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AI and I

Author: Dan Shipper

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Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves.

For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest.
26 Episodes
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Dr. Bradley Love is building a tool that can predict the future. Dr. Bradley Love is transforming neuroscience research with AI. He's the creator of BrainGPT, a large language model that can predict the results of neuroscience studies—before they’re conducted. And it performs better than human experts. We spent 90 minutes exploring how AI is reshaping scientific research and our understanding of the brain. Bradley argues that as scientific knowledge grows exponentially, we need new tools to make sense of it all. BrainGPT isn't just summarizing existing research—it's predicting future discoveries. We get into: • How BrainGPT outperforms neuroscience professors • Why clean scientific explanations may be a thing of the past • The challenges of interpreting complex biological systems • How AI could change the way we approach scientific research • The limitations of our intuitive understanding of the brain This is a must-watch for anyone interested in the future of science, AI, and how we understand the human mind. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: • Subscribe to Every: https://every.to/subscribe • Follow him on X: https://twitter.com/danshipper Timestamps: 00:00:00 - Teaser 00:01:00 - Introduction 00:01:58 - The motivations behind building a LLM that can predict the future 00:11:14 - How studying the brain can solve the AI revolution’s energy problem 00:13:32 - Dr. Love and his team have developed a new way to prompt AI 00:18:27 - Dan’s take on how AI is changing science 00:22:54 - Why clean scientific explanations are a thing of the past 00:29:49 - How our understanding of explanations will evolve 00:37:31 - Why Dr. Love thinks the way we do scientific research is flawed 00:40:42 - Why humans are drawn to simple explanations 00:45:03 - How Dr. Love would rebuild the field of science Links to resources mentioned in the episode: Dr. Bradley Love: https://bradlove.org/; https://twitter.com/ProfData BrainGPT: https://braingpt.org/ Thomas Nagel’s book on the philosophy of science that Dr. Love recommends: The View From Nowhere The essay that Thomas Nagel is famous for: What is it like to be a bat?
Claire Vo built ChatPRD—an on-demand chief product officer powered by AI. It’s now used by over 10,000 product managers and is pulling in six figures in revenue. The best part? Claire has a demanding day job as the CPO at LaunchDarkly. So she built all of ChatPRD herself—over the weekend—with AI. I sat down with Claire to talk about how ChatPRD works, how she built it as a side hustle using AI, and all of the ways she’s using AI tools to accelerate her work and life. We get into: How she used AI to build ChatPRD over Thanksgiving break The part of product management that Claire thinks AI will disrupt Why the PMs of tomorrow will be “proto-managers” who create prototypes rather than just specs How junior PMs can use AI to upskill faster The ways in which ChatPRD is baked into her own workflow How building ChatPRD is making Claire a better PM How Claire uses AI as a tech-forward parent This is a must-watch for anyone interested in turning their side hustle into a thriving business or who works in product. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Claire Vo: https://x.com/clairevo ChatPRD: https://www.chatprd.ai/; https://x.com/chatprd; https://www.linkedin.com/company/chatprd/; https://www.youtube.com/@ChatPRD Some of the AI tools that Claire used to build ChatPRD: http://Clerk.dev; https://tiptap.dev/ Greeking Out, the Greek mythology podcast that Claire’s son enjoys: https://www.nationalgeographic.com/podcasts/greeking-out
An interview with best-selling sci-fi novelist Robin SloanOne of my favorite fiction writers, New York Times best-selling author Robin Sloan, just wrote the first novel I’ve seen that’s inspired by LLMs. The book is called Moonbound, and Robin originally wanted to write it with language models. He tried doing this in 2016 with a rudimentary model he built himself, and more recently with commercially available LLMs. Both times Robin found himself unsatisfied with the creative output generated by the models. AI couldn’t quite generate the fiction he was looking for—the kind that pushes the boundaries of literature. He did, however, find himself fascinated by the inner workings of LLMs Robin was particularly interested in how LLMs map language into math—the notion that each letter is represented by a unique series of numbers, allowing the model to understand human language in a computational way. He thinks LLMs are language personified, given its first heady dose of autonomy. Robin’s body of work reflects his deep understanding of technology, language, and storytelling. He’s the author of the novels Mr. Penumbra’s 24-hour Bookstore and Sourdough, and has also written for publications like the New York Times, the Atlantic, and MIT Technology Review. Before going full-time on fiction writing, he worked at Twitter and in traditional media institutions. In Moonbound, Robin puts LLMs into perspective as part of a broader human story. I sat down with Robin to unpack his fascination with LLMs, their nearly sentient nature, and what they reveal about language and our own selves. It was a wide-ranging discussion about technology, philosophy, ethics, and biology—and I came away more excited than ever about the possibilities that the future holds. This is a must-watch for science-fiction enthusiasts, and anyone interested in the deep philosophical questions raised by LLMs and the way they function. