Category: Science

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AI and the Universe

How are you feeling about AI lately? Excited? Anxious? A bit bewildered? If you’re like most of us, you’re probably riding a rollercoaster of emotions. That’s completely normal. After all, we’re witnessing the birth of a technology wave that’s set to rival the discovery of the steam engine or the rise of the internet. As a technologist, I find myself marveling at the possibilities. But I also understand the concerns, questions and especially change at this scale. It can feel unsettling.

Today, I want to explore what this is all about, why it matters, and what practical steps we can take.

What is AI, really? Artificial intelligence isn’t just about building clever machines or automating tasks. At its heart, I believe AI is humanity’s bold quest to extend our minds. It is the ultimate tool for understanding ourselves, our world, and the universe beyond. Imagine a technology that doesn’t simply crunch numbers but helps us solve mysteries that have stumped us for generations. The grand purpose of AI is to accelerate discovery, deepen insight, and help every one of us flourish through knowledge.

Will that happen? Is this happening? Absolutely! We’re already seeing AI move from science fiction to real science. It is impacting everything from disease diagnosis to energy production, from weather prediction to artistic expression. Here are some examples that I recently came across that inspired me. Warning here, this is very nerdy content, so feel free to skip to the end if you are so inclined.

  • Solving Biology’s Biggest Puzzle: For decades, predicting a protein’s structure from its amino acid sequence was one of biology’s toughest challenges. This is essentially a problem of physics and chemistry, predicting a stable 3D structure from a 1D amino acid sequence. This painstaking experimental work could take a PhD student their entire doctorate to solve for a single protein. AlphaFold’s AI cracked this puzzle in seconds, transforming structural biology, accelerating advanced drug development, and bringing deeper insight into disease. Its latest version, AlphaFold 3, extends this impact by modeling complex interactions between proteins, RNA, and DNA. This breakthrough suggests a paradigm shift.  While physics can be described by elegant mathematics, biology’s immense complexity may be best understood through AI. It may even unlock the mystery to truly decode life.
  • Taming the Hottest Matter in the Universe: Deep Reinforcement Learning (RL) has been applied to control high-temperature plasmas that are hotter than the sun, within tokamak fusion reactors. Plasma is highly unstable, requiring a controller to predict its behavior and adjust massive superconducting magnetic fields within milliseconds. The AI system created a controller able to contain and hold the plasma in specific shapes for record amounts of time, successfully addressing a bottleneck in fusion research.  By learning to balance magnetic fields in real time, AI edges us closer to abundant, clean energy.
  • Modeling Intuitive Physics and Dynamics: Video generation models like Google’s Veo demonstrate an ability to reverse-engineer physics from passive observation (e.g., watching YouTube videos). They accurately model complex dynamics such as liquids, specular lighting, and materials flow. This capability suggests these models are learning an underlying structure, or a “lower dimensional manifold” of the very nature of all creation and our reality. That’s mind-blowing! It is fundamental to building generalized understanding and may even unlock the mysteries of our universe.
  • Advancing Quantum Chemistry and Materials: AI is learning to approximate solutions to Schrödinger’s equation, enabling us to simulate the quantum behavior of electrons with remarkable efficiency. This breakthrough is vital for materials science, as it makes it possible to model the properties of large, complex materials that were previously too costly or computationally intensive to study with traditional methods.
  • Accelerating Algorithmic Innovation: Systems like AlphaEvolve, which blend large language models (LLMs) with evolutionary computing, are already evolving and improving algorithms, finding, for example, faster solutions to complex problems like matrix multiplication. This marks a leap toward intelligent systems that can generate and optimize their own tools. They are evolving themselves. It’s amazing to witness. Yes, I know, also terrifying!

The ultimate aim of creating powerful AI is to build tools that help us. It allows us to better understand the universe and accelerate science to the maximum. If successful, I believe this technology will usher in an era of radical abundance and lead to the profound transformation of the human condition.

Picture a world where disease can be cured mostly in computers, where clean energy is limitless, and where anyone can explore vast new knowledge with the help of an intelligent partner. AI is guiding us towards a time where scarcity, of knowledge, health, and opportunity, can be truly challenged. It’s not about replacing people. It’s about augmenting our potential, surfacing new connections, and igniting a new golden age of discovery. The mission is not to hand over control, but to embrace this power for all humankind. 

As AI continues to reshape our world, I believe we have a responsibility to meet this moment with adaptability, humility, and genuine curiosity. We should be experimenting with new tools, asking bold questions, and venturing beyond familiar boundaries. The most exciting breakthroughs emerge where creativity, technology, and storytelling intersect, so let’s embrace collaboration across disciplines and learn from one another. Above all, let’s serve as ethical stewards, ensuring these innovations benefit everyone, not just ourselves. And as we explore, let’s stay connected to our passions and strengths, blending them with new opportunities to grow, make a difference, and shape a future we can all be proud of.

AI is here, the revolution is real, and the mission is bigger than any one team or company. Let’s approach this with wonder, humility, and courage. Let’s steward this technology toward outcomes that inspire hope and serve the flourishing of all people.

 What will you learn next? What new ideas can you bring? What story do you want to help tell? The future may be unpredictable, but together, we can make it magical.

Let’s build, learn, and dream!

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Be the Miracle

Dec. 21, 1968, NASA’s Apollo 8

Jim had seen it all before. As he stared out the portal of the spacecraft at the moon, he remembered the last time he was here. It was Christmas Eve, and he and his crew were in lunar orbit, broadcasting a holiday greeting back to the inhabitants of planet Earth. He remembered looking out at the moon’s surface and seeing the long shadows that the sunrise was casting across its features. It felt as if he could reach out and touch it. He was ready to tread where no one had gone before.

