. It says that there are plenty of things in the world where you have to kind of go through the steps to see what will happen.In a sense, even though that's kind of a bad thing for science, it says that there's sort of limitations on the extent to which we can use science to predict things. It's sort of a good thing, I think, for leading one's life because it means that as we experience the passage of time, in a sense, that corresponds to the sort of irreducible computation of what we will do.It's something where that sort of tells one that the passage of time has a meaningful effect. There's something that where you can't just jump to the end and say, "I don't need to live all the years of my life. I can just go and say, and the result will be such and such." No, actually, there's something sort of irreducible about that actual progression of time and the actual living of those years of life, so to speak. So that's kind of one of the enriching aspects of this concept of computational irreducibility. It's a pretty important concept. It's something which I think, for example, in the future of human society, will be something where people right now will think of it as this kind of geeky scientific idea, but in the future, it's going to be a pivotal kind of thing for the understanding of how one should conduct the future of human society.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think one very big example of this phenomenon is the computational irreducibility. This idea that even though you know the rules by which something operates, that doesn't immediately tell you everything about what the system will do. You might have to follow a billion steps in the actual operation of those rules to find out what the system does.There's no way to jump ahead and just say, "the answer will be such and such." Well, computational irreducibility, in a sense, goes against the hope, at least, of, for example, mathematical science. A lot of the hope of mathematical science is that we'll just work out a formula for how something is going to operate. We don't have to kind of go through the steps and watch it operate. We can just kind of jump to the end and apply the formula. Well, computational irreducibility says that that isn't something you can generally do. It says that there are plenty of things in the world where you have to kind of go through the steps to see what will happen.In a sense, even though that's kind of a bad thing for science, it says that there's sort of limitations on the extent to which we can use science to predict things. It's sort of a good thing, I think, for leading one's life because it means that as we experience the passage of time, in a sense, that corresponds to the sort of irreducible computation of what we will do.It's something where that sort of tells one that the passage of time has a meaningful effect. There's something that where you can't just jump to the end and say, "I don't need to live all the years of my life. I can just go and say, and the result will be such and such." No, actually, there's something sort of irreducible about that actual progression of time and the actual living of those years of life, so to speak. So that's kind of one of the enriching aspects of this concept of computational irreducibility. It's a pretty important concept. It's something which I think, for example, in the future of human society, will be something where people right now will think of it as this kind of geeky scientific idea, but in the future, it's going to be a pivotal kind of thing for the understanding of how one should conduct the future of human society.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast
Within the past few years, organizations that help improve public well-being by providing data-driven insights have witnessed significant changes. From a digital transformation hastened by big data and artificial intelligence (AI) to the globalization of evidence-based solutions for problems that transcend borders, changes in technology, society, and culture are challenging leaders to rethink how their organizations operate. On the latest episode of Mathematica's On the Evidence podcast, NORC at the University of Chicago President and Chief Executive Officer Dan Gaylin joined Mathematica President and Chief Executive Officer Paul Decker for a wide-ranging discussion about leadership, AI, globalization, the COVID-19 pandemic, and advocating for the use of high-quality evidence without straying into activism. Find a full transcript at mathematica.org/blogs/norc-and-mathematica-ceos-on-the-future-of-data-and-evidence Read an article by Dan Gaylin on LinkedIn where he explains his philosophy around the importance of sharing research findings: https://www.linkedin.com/pulse/from-silence-significance-case-sharing-your-research-dan-gaylin-d1cve/?trackingId=Mm6Fa4kN4WbH29J%2FQArQrg%3D%3D Learn more about NORC's AmeriSpeak Panel: https://amerispeak.norc.org/ Learn more about NORC's 2020 Election Research Project for Facebook: https://www.norc.org/research/projects/2020-election-research-project.html Learn more about NORC's Advanced Data Solutions Center: https://www.norc.org/about/departments/advanced-data-solutions-center.html Watch Decker's interview with Mark Zandi, chief economist at Moody's Analytics, which includes a discussion about the declining response rates in federal surveys and what they might mean for informing policy decisions: https://www.mathematica.org/blogs/mark-zandi-chief-economist-of-moodys-analytics-on-data-driven-decisions-in-public-policy Watch Decker's interview with Max Stier, the president and CEO of the Partnership for Public Service: https://www.mathematica.org/blogs/the-partnership-for-public-services-max-stier-on-using-data-to-improve-the-government