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Links to resources mentioned in the episode: Robin Sloan: https://www.robinsloan.com/  Robin’s books: Mr. Penumbra's 24-Hour Bookstore, Sourdough, Moonbound Dan’s first interview with Robin four years ago: https://every.to/superorganizers/tasting-notes-with-robin-sloan-25629085  Anthropic AI’s paper about how concepts are represented inside LLMs: https://www.anthropic.com/news/mapping-mind-language-model  Dan’s interview with Notion engineer Linus Lee: https://www.youtube.com/watch?v=OeKEXnNP2yA  Big Biology, the podcast that Robin enjoys listening to: https://www.bigbiology.org/ 
We use it to find bestselling author Steven Berlin Johnson’s next project. I sat down with bestselling author Steven Johnson to see if we could come up with a concept for his next project—using AI. The results were amazing. We loaded 200,000 words of NASA transcripts and all of Steven’s reading notes since 1999 into NotebookLM, Google’s personalized research assistant. We wanted to see if it could help us explore the Apollo 1 fire and find relevant and surprising ideas from history that could work to explain it. NotebookLM condensed disparate 200,000 words of NASA transcripts into readable formats like FAQs and chronological timelines. It sifted through the material to identify the catalyst for the fire. The model even went through Steven’s Readwise notes to find a relevant, and unexpected, story from history that we could use to explain the history and origins of the fire If you’re a fan of Steven Johnson’s work or you’re interested in AI as a creative tool, you need to watch this episode.  All of this happens as a live exploration of NotebookLM, and it’s a seriously wild ride. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every Follow him on X Links to resources mentioned in the episode: Follow Steven JohnsonNotebookLM Steven’s newsletter, Adjacent Possible Steven’s latest book about the rise of the modern detective: The Infernal Machine A few of Steven’s other books: How We Got to NowWhere Good Ideas Come FromThe Ghost MapEmergenceThe Invention of Air
Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves.  For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest
The NYT’s Kevin Roose has 18 new friends—none of whom are human. His new friends are AI personas that he made with Noma, Kindroid, and other AI companion apps. There’s fitness guru Jared, therapist Peter, trial lawyer Anna, and over a dozen more. Kevin talked to them every day for a month, sharing his feelings, asking for parenting advice, and even using them for “fit” checks. This isn’t the first time Kevin has had an…unusual interaction with an AI persona. A year ago, he was the target of Bing’s chatbot Sydney’s unhinged romantic affections. Kevin has gone deeper into the world of AI companions than anyone I know. He is a tech columnist at the New York Times, cohost of the Hard Fork podcast, and the author of three books. In this episode, I sat down with Kevin to learn more about his interactions with AI. We dive into: Why AI companions aren’t just for lonely people or shy teenagers Why AI personas are better friends than ChatGPT How AI companions can be used to safely explore different social contexts The risk of young people relying on AI for friendship The icks of AI dating and intimacy How to use AI to articulate what you value in your relationships This is a must-watch for anyone curious about how AI is changing the way we form relationships. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every Follow him on X Links to resources mentioned in the episode: Kevin Roose Hardfork, the podcast that Kevin cohosts Kevin’s latest book about being human in a world designed for machines Kevin’s piece in the New York Times about his experience making AI friends Two of the apps that Kevin used to create AI companions: Kindroid and Nomi Dan’s piece that explains why AI writing will feel real through psychologist D.W. Winnicott’s theory Every’s piece that explores AI companion app Replika
