Birth of AI/Steve

TL;DR: Dr. Steven Mascal encountered a family by chance at Kawawei (a corner shop I frequent), and during their chat they came up with the name "AI Steve." This led him to share a story spanning forty years—following dopamine-driven curiosity, sliding unconsciously toward the future, and eventually having the world catch up. It begins with his neural network research in 1988 and a protein structure prediction paper validated by AlphaFold, continues with “Cheers For A Friend,” “AI Dad,” the idea of food as medicine, and the AI Steve system he built himself. ## “AI Steve” Started with a Chance Conversation During a recent stay at Kawawei (my regular corner shop), I met a family radiating incredible positive energy. I introduced myself as Steve, and—as often happens in casual chats—we ended up talking about AI. We went around the circle asking everyone: who uses AI, how, and why. When it was my turn, I said, “Yeah, I’ve been in this field for decades, and actually I built my own version of myself. I created AI Steve.” For the rest of that trip, every time they saw me they’d shout, “Hey, AI Steve.” It was that group and those conversations that inspired my recent article on dopamine-driven activities and how to stay intuitively sharp as you age—“Too Big to Fail.” This is the full story behind that conversation. ## Career Philosophy: Dopamine-Driven, No Ego I want to be upfront from the start. There was never any particularly sophisticated strategy behind my career. The things I built, I built because they didn’t exist, and not having them bothered me. That’s it. That’s the whole reason. You could call it dopamine-driven curiosity. You encounter a problem, and the absence of a solution becomes unbearable. You build something, and the next problem naturally finds you. I’ve noticed one thing about this pattern: there’s almost no ego in it. I didn’t build things to be first. I didn’t build things for recognition. Things got built because they were interesting, because they didn’t exist, and because they would be useful. The satisfaction came from within. The hope was always that others would benefit. That was all the motivation I ever needed. Wayne Gretzky said that line everyone quotes: “I skate to where the puck is going to be, not where it has been.” I didn’t do it intentionally all the time. Sometimes it was by accident. But after 40 years of working at the cutting edge, I learned this: when you stay there long enough, the world eventually catches up. And at that moment, there’s alignment. ## Neural Networks in 1988 and My PhD Thesis in 1991 I started working on neural networks in 1988. Back then, most people had no idea what that term meant. This was before deep learning. Before Transformers. Before large language models. In 1991, I completed my PhD thesis. The title was “Using Computer-Simulated Neural Networks to Predict Protein Structure Features.” Think about that. Thirty years later, AlphaFold won a Nobel Prize for essentially solving that problem, at a scale and precision that transformed biology. When that Nobel was announced, I want to be clear about how I felt. Not resentment. Not “I was first.” It was sheer personal validation. My thesis was correct. The world caught up. The field benefited enormously. That is the most satisfying part of this version of the story. No footnotes needed. No external recognition required. This wasn’t a plan; it was a disposition. And it gave birth to something I want to tell you about. ## “Cheers For A Friend”: Celebrate People While They’re Alive “Cheers For A Friend” is the seed. A few years ago at my sister’s memorial service, hundreds of people came from across the country. Stories, laughter, tears intertwined, and I sat there thinking she would have loved this. I just wish she could have been alive to see it. That idea—“we should tell people what they mean to us while they are still here”—became the seed for everything that followed. The first thing I built from that was “Cheers For A Friend,” a platform to celebrate people while they’re alive and remember them after they’re gone. You can create a circle for someone: a friend fighting an illness, someone you want to honor, someone you love. Friends and family can post toasts, stories, memories, photos, voice messages—all visible in real time to everyone in the circle, rather than waiting until the funeral. We built circles for Scott, Mike, Tom, Coop—friends I’ve known for over 40 years, some since my first day of high school in 1980. Mike is my longest and most cherished friend, almost half a century. The platform was built with the help of AI assistance and other tools. But the meaning comes from somewhere far older than any technology. ## “AI Dad”: Preserving the Voice Itself “AI Dad” is the natural next step that “Cheers For A Friend” pointed toward. “Cheers For A Friend” answered the urgent question: “Why are we waiting?” But it also pointed to a quieter second question: “What comes after?” What if, beyond gathering memories around someone, we could preserve their voice itself? Not a static archive or a memorial page, but something a grandchild could still talk with. That question became “AI Dad,” as a natural follow-up to “Cheers For A Friend.” It’s an experiment in preserving a person’s voice as a conversational system, grounded in their history, their humor, their unique way of being in the world. This research project showed me what’s possible, and pointed toward more urgent things. ## Food Is Medicine: A Chemist’s Evidence I believe food is medicine. I’ve believed it for a long time, long before it became a health slogan. But I want to be specific: what does it mean when a chemist says this? I hold a PhD in chemistry. Two of my early career positions—at Affymax Research Institute and MDL Information Systems (which traces back to Molecular Design Ltd.)