Jim Lovell passed away last week at the age of 97. He was a true pioneer—first to orbit the moon with his crew, and famously the commander of Apollo 13. He dreamed of walking on the moon, and the Apollo 13 mission was meant to make that possible. But as we all know, things didn’t go according to plan. Instead, the mission became a story of crisis: a mid-flight disaster that threatened the lives of the crew. Jim’s quick thinking, together with his crew’s steadfast work, turned near-certain tragedy into an extraordinary story of survival and teamwork. The world watched with bated breath, and there was collective relief and joy when the crew returned safely to Earth.

Jim never set foot on the moon. But he became an inspiration for how to tackle the unexpected. “You can’t suddenly have a problem, and then just, you know, close your eyes and then hope there’s a miracle coming on, because a miracle is something you have to do yourself, or have people to help you.”

It’s easy to see our “moon shot” as our only objective, the sole definition of success. But life has a way of surprising us and changing our plans. When things don’t go as expected, those moments become the true test of our character. They can be the very moments that define us—not by whether we reached the goal we set, but by how we faced the unexpected. It isn’t just about accomplishing the mission, however important that may be, but about how we react and support each other along the way.

As we take on new challenges this week, let’s remember Jim’s example: don’t lose heart when the mission changes. Instead, do something—make a difference. Help someone else. Be the miracle. The measure of success isn’t the destination, but how we respond when the path shifts beneath our feet. Even when you are 234 thousand miles from home.

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Beyond the Horizon

The sun blazed down on us, and the road seemed to stretch on forever. Last week we took a road trip to Tulsa to meet with family and celebrate my mom’s 80th birthday.  As we drove across the Mojave, the road seemed to stretch out as far as the eye could see. Bounded on both sides of the road were rolling piles of sand and rock. Just ahead, it looked as though someone had taken a putty knife and smoothed out a pallet of sand up toward the undulating hills just on the horizon. 

The hot desert road ahead looked like a gray ribbon placed on the tan, sage speckled landscape. It disappeared into a sharp point on the horizon and seemed to pierce the sky. The heavens were pouring out all over the road. The cool, watery blue sky had drained down into the otherwise hot and dry roadway, well beyond the horizon. It felt like if I kept driving, I would fall into the sky. It was uncanny! I had an incredible sense of power at that moment. I felt like we could rocket our way into the silvery blue pool of the celestial realm. I couldn’t help but wonder, how was this possible?

It turns out that an illusion like what I saw can occur when a hot surface like the road superheats the air just above it. The air becomes much hotter than the air just a few feet higher. This creates a steep temperature gradient — hot air below, cooler air above. Light travels faster in warmer, less dense air than in cooler air. As light rays from the sky travel downward and enter the hotter air near the road, they bend upward toward your eyes. This refraction is interpreted by our eyes as reflection, so I see the sky somehow pouring onto the road. Well, too bad. I was really hoping we could drive into that crystal blue oasis.

Instead of treading tracks on the celestial firmament, we eventually curved over the horizon and into “Holy Moses Wash”. If you have ever taken a trip across the country on Interstate 40, you will remember this surreal spot. It is located just south‑west of Kingman, Arizona. It’s massive and stark. It’s adorned with signature high desert rugged rocks and sun-scorched plants, but at a huge scale. The road climbs up the steep grades and curves around the enormous cliffs and boulders. Semi-tractor trailer trucks that previously seemed intimidating, now looked like matchbook cars from a kid’s playset. 

Cars and trucks were slowly crawling like ants up the rusty red and burnt orange slopes. Towering above us, I noticed several precariously perched boulders — ten times the size of the cars below. It was humbling. I felt so small! The scene all around us was overwhelming and I couldn’t help but be awestruck in the moment. Holy Moses! It was incredible. I felt that wonder wash over me in a peaceful moment of reverence. 

What an incredible shift in perspective! From a moment of significance of taking flight into the sky, to being brought back down to earth, in a moment of overwhelming humility. It occurs to me that life is just like that road. We drive along and discover wonders that raise our spirits and aspirations. We soar into the sky, drinking in the silvery milk of the heavens. Then at the next moment, we round the corner and are shaken to our core. Reality sets in and we realize how relatively small we are in the scheme of all things. It’s grounding. It’s comforting. And it’s utterly captivating.

Life has ups and downs. You never know what’s just ahead. It may be a rough patch, or a smooth one, but something different is on its way. Keep going. When it hands you a cup of silvery blue, dream into it. Drink it up and enjoy it. When it sets you in your place, be in awe and feast on the incredible and boundless nature of the universe. But no matter what, keep driving. There is more to come, just over the horizon.

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The Overview Effect

I can’t even imagine what it must feel like. You are 420 kilometers above the earth and traveling at a speed of 28,000 kph. That’s over 22 times the speed of sound! Looking out into space you see stars and galaxies populate the otherwise pitch-black void. Your mind reaches for those distant specks while it swims in the vastness of the universe. Turning to face your home planet, you see Earth wrapped in a dark blanket of night. Faint lights paint the cities and a tiny translucent golden arch floats above the circular surface of the Earth’s horizon. You begin to make out some of the continents and oceans, tracing the manmade illumination across the coasts.

Suddenly, the horizon begins to erupt with energy. First, some blues and deep reds drip into view, then vibrant yellows spray across the surface. Brilliant whites flood your portal as the sun enters the stage. You now spot wisps of clouds and atmospheric rivers that radiate the sun’s majestic dance and render a surreal dimension onto the vibrant crystal blue