This weekend, a small team in Latvia won an Oscar for a film they made using free software. That’s not just cool — it’s a sign of what’s coming. Sunday night was family movie night in my home. We picked a recent movie, FLOW. I’d heard good things about it and thought we’d enjoy it. What we didn’t know was that as we watched, the film won this year’s Academy Award as best animated feature. Afterwards, I saw this post from the movie’s director, Gints Zilbalodis: We established Dream Well Studio in Latvia for Flow. This room is the whole studio. Usually about 4-5 people were working at the same time including me. I was quite anxious about being in charge of a team, never having worked in any other studios before, but it worked out. pic.twitter.com/g39D6YxVWa — Gints Zilbalodis (@gintszilbalodis) January 26, 2025 Let that sink in: 4-5 people in a small room in Latvia led by a relatively inexperienced director used free software to make a movie that as of February 2025 had earned $20m and won an Oscar. I know it’s a bit more involved than that, but still – quite an accomplishment! But not unique. Billie Eilish and her brother Phineas produced her Grammy-winning debut album When We All Fall Asleep, Where Do We Go? in their home studio. And it’s not just cultural works such as movies and albums: small teams have built hugely successful products such as WhatsApp and Instagram. As computers and software get cheaper and more powerful, people can do more with less. And “more” here doesn’t mean just a bit better (pardon the pun) – it means among the world’s best. And as services and products continue migrating from the world of atoms to the world of bits, creators’ scope of action grows. This trend isn’t new. But with AI in the mix, things are about to go into overdrive. Zilbalodis and his collaborators could produce their film because someone else built Blender; they worked within its capabilities and constraints. But what if their vision exceeded what the software can do? Just a few years ago, the question likely wouldn’t even come up. Developing software calls for different abilities. Until recently, a small team had to choose: either make the movie or build the tools. AI changes that, since it enables small teams to “hire” virtual software developers. Of course, this principle extends beyond movies: anything that can be represented symbolically is in scope. And it’s not just creative abilities, such as writing, playing music, or drawing, but also more other business functions such as scheduling, legal consultations, financial transactions, etc. We’re not there yet. But if trends hold, we’ll soon see agent-driven systems do for other kinds of businesses what Blender did for Dream Well Studio. Have you dreamed of making a niche digital product to scratch an itch? That’s possible now. Soon, you’ll be able to build a business around it quickly, easily, and without needing lots of other humans in the mix. Many people have lost their jobs over the last three years. Those jobs likely won’t be replaced with AIs soon. But job markets aren’t on track to stability. If anything, they’re getting weirder. While it’s early days, AI promises some degree of resiliency. For people with entrepreneurial drive, it’s an exciting time: we can take ideas from vision to execution faster, cheaper, and at greater scale than ever. For others, it’ll be unsettling – or outright scary. We’re about to see a major shift in who can create, innovate, and compete in the market. The next big thing might not come from a giant company, but from a small team – or even an individual – using AI-powered tools. I expect an entrepreneurial surge driven by necessity and opportunity. How will you adapt?

For week 9 of the humanities crash course, I revisited the most important text in Western culture: the Bible. Of course, I didn’t read the whole book – only a small subset. Still, it was a lot. As I’ve done in previous weeks, I followed Gioia’s suggestions for the texts. Readings Gioia’s plan aims for around 250 pages per week. This week’s readings exceeded that. I tackled seven books: Genesis, Ecclesiastes, the four Gospels, and Romans. I said ‘revisited’ because in 2009, I read the whole Bible. But it’s been fifteen years, and these texts are important enough that they merited a second reading. (In the case of Genesis, a third.) I used the English Standard Version. Yes, King James is more influential, but it’s also harder to grok – and I’m reading for understanding. I considered reading in Spanish this time, since my earlier reading was in English, but I couldn’t find a decent freely downloadable ePub. (What’s up with that?) That was the plan, anyway. I soon realized that reading these books would require more time than I’ve allotted to the project. So I devised an alternative: listening to the work as an audiobook. I already did this for the Odyssey, which I justified because that work was originally oral. No such justification for the Bible. Oh well. Audible has several versions of the ESV Bible read by different narrators. I picked the one read by Robert Smith, who has a wonderfully warm voice. Smith’s narration accompanied me during two long drives and several morning walks. What can one say about the Bible? I kept thinking of something Bill Moyer said about Joseph Campbell when introducing one of their interviews: Campbell told the story of the young Hindu who called on him in New York and said, “When I visit a foreign country, I like to acquaint myself with its religion. So I