Nick Dobos, maker of the #1 programming GPT, on prompt-gramming with AI Nick Dobos showed me how to ship a website with two words and a single click.  He’s the creator of Grimoire, the #1 custom GPT for programming that has been used for over 1 million chats.  All he gave Grimoire was two words: “coffee website.” Just a minute later, Grimoire built the website and pushed it live to the internet. It was wild. Grimoire can do a lot more than create websites—it’s a coding assistant with 75+ built-in hotkey commands and sample projects, a guide to learning how to code from scratch, and a tool for programmers to find answers to their questions in real-time. Before he created Grimoire, Nick was an iOS developer at Twitter. When ChatGPT came out, Nick started experimenting with it—and ended up building Grimoire. Today, he’s at the leading edge of experimenting and building with AI.  I sat down with Nick to explore how people are using Grimoire and what it tells us about the age of programming by prompting. We dive into: How AI is massively lowering the barriers to code Why it’s important to solve the “blank canvas problem” that people experience while creating with AI How AI tools can streamline your creative process Why Grimoire has an edge over ordinary ChatGPT The best ways to use Grimoire to code smarter and faster This is a must-watch for coders, creative people, and anyone curious about how AI is changing the way we interact with computers. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction: 00:00:31 How Nick built Grimoire, the top-ranked GPT for programming: 00:05:20 Ship a website with two words and a single click: 00:10:25 How Grimoire is solving the “blank canvas problem” in AI creation: 00:14:57 The coding curriculum that can take you from zero to full programmer: 00:16:30 Why Grimoire has an edge over ordinary ChatGPT: 00:23:29 Nick’s thoughts on building the system prompt for a GPT: 00:34:10 The utility of AI as a new layer on top of existing apps: 00:40:04 How Nick uses a custom GPT to unpack his emotions: 00:43:11 How to use AI to break down tasks—from programming to daily to-do lists: 00:50:35 Links to resources mentioned in the episode: Nick Dobos: @NickADobos Grimoire: https://chat.openai.com/g/g-n7Rs0IK86-grimoire  Nick’s website for his experiments with AI: https://mindgoblinstudios.com/  AI-first code editor Cursor: https://cursor.sh/  Open Interpreter: https://www.openinterpreter.com/  Lisa Feldman Barrett’s book: How Emotions Are Made Demo Hume, the empathetic AI voice: https://demo.hume.ai/ 
This AI can read emotions better than you can. It was created by Alan Cowen, the cofounder and CEO of Hume, an AI research lab developing models that can read your face and your voice with uncanny accuracy. Before starting Hume, Alan helped set up Google’s research into affective computing and has a Ph.D. in computational psychology from Berkely. Hume’s ultimate goal is to build AI models that can optimize for human well-being, and in this episode I sat down with Alan to understand how that might be possible.  We get into: What an emotion actually is Why traditional psychological theories of emotion are inadequate How Hume is able to model human emotions How Hume's API enables developers to build empathetic voice interfaces Applications of the model in customer service, gaming, and therapy Why Hume is designed to optimize for human well-being instead of engagement The ethical concerns around creating an AI that can interpret human emotions The future of psychology as a science  This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Dan tells Hume’s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alan’s radical approach to studying human emotion: 00:13:46  Methods that Hume’s AI model uses to understand emotion: 00:16:46  How the model accounts for individual differences: 00:21:08 Dan’s pet theory on why it’s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22 Ethical concerns around developing AI that can interpret human emotion: 00:44:42 Links to resources mentioned in the episode: Alan Cowen: @AlanCowen Hume: @hume_AI; hume.ai If you want to demo Hume: demo.hume.ai The nonprofit associated with Hume: Hume Initiative Lisa Feldman Barrett’s book: How Emotions Are Made The TV series based on Paul Ekman’s theory of emotion: Lie to Me
Learn how to use philosophy to run your business more effectively. Reid Hoffman thinks a masters in philosophy will help you run your business better than an MBA. Reid is a founder, investor, podcaster, and author. But before he did any of these things, he studied philosophy—and it changed the way he thinks. Studying philosophy trains you to think deeply about truth, human nature, and the meaning of life. It helps you see the big picture and reason through complex problems—invaluable skills for founders grappling with existential questions about their business. I usually bring guests onto my podcast to discuss the actionable ways in which people have incorporated ChatGPT into their lives. But this episode is different.  I sat down with Reid to tackle a deeper question: How is AI changing what it means to be human?  