This episode of Mathematica's On the Evidence podcast features a discussion about how various parties within the health care ecosystem can responsibly use artificial intelligence (AI) to improve patient health. The conversation comes amid increasing interest in the applications of AI in daily life and one month after Mathematica announced the launch of its Health Data Innovation Lab, a digital operational hub for government agencies, foundations, medical centers, and other health organizations to collaborate with data scientists and health policy experts. The episode draws from a recent webinar moderated by Noland Joiner, the chief technology officer of health care at Mathematica, with Ngan MacDonald and Ellie Graeden as guests. MacDonald is the director of health data innovations at Mathematica and Graeden is a partner and chief data scientist at Luminos.Law. She is also an adjunct research professor at Georgetown University. A transcript of the episode is available here: https://www.mathematica.org/blogs/improving-health-through-responsible-ai Learn more about Mathematica's Health Data Innovation Lab: https://www.mathematica.org/sites/health-data-innovation-lab
In his final years, Richard Feynman's curiosity took him to some surprising places. We hear from his companions on the trips he took — and one he wasn't able to. (Part three of a three-part series.) SOURCES: Alan Alda, actor and screenwriter.Barbara Berg, friend of Richard Feynman.Helen Czerski, physicist and oceanographer at University College London.Michelle Feynman, photographer and daughter of Richard Feynman.Cheryl Haley, friend of Richard Feynman.Debby Harlow, friend of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Lisa Randall, professor of theoretical particle physics and cosmology at Harvard University.Christopher Sykes, documentary filmmaker.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. RESOURCES: Quantum Man: Richard Feynman's Life in Science, by Lawrence M. Krauss (2011).Perfectly Reasonable Deviations From the Beaten Track: Selected Letters of Richard P. Feynman, edited by Michelle Feynman (2005).The Pleasure of Finding Things Out, by Richard Feynman (1999).The Demon-Haunted World: Science as a Candle in the Dark, by Carl Sagan and Ann Druyan (1995).Genius: The Life and Science of Richard Feynman, by James Gleick (1992).The Quest for Tannu Tuva, by Christopher Sykes (1988)“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985).Fun to Imagine, BBC docuseries (1983). EXTRAS: “The Brilliant Mr. Feynman,” by Freakonomics Radio (2024).“The Curious Mr. Feynman,” by Freakonomics Radio (2024).
What happens when an existentially depressed and recently widowed young physicist from Queens gets a fresh start in California? We follow Richard Feynman out west, to explore his long and extremely fruitful second act. (Part two of a three-part series.) SOURCES:Seamus Blackley, video game designer and creator of the Xbox.Carl Feynman, computer scientist and son of Richard Feynman.Michelle Feynman, photographer and daughter of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Lisa Randall, professor of theoretical particle physics and cosmology at Harvard University.Christopher Sykes, documentary filmmaker.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language.Alan Zorthian, architect. RESOURCES:"Love After Life: Nobel-Winning Physicist Richard Feynman's Extraordinary Letter to His Departed Wife," by Maria Popova (The Marginalian, 2017).Quantum Man: Richard Feynman's Life in Science, by Lawrence M. Krauss (2011).The Pleasure of Finding Things Out, by Richard Feynman (1999).Genius: The Life and Science of Richard Feynman, by James Gleick (1992)."G. Feynman; Landscape Expert, Physicist's Widow," (Los Angeles Times, 1990)."Nobel Physicist R. P. Feynman of Caltech Dies," by Lee Dye (Los Angeles Times, 1988).“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985).Fun to Imagine, BBC docuseries (1983)."Richard P. Feynman: Nobel Prize Winner," by Tim Hendrickson, Stuart Galley, and Fred Lamb (Engineering and Science, 1965).F.B.I. files on Richard Feynman. EXTRAS:"The Curious Mr. Feynman," by Freakonomics Radio (2024).
From the Manhattan Project to the Challenger investigation, the physicist Richard Feynman loved to shoot down what he called “lousy ideas.” Today, the world is awash in lousy ideas — so maybe it's time to get some more Feynman in our lives? (Part one of a three-part series.) SOURCES:Helen Czerski, physicist and oceanographer at University College London.Michelle Feynman, photographer and daughter of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. RESOURCES:"How Legendary Physicist Richard Feynman Helped Crack the Case on the Challenger Disaster," by Kevin Cook (Literary Hub, 2021).Challenger: The Final Flight, docuseries (2020).Truth, Lies, and O-Rings: Inside the Space Shuttle Challenger Disaster, by Allan J. McDonald and James R. Hansen (2009).Perfectly Reasonable Deviations From the Beaten Track: Selected Letters of Richard P. Feynman, edited by Michelle Feynman (2005).The Pleasure of Finding Things Out, by Richard Feynman (1999).Genius: The Life and Science of Richard Feynman, by James Gleick (1992).“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988)."Mr. Feynman Goes to Washington," by Richard Feynman and Ralph Leighton (Engineering & Science, 1987).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985)."The Pleasure of Finding Things Out," (Horizon S18.E9, 1981)."Los Alamos From Below," by Richard Feynman (UC Santa Barbara lecture, 1975)."The World from Another Point of View," (PBS Nova, 1973). EXTRAS:"Exploring Physics, from Eggshells to Oceans," by People I (Mostly) Admire (2023).
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