bought myself a Bible and for some months now have been reading it from the beginning. But, you know, I can’t find any religion in it.” Genesis, in particular, reads more like tribal mythology than a work of spiritual guidance, such as the Dhammapada. Of course, for those of us raised in a Western culture, the stories in this book are very familiar: the creation of the world, expulsion from the Garden, Cain and Abel, the Tower of Babel, Noah and the Ark, Joseph and his brothers, etc. Ecclesiastes feels closer to what Cambpell’s friend might have been looking for. Rather than chronological narratives, it offers advice for living – some of it surprising. The main gist: much in life is vanity; death is inevitable; you should fear God and enjoy life even amidst uncertainty. The Gospels narrate Jesus’s life, each with a slightly different emphasis. Mark is the earliest and shortest. It, along with Matthew and Luke, focuses on the life of Jesus. John is more theological, exploring Jesus’s message and meaning. The Epistle to the Romans, written by Saint Paul, is part of the theological framework developed by the early Christian community. It connects Jesus’s life and teachings with the earlier Jewish scriptures, but contextualizing it and making it relevant to a broader audience. Audiovisual Gioia recommended music and art inspired by these readings. I was already familiar with Handel’s Messiah, Thomas Tallis’s work, and The Byrd’s Turn! Turn! Turn!, a Pete Seeger tune that sets part of the third chapter of Ecclesiastes to music. I saw Michelangelo’s Sistine Chapel ceiling and sculptures in person when I lived in Rome in the early 1990s, so I opted to not dive in this week. But obviously, this week’s texts served as inspiration for the most important works of art and architecture in the Western world. For this week’s movie, I opted for Martin Scorcese’s THE LAST TEMPTATION OF CHRIST. I’d seen it shortly after it came out. I was familiar with the Gospel stories then, but hadn’t read the original sources. I revisited it now, primarily for its textures. The movie features powerful imagery. The scenes of crucifixions effectively convey the horror, suffering, and shame entailed by this brutal method of execution. Willem Dafoe is magnificent as a conflicted and uncertain Jesus. Peter Gabriel’s soundtrack and its companion Sources album have long been among my favorites; the music is even more powerful in context. Reflections I can see why THE LAST TEMPTATION was (and still is, in some countries) controversial. Although it features a prominent disclaimer, the movie diverges significantly from the Gospels. It also shows Jesus having sex. But the movie also addresses serious spiritual questions. What does it mean for somebody to be both human and divine? Did Jesus act freely? Was he predetermined to suffer? What is the role of suffering in salvation? I was surprised to realize that two of the stars of previous movies in the crash course also have important roles in this movie: Andre Gregory (of MY DINNER WITH ANDRE) plays John the Baptist and Harry Dean Stanton (of PARIS, TEXAS) plays Saul/Paul. Both characters bookend Jesus’s arc. Back to the texts: of this week’s readings, I was most pleased to revisit Ecclesiastes. I was struck by its parallels with the Buddhist scriptures. Both caution against becoming attached to transitory things – and in this sensuous world, all is transitory. Understanding that suffering comes with life is the first step in overcoming suffering. All else is vanity. Notes on Note-taking This week, I implemented a new note-taking habit: early each morning, after my daily journaling, I wrote down a few notes on the text I finished the day before. I’m still using Obsidian with the Text Generator plugin. The Judeo-Christian scriptures are part of the LLM’s training corpus, as is much of the commentary around them. I took advantage of this fact by asking GPT-4o for summaries in each text’s Obsidian note. This week, I also started a new section in these notes. In addition to my reflections and GPT summaries, I’ve started reflecting on the influence and criticisms of each work. For the influence, I used variations of the following prompt: Why is the Gospel of Matthew considered important? Focus on its overall influence but also relative to the other three Gospels: For criticisms, I used variations of this prompt: What are the main criticisms levied against the Gospel of Matthew? GPT’s answers to these prompts were invariably insightful. It was especially helpful for understanding the differences and similarities between the four Gospels. I started a separate note in to examine the Gospels at this higher level, linking them together. An obvious next step is creating more granular notes to capture individual ideas from the scriptures and linking those too. I’ll eventually get to that; this won’t be my last explorations of these scriptures. But now, we must move on to other works. Up Next We’re heading back to Ancient Greece: Sophocles’s Oedipus trilogy plus plays by Aeschylus, Euripides, and Aristophanes. Standard Ebooks has beautiful versions of Sophocles’s works, but I’m also listening to audiobooks. These plays come to life when dramatized, and Audible has excellent versions as part of their subscription package. Check out Gioia’s post for the full syllabus. Again, there’s a YouTube playlist for all the videos I’m sharing here. And as a reminder, I’m also sharing these posts via Substack if you’d like to subscribe and comment.