It was honestly one of the most meaningful shows I’ve recorded yet. We dive into: How philosophy prepares you to be a better founder The importance of interdisciplinary thinking Essentialism v. nominalism in the context of AI How language models are evolving to be more “essentialist” The co-evolution of humans and technology Reid also shares actionable uses of ChatGPT for people who want to think more clearly, like: Input your argument and ask ChatGPT for alternative perspectives Generate custom explanations of complex ideas Leverage ChatGPT as an on-demand research assistant This episode is a must-watch for anyone curious about some of the bigger questions prompted by the rapid development of AI. Thanks again to our sponsor CommandBar, the first AI user assistance platform, for helping make this video possible. https://www.commandbar.com/copilot/ If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Links to resources mentioned in the episode: Reid Hoffman: @reidhoffman The podcasts that Reid hosts: Possible (possible.fm) and Masters of Scale (https://mastersofscale.com/) Reid’s book: Impromptu The book Reid recommends if you want to be more philosophically inclined: Gödel, Escher, Bach Reid’s article in the Atlantic: "Technology Makes Us More Human" The book about why psychology literature is wrong: The WEIRDest People in the World by Joseph Henrich The book about how culture is driving human evolution: The Secrets of Our Success by Joseph Henrich
Seth-Stephens Davidowitz wrote a book in 30 days—and he did it with ChatGPT. Seth is a data scientist, economist, and author who challenged himself to write a book—Who Makes the NBA?—in less than 1 month after realizing how fast he could work by using ChatGPT plugin Advanced Data Analysis. But along the way he discovered something else: Writing with AI wasn’t just faster, it was also way more fun. Seth outsourced the boring parts of data analysis—like cleaning data, merging files, and looking up code snippets—to AI. This left him to focus on what he loves: thinking up questions to ask the dataset. In a world where AI can answer any question humans know the answer to, asking the right questions is becoming increasingly important—a skill Seth isn’t just really good at, but also finds joy in. In this episode, Seth walks me through how he used AI to analyze data and write a book in 30 days. We get into: How to create and edit complex charts with AI in seconds Using ChatGPT to brainstorm creative ideas How AI is redefining who can be an artist Why ChatGPT is an excellent tool to get a quick ballpark estimate Developing a sixth sense about when ChatGPT is wrong The power of AI instantly answering hard questions that would normally take months of research We also use ChatGPT to analyze a dataset of Olympic athletes live on the show—in pursuit of finding out which sport I’m best suited for! This episode is a must-watch for anyone curious about data science and how AI is transforming the future of creativity (or who is just a fan of the NBA). If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every Follow him on X Links to resources mentioned in the episode: Seth Stephens-Davidowitz: https://twitter.com/SethS_D http://sethsd.com Seth’s books: Who Makes the NBA? , Everybody Lies and Don’t Trust Your Gut
Nicholas Thorne is building Squarespace for the AI age. It’s called Audos, and it’s an AI chatbot to help any entrepreneur go from idea to: - Pitch deck - Working website - Custom GPT - User interviews with real customers All in just a few minutes. And he did it using ChatGPTapp. It’s AI all the way down—and it’s one of the most impressive AI businesses I’ve ever seen. Nicholas is a general partner at Prehype, an incubator that launched Barkbox and Ro Health. It’s also where I started Every, so it was great to come full circle. Nicholas’s job at Prehype is to launch new companies. He’s taken everything he’s learned running an incubator and used it to help entrepreneurs start businesses at scale—with AI. As we talk, Nicholas walks me through the interactions of Audos’s chatbot with a user live on the show. Nicholas tells me that he used ChatGPT to prototype most of Audos’s features—despite being non-technical himself. He shares exactly how he did this by showing me how he’s using AI to create a new feature for the product. We get into: - Ways AI can make you a more effective founder - How to use ChatGPT to build your prototype - Strategies to refine problem statements with AI - Using GPTs to gather and synthesize customer feedback This episode is a must-watch for anyone who has ever toyed with the idea of starting a business—and wants to do it with AI.If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ⁠ultimate guide to prompting ChatGPT⁠. It’s usually only for paying subscribers, but you can get it here for free: https://every.ck.page/ultimate-guide-to-prompting-chatgpt To hear more from Dan Shipper: Subscribe to Every: ⁠https://every.to/subscribe⁠ Follow him on X: ⁠https://twitter.com/danshipper⁠ Timestamps: 00:00:00 - Teaser 00:00:48 - Introduction 00:12:10 - How AI can make you a more effective founder 00:17:03 - Live demo of Audos! 00:24:07 - Why Nicholas built an AI tool to enable entrepreneurs 00:25:35 - How Audos puts you in “edit mode” instead of “create mode” 00:28:12 - Tools to gather customer feedback, generated by Audos 00:32:58 - How Audos actually works 00:35:07 - Nicholas uses ChatGPT to prototype a new feature 00:42:37 - How to establish checks and balances while using ChatGPT 00:57:20 - AI as a force for pushing entrepreneurship to new heights Links to resources mentioned in the episode: Nicholas Thorne: ⁠@thorneny⁠; ⁠nicholas@prehype.com⁠ Audos: ⁠https://www.audos.com/⁠ Nicholas’s book, Me, My Customer, and AI, is slated to publish next month. Follow him on X for updates: https://mmcai.super.site/