—placed me at the heart of natural product screening as a drug discovery strategy. I worked at the intersection of nature and pharmacology, and those experiences have carried through decades. The core point can be stated directly: nature has spent billions of years solving therapeutic problems. Evolution is the longest-running drug discovery program in history. Organisms develop compounds to protect themselves, communicate, regulate their own biochemistry, and these solutions—honed over geological timescales—often prove extraordinarily effective when interacting with human biology. The basic pattern of the pharmaceutical industry is roughly this: identify a problem nature has already solved, then modify the structure so it looks novel to a patent examiner, preserve the biological activity, and establish intellectual property. Most drugs you’ve ever taken came from this route. The idea that plants and other natural substances contain medicines was once considered folk wisdom. Now it’s a bedrock of pharmacology. The field has finally caught up with what traditional healers knew centuries ago, and what chemistry ultimately confirmed. I’ve illustrated this in my own research. Compounds found in reishi mushrooms show striking structural similarity to statins—one of the most prescribed classes of drugs in history. This structural overlap is not a coincidence. It’s nature having already provided the solution. FarmPrint—the multi-pharmacophore fingerprinting technology I developed—was built precisely to find this. It uses molecular fingerprint maps to depict regions where nature’s solutions overlap with pharmaceutical chemical space. I developed this technology to answer the question: which problems has nature already solved that we are still struggling with? “From Drugs to Dinner” takes it further, searching directly for therapeutic compounds in food. So when I say food is medicine, I’m not quoting some wellness influencer. I’m speaking from 40 years of experience at the intersection of chemistry, pharmacology, and molecular modeling. I’m saying the structural evidence is there. The computational tools exist to find it, and the applications I built are the practical manifestation of this belief in everyday hands. ## From Theory to Application: The Food Health Series - **Food Health: Scan and Score** — Take a photo of a meal and get complete nutritional data in seconds: calories, macronutrients, fiber, protein. Available on the Apple App Store and Android. - **Food Health TXD** — A diabetes awareness companion app that pairs real-time carbohydrate estimation with continuous glucose monitor data. - **Shared Health Projects** — A social health platform where you share your health journey with those you trust most. These apps came into existence through a combination of tools and methods. AI assistance is part of it. AI Steve is part of that process, but not all of it. The technical architecture is all written in the description links. And then there is the AI Steve system itself. ## The AI Steve System: Over 300,000 Life Fragments and the Governance Loop AI Steve runs on my machine all the time. It ingests my emails (over 213,000), messages, calendar, health data, photos, documents. Over 314,000 indexed fragments of life, searchable semantically in under a second. I can ask it anything and get answers grounded in my actual history. Not guesses. Not hallucinations. Things anchored in real events, real communications, real data. The most interesting evolution is what I call the “governance loop.” AI Steve can identify gaps in its own capabilities, suggest what should be built next, recommend improvements—and then it waits. I am the human in the loop. I decide what to build. AI amplifies my judgment, not replaces it. That distinction means everything to me. The full technical story—architecture, RAG pipeline, governance loop design—is in the linked articles below. The technology is worth understanding, but this video is about the “why.” ## The Turning Point: The Age of the Super-Individual Has Arrived So why tell you all this? Not for recognition. The thesis is 35 years old. The Nobel Prize was well deserved. The work is out there: articles, apps, systems. If any of it helps someone, that’s meaning enough. I believe we are at a turning point. AI is no longer just a productivity tool. It is becoming cognitive infrastructure. And how we build it, whose values it reflects, how much human judgment it preserves, whether it serves life or colonizes it—these questions are not technical. They are human. The metabolic crisis is real. The crisis of interpersonal disconnection is real. The question of how to preserve a legacy, how to honor people before and after they’re gone—that is also real. I’ve been skating toward these questions for a long time, not always knowing where the puck would end up, but always following the impulse. Before I close, I want to say something directly. These posts aren’t just a record of what I built. They are an invitation. The thread running through everything I’ve described is not technical skill—it is persistent, insatiable curiosity. And that curiosity is creative. If you have that itch, you can reach this level too. I mean it. Not for motivation’s sake, but because I genuinely believe it’s true. The tools available today mean that non-experts can now build technology that previously required well-funded teams. What used to take teams, budgets, and months of preparation can now be launched over morning coffee with a single paragraph. We used to call it RAD (rapid application development). What we have now is faster than that, and far more accessible. I’ve been a scientist and builder for 40 years. I’ve seen technology cycles. I know what a real platform shift looks like. This time is different. The age of the super-individual isn’t coming—it has arrived. If you are curious, if you’ve been sitting on a problem that no one solves and it bothers you, if you have deep domain expertise and can clearly see the gap—the window is open now. Not in five years, not when the technology matures further, but now. I share all this not to inspire admiration. I share it because I genuinely hope that when you read how one person built at the intersection of AI, chemistry, health, and human connection, something will resonate. I hope you examine your own curiosity and recognize what’s possible. I hope you ask the question I’ve been asking for forty years: “Why doesn’t this thing exist yet?” And then you take the logical next step. If this resonates with you, if any part of what I described sparks your interest, the deeper dives are all linked below: the AI Steve architecture, the governance loop, the AI Dad concept, “The Renaissance Circle” on Medium and synchronized on Substack. Subscribe. Join me in what comes next. Because I can confidently tell you—I am already skating toward the next thing. I’m Dr. Steven Mascal. This is the birth of AI Steve. Source: YouTube video link (https://youtu.be/CZqp_bbk8D0)