A Thousand Brains: A New Theory of Intelligence By Jeff Hawkins Basic Books, 2021 If you’re interested in artificial intelligence (and you should be,) it behooves you to learn about intelligence in general. While there’s still lots to learn, neuroscience has made lots of progress in the last few decades. This book offers a compelling new theory of how we think. Hawkins is a tech entrepreneur (i.e., he founded Palm Computing.) But his passion is neuroscience. He’s on a quest to understand how intelligence works, and this book explains what he and his team have found. It’s divided into three parts, with the first focused on their “Thousand Brains” theory. It starts by explaining what we know about the brain’s architecture. The brain is a complex organ composed of subsystems. Its older parts are responsible for baseline features such as breathing and walking. The neocortex is a newer part that is responsible for more complex tasks, such as reading and talking. Hawkins recaps two general tenets underlying all of this: Thoughts, ideas, and perceptions are the activity of neurons Everything we know is stored in the connections between neurons Physically, the neocortex is composed of around 150,000 cortical columns, modular units responsible for somewhat independent tasks in the brain. For a long time, people didn’t fully grok the role of these columns in thinking and perceiving. Hawkins and his team made three discoveries: The neocortex learns a predictive model of the world Predictions occur inside neurons The secret of the cortical column is reference frames Specifically, each column learns models of objects and concepts based on sensory inputs. The brain learns models by observing change in inputs over time. For example, moving around a space lets you perceive its boundaries from different perspectives. As you do, you create a sort of mental map of the space. The brain uses these models to make predictions about the world. Each cortical column develops models independently of other columns. It’s a decentralized model of understanding that contrasts with the more traditional hierarchical model. Reference frames are like maps that set objects in context so the brain can understand how things relate to each other. When you grab a cup, your brain uses reference frames for both the cup and your hand. Your senses provide input on where either is in relation to the other. Reference frames let you track both the cup’s and hand’s locations and features as they (and you) move in space. Each cortical column builds a spatial and conceptual reference frame for things you encounter in the world. The brain integrates these disparate models into a cohesive understanding of objects, environments, and abstract concepts – including information coming in through the senses. Having learned the attributes and expected capabilities of things (e.g., hands and cups) over time, your brain can predict what will happen when you act on them (or with them) in various ways. Which is to say, reference frames are essential to learning, understanding, and acting. They’re how the brain models the world so you can act skillfully. Part two of the book explores the theory’s implications for building artificially intelligent systems. A key takeaway: current approaches AI won’t get us to “true” intelligence (my term, not Hawkins’s) since they lack embodied reference frames. Hawkins believes that artificial systems that aim to function like our brains would need to provide analogs to this distributed structure, even if their sensory and actuating mechanisms were wildly different from ours. AIs can’t achieve human-level general intelligent absent reference frame-based models. Part three explores the theory’s social implications. Hawkins is concerned with the preserving intelligence in a world that is 1) on track to develop artificial intelligent systems while 2) destroying the environment. Intelligence is a fragile phenomenon that could disappear, so Hawkins argues for “estate planning for humanity” – i.e., finding resilient ways to perpetuate intelligence and its accomplishments. As you may surmise from these notes, the book gets progressively more speculative as it goes. Part one, which is grounded on solid evidence, is the most informative. By part three, the book has shifted to speculative/philosophical advocacy. The “Thousand Brains” theory has important implications for both AI and design. For one thing, it grounds the concept of mental models on neuroscience. We do indeed carry around “maps” in our brains that help us act and decide in the world – something that designers have known empirically all along. For another, these models emerge from our experiences as embodied beings. Our models of hands and coffee cups are only relevant to beings that share our physical, sensory, and neural characteristics. An ant would have a very different model of a cup, for example. This second point raises questions about the ability of current AIs to supplant humans in many (most?) activities. LLMs in particular work by detecting patterns in language that may create something like models, but they’re unlike the models in embodied beings with reference frame-driven architectures. Which is to say, the “Thousand Brains” theory suggests current AI architectures might not lead to what most of us imagine as AGI. That doesn’t mean they’re useless, but they’re definitely different. We have lots to learn about how to work effectively with these things. The theory is still relatively new and not yet widely accepted. But it represents an intriguing shift in how we think about how we think. The idea that intelligence emerges from independent yet cooperative modular units has intriguing implications for AI and beyond. As a non-specialist, I found the book compelling and insightful. At a minimum, it offers fascinating thoughts about the preciousness and fragility of attention and intelligence in a world bent on commoditizing both. A Thousand Brains: A New Theory of Intelligence

In episode 4 of the Traction Heroes podcast, Harry and I discussed mental models. It’s a tricky phrase: we brought up two different, yet common, uses: Mental models as individuals’ internal understandings of a particular things and situations – i.e., the “Indi Young” sense. Mental models as universally-applicable mental shortcuts or tools for thinking about situations – i.e., the “Shane Parrish/Charlie Munger” sense. Knowing how your mind understands things will help you act more skillfully. But models are often based on incomplete information or in tension with other latent ideas. We landed on a practical note, with Harry explaining a framework for making these points of tension visible. We’re still trying to get our bearings with this new show. I’d love to know how these conversations are landing for you. If you have feedback, please get in touch and tweak my own models.