Antidepressants changed my life. I have OCD and antidepressants did what nearly a decade of therapy, meditation, and supplements couldn’t: they allowed me to live my life without being in a 24/7 spiral. (Bonus: they actually made therapy and meditation far more helpful once they started to work.) I think antidepressants are seriously misunderstood. Yes, they blunt negative emotions. But they also operate on personality and sense of self: they can make you bolder, less sensitive to failure, and less risk-averse. In short: they are a technology that changes how we see ourselves and the world. That’s why I invited Dr. Peter D. Kramer on my show. Dr. Kramer is a psychiatrist and the author of eight books, including Listening to Prozac, which is an international bestseller. He has practiced psychiatry and taught psychotherapy at Brown University for nearly four decades. Listening To Prozac is one of my favorite books, and it documents Dr. Kramer’s experiences as a psychiatrist seeing how antidepressants like Prozac changed his patients’ sense of self and personality. Now, you might be wondering why have him on a show about ChatGPT? Well, technology can change who we are even if it comes as a software product rather than a pill. It’s undoubtedly true that as generations of humans learn to live with AI, it will change what it means to be human—and how we see ourselves and the world. I think that can be a good thing, but it could also be scary. I wanted to talk to Dr. Kramer about his book, and see if we could apply some of his insights in Prozac to ChatGPT. It was an incredible conversation, and I was honored to talk to him. Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  To learn more about the topics in this episode: Listening to Prozac by Peter D. Kramer ChatGPT and the Future of the Human Mind by Dan Shipper SSRIs by Scott Alexander Timestamps: Introduction: 00:50 How technology changes the way we see ourselves and the world: 08:24 Antidepressants and their impact on our personality and sense of self: 21:25 How the availability of a technological solution prompts us to see the problem everywhere: 26:35 Technology alters the categories we have divided the world into: 34:06 How I use ChatGPT in my writing process: 40:05 Experimenting with ChatGPT to get relationship advice: 45:41 Prompting ChatGPT to be more specific: 51:16 Clearly indicate the tone you want ChatGPT to take: 55:11 Dr. Peter D. Kramer’s final thoughts on ChatGPT as a therapist: 1:02:27 Links to resources mentioned in the episode: Dr. Peter D. Kramer: https://twitter.com/PeterDKramer  ChatGPT and the Future of the Human  Mind by Dan Shipper: https://every.to/chain-of-thought/chatgpt-and-the-future-of-the-human-mind  Listening to Prozac  by Dr. Kramer: https://www.amazon.com/Listening-Prozac-Landmark-Antidepressants-Remaking/dp/0140266712  Should You Leave? by Dr. Kramer: https://www.amazon.com/Should-You-Leave-Psychiatrist-Autonomy/dp/0140272798  Against Depression by Dr. Kramer: https://www.amazon.com/Against-Depression-Peter-D-Kramer/dp/0143036963  Ordinarily Well by Dr. Kramer: https://www.amazon.com/Ordinarily-Well-Antidepressants-Peter-Kramer/dp/0374536961  Pierre Menard, Author of the Quixote by Jorge Luis Borges: https://raley.english.ucsb.edu/wp-content/Engl10/Pierre-Menard.pdf  The Soul of A New Machine by Tracy Kidder: https://www.amazon.com/Soul-New-Machine-Tracy-Kidder/dp/0316491977  Making Hay by Verlyn Klinkenborg: https://www.amazon.com/Making-Hay-Verlyn-Klinkenborg/dp/0941130185  Oranges by John McPhee: https://www.amazon.com/Oranges-John-McPhee/dp/0374512973 
You can build and run a one-person internet business that earns half a million in annual revenue—with AI. Ben Tossell showed me exactly how in this episode. Ben is the founder of Ben’s Bites—one of the best daily AI newsletters out there, which I love reading every day—and an investor in a number of promising early-stage AI startups. Ben is also an experienced founder whose no-code platform Makerpad was acquired by Zapier. I think Ben is really good at starting profitable internet businesses that are sneakily big, but don’t require too many resources. Over the last couple of years, he’s assembled a war chest of AI tools including ChatGPT, Claude, Gemini, Lex, and Supernormal to help him do this. In this episode, we get into the weeds of how Ben has integrated AI into his workflow to find new business opportunities, run them well, and evaluate their performance. We get into: How to use ChatGPT as a business strategist Building your MVP with ChatGPT Turning interview transcripts into compelling articles Analyzing business data using AI tools How to generate persuasive landing page copy with ChatGPT Offload time-consuming tasks to AI This episode is a must-watch for anyone who is curious about using AI to bootstrap a profitable internet business. Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Ben Tossell: https://twitter.com/bentossell
I made the greatest trade of my life with Jesse Beyroutey in 2019. We bought Nvidia shares when they were trading at $33. They’re worth nearly $800 today. I sat down with Jesse to top that trade in 90 minutes using Gemini Pro 1.5’s incredible 1 million token context window—and make a $1,000 trade live on the show.  Jesse is a managing partner at IA Ventures, a $600 million venture fund with seed investments in companies like Wise and Digital Ocean. He’s also a very close friend and one of the smartest people I know.  We unpack our investment thesis for our Nvidia trade and leverage the power of Gemini Pro 1.5 and ChatGPT to orchestrate what we hope will be the best trade of our lives. We put our money where our mouth is and make a $1,000 trade while the cameras are still rolling. There’s a plot twist at the end of this episode—so stick around to see the epilogue Jesse and I recorded just days after we made our investment. We get into: How Jesse leverages LLMs to get nuanced answers to his questions Ways to find patterns in large swaths of data using Gemini Pro 1.5  Gemini Pro 1.5 and ChatGPT going head-to-head How Gemini Pro 1.5 can be used to understand the stock market Why it’s important to consistently refine your search queries What Jesse thinks are the new big opportunities enabled by LLMs This is not investment advice, but it’s a must-watch for anyone who wants to leverage the power of AI to make smarter financial decisions. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction: 01:29 How Dan made the greatest trade of his life: 03:50 Jesse’s strategy to use LLMs to get nuanced answers 05:27 Gearing up to orchestrate the best trade of our lives with Gemini Pro 1.5 09:20 How Jesse gets AI to make great decisions 17:52 Using Gemini Pro 1.5 to find patterns in data 22:38 How AI can provide deeper insights into the stock market 26:48 Leveraging Gemini Pro 1.5’s huge context window to analyze data 34:41  Gemini Pro 1.5 and ChatGPT go head-to-head 46:33  Choosing a stock with just 15 minutes left on the clock 1:10:11 What Jesse thinks are the biggest new opportunities enabled by LLMs 1:24:01 The epilogue Jesse and Dan recorded one week after making the trade 1:28:43 Links to resources mentioned in the episode: Follow Jesse Beyroutey Nathan Labenz’s podcast, The Cognitive Revolution
You can break into Hollywood with a movie you made alone in your room. Dave Clark can show you exactly how in < 60 minutes. He’s a film director with a body of work that includes both feature films and commercials for brands like Google. His latest achievement is a stunning sci-fi short that got Hollywood’s attention, one that Dave made exclusively using AI.  Dave and I make a movie live on this episode, iterating from rough ideas to a real motion picture in < 1 hour. It’s a noir short featuring Nicolas Cage using a haunted roulette ball to resurrect his dead movie career that you don’t want to miss. We dive deep into the world of AI tools for image and video generation, specifically exploring their implications on lowering the barriers to enter the traditional movie industry. This episode is also packed with Dave’s wisdom on how to use these tools to create mind-bending movies. We get into: How AI is enabling everyone with a laptop to be a filmmaker Actionable tips to 10x your use of creative AI tools like Midjourney, Runway, and Elevenlabs How to integrate ChatGPT into the process to craft compelling stories  Strategies to make your AI-generated clips stand out  How to leverage AI tools to refine your videos This episode is a must-watch for creative people interested in bringing their stories to life, movie buffs, and anyone curious about the future of creativity.  If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper Timestamps: Introduction 01:33 How AI is enabling everyone with a laptop to be a filmmaker 10:19 The new tool set for making AI films 14:30 How to make your AI-generated clips stand out 16:56 The first prompt in Dave’s custom text-to-image GPT for our movie 25:00 The big advantage text-to-image GPTs have over Midjourney 37:58 The best way to generate Midjourney prompts with a GPT 44:13 Animating the images for our movie in Runway 49:10 First look at our movie! 53:42 How Dave thinks about animating images without an obvious motion element 58:22 Why you need to be persistent while working with generative AI 59:46 Links to resources mentioned in the episode: Follow Dave Clark Borrowing Time, Dave’s viral sci-fi short Forbes article that mentions Borrowing Time Dan’s article on how AI is changing filmmaking Nathan Labenz’s podcast, The Cognitive Revolution
Are you a curious person with a lot of ideas and little time? Anne-Laure Le Cunff can show you how to do it all. Anne-Laure is the founder of one of my favorite internet communities for curious minds, Ness Labs, a prolific writer, and a neuroscience PhD candidate. She’s also writing a book, Liminal Minds, that’ll be out later this year. And she said that the reason she can run a business, write a book, and do a PhD all at the same time is ChatGPT. Anne-Laure is one of the busiest people I know, and in this episode we dive into how she uses ChatGPT to get everything done. We get into: How to use ChatGPT to be more efficient Tips to break down research papers into digestible insights How she leverages ChatGPT to revamp her YouTube thumbnails Tips on using ChatGPT to write prolific articles Doing deep research on the internet using ChatGPT How to use ChatGPT to generate advice tailored for your needs How to surface useful insights from your journal using ChatGPT This is a must-watch for curious, creative people who want to get more done. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every Follow him on X Timestamps: 00:00:00 - Teaser 00:01:10 - Introduction 00:02:11 - How to use ChatGPT to save time 00:05:17 - Tips to breakdown research papers with ChatGPT 00:09:38 - How to use ChatGPT to generate explanations tailored to you 00:19:51 - Leveraging ChatGPT to find hidden gems on the internet 00:33:47 - How to create awesome YouTube thumbnails with ChatGPT 00:51:13 - Incorporating ChatGPT into your writing process 00:56:52 - Rapid fire questions from X 01:13:01 - Surfacing useful insights from Anne-Laure’s meditation journal 01:29:04 - The case for journaling in the age of AI Links to resources mentioned in the episode: Anne-Laure Le Cunff Anne-Laure following ChatGPT’s recipe to make an obscure Algerian cheese Anne-Laure’s meditation journal Nathan Labenz’s podcast, The Cognitive Revolution
Steph Smith is the host of the a16z podcast and a prolific online creator.  Steph sees the internet through a high-definition lens that gives her a deep understanding of what people want.  She can isolate a clear signal from the noise, which she uses to build wonderfully creative, useful things.   In this episode, I dive deep with Steph on how she uses the internet and AI to unearth emerging trends and validate business ideas. I pitch Steph two potential companies on the show, and we use an arsenal of tools and strategies to vet them live.  We get into: How she leverages ChatPT to generate great ideas  Why ChatGPT is ideal for understanding complex concepts  How she uses ChatGPT to organize huge swaths of data Tips on using SEO tools to vet business ideas How to surface useful insights from Reddit  What to look for while reading customer reviews Ways to gather more data on a market just from Google  This is a must-watch for anyone who spends time online and wants to discover the next big idea hiding on the internet. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps: Introduction 01:12 Leveraging ChatGPT to generate great ideas 22:11 Why ChatGPT is ideal for understanding complex concepts 29:29 How to use ChatGPT to organize huge datasets 48:00 Shark tank! Dan pitches Steph business ideas 1:00:41 Steph’s first move while validating a business idea on the internet 1:07:51 What to look for in a customer review 1:11:09 Tips on secondary keyword searches 1:17:45 How to gather market data from a simple Google search 1:26:24 What type of trend charts depict a good market 1:31:55 Using SEO tools to find useful insights from Reddit: 1:34:11 How to gather data about competitors: 1:42:37 Lightning-round questions from X 1:55:51 Links to resources mentioned in the episode: Steph Smith: https://twitter.com/stephsmithio Internet Pipes: https://internetpipes.com/ Doing Content Right: https://doingcontentright.com/#features Steph's database of untranslatable words: https://eunoia.world/ Dan’s piece on the Allocation Economy: https://every.to/chain-of-thought/the-knowledge-economy-is-over-welcome-to-the-allocation-economy  Neal Agarwal: http://neal.fun Keywords Everywhere: https://keywordseverywhere.com/ Reddit tools: https://anvaka.github.io/sayit/?query=, https://gummysearch.com/ SEO tools for market analysis: https://www.similarweb.com/,  https://www.junglescout.com/, https://answerthepublic.com/ 
You can build a video game without writing a single line of code. Logan Kilpatrick and I use ChatGPT and GPT Builder to make our own video game in less than 60 minutes—live on this show.  Logan is OpenAI’s first dev relations and advocacy hire and is committed to empowering more people to build using AI. It’s only fitting that we explore the depths of our own creativity by making a video game with GPT Builder—we start with a rough idea and iterate all the way up to a functional video game in < 1 hour.  This episode is full of Logan’s actionable insights on leveraging GPT Builder and ChatGPT to build any custom GPT that you’d like.  We get into: How ChatGPT is enabling the next billion software developers How GPT Builder is expanding the horizon of people who can build things Why he thinks coding is the most high-leverage thing anyone can do in their life How to increase the chances your custom GPT will go viral Tips to use GPT Builder like a pro to create great custom GPTs How to use ChatGPT in conjunction with GPT Builder to get better performance This is a must-watch for anyone who wants to bring their creative ideas to life. If you found this episode interesting, please like, subscribe, comment, and share!  Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe  Follow him on X: https://twitter.com/danshipper  Timestamps 00:00:00 - Teaser 00:00:44 - Introduction 00:09:18 - Why learning to code is the highest-leverage thing you can do 00:13:40 - AI is empowering the next billion coders 00:35:58 - The first prompt in GPT Builder for our video game 00:39:27 - How to increase the chances your custom GPT will go viral 00:43:00 - Prompt engineering tips while using GPT Builder 00:56:13 - How to use ChatGPT in conjunction with GPT Builder 01:06:33 - Ready to play our text-based strategy game! 01:19:44 - How to finetune your custom GPT 01:43:12 - Why you should build custom GPTs Links to resources mentioned in the episode: Our video game, Allocator: https://chat.openai.com/g/g-oooxUbOkj-allocator
Dr. Gena Gorlin⁠ is a clinical psychologist at UT Austin whose goal is to raise the ceiling on human potential.  I sat down with her to discuss how @ChatGPTapp has become a key tool in her quest for radical self-betterment. In this episode, she feeds ChatGPT a list of her old journal entries, and it conducts the most thorough and insightful annual review and goal-setting session you’ve ever seen:  It writes a personal biography for her, unpacking themes and key questions from each year of her life It helps her plan her year for 2024, aligning her focus and helping set goals It allows her to see her own blindspots and avoid common failure modes It predicts what the year might have in store for her It helps her be more ambitious and reach higher for the things she wants Ultimately, it acts as both a mirror and mentor for her—one that’s always on, responds instantly, and can take on any personality or psychological modality that she needs. It’s a mind-bending example of how ChatGPT can unlock your potential. If you found this episode interesting, please like, subscribe, comment, and share!  Want more? Dan is running a course with Dr. Gorlin called Maximize Your Mind With ChatGPT. It’s a four-week cohort-based course marrying the cutting edge of AI with the best of what psychology knows about how to reach your potential.  Learn more: ⁠⁠https://maxyourmind.xyz⁠⁠ Want even more? Sign up for Dan’s newsletter Every to unlock our ⁠⁠ultimate guide to prompting ChatGPT⁠⁠. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to ⁠⁠Every⁠⁠ Follow him on ⁠⁠X⁠⁠ Timestamps: Introduction 00:18 An external hard drive for our brains 4:14 What is epistemic hygiene? 7:25 Upscaling with ChatGPT 12:25 Dan and Gena’s brainstorming session 20:34 Gena uses ChatGPT to analyze her years-in-review 31:43 Outsourcing to ChatGPT 46:51 Pushing beyond “work-life balance” 53:36 Will ChatGPT replace therapists? 1:09:22 Building a new version of you 1:20:00 Links to resources mentioned in the episode: ⁠⁠In Defense of Radical Self-Betterment⁠⁠ ⁠⁠How to Use ChatGPT for Psychological Growth⁠ ⁠⁠⁠Gena’s newsletter⁠⁠⁠
Tyler Cowen is an economist who has been thinking about the impact of technology on life, work, and the economy for the past decade.  He is a prolific writer behind the leading economic blog Marginal Revolution, a professor of economics at George Mason University, and the author of 17 books.  In this episode, I dive deep with him on how ChatGPT will change the economy, and how he uses it in his own life. We get into: How ChatGPT makes him smarter How he uses it for deep reading and research How it acts as a “universal translator” when he travels How he uses ChatGPT and Perplexity AI together How “charisma” and “a hyped-up executive function” may be the most economically rewarded skills over the next 10 years His thoughts on the allocation economy and the future of work with AI-assistance Whether a ChatGPT clone of Tyler’s personality would answer questions in the same way Tyler does himself This is a must-watch for anyone who wants insights on adapting to the future of work. If you found this episode interesting, please like, subscribe, comment, and share. And sign up for Every to get our ultimate guide to prompting ChatGPT. To hear more from Dan Shipper: Subscribe to Every Follow him on X Register for his course, Maximize Your Mind With ChatGPT Timestamps: Intro: 00:57 His predictions on AI’s immediate and long-term effects: 05:57 How AI can be leveraged to manage people: 11:31 Using ChatGPT as a universal translator during travel: 17:19 Why he worries less about hallucinations: 21:00 Using specific prompts to do deep research with ChatGPT: 22:00 Why he prefers using Playground: 25:54 ChatGPT goes head-to-head with Perplexity AI: 41:09 Using ChatGPT in university classrooms: 49:58 “Tyler” test: 57:59
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Adeola Elegbede

ChatGPT Nederlands currently has ChatGPT 4 and ChatGPT4-o. To use it for free you can go to: https://gptnederlands.com/

Jun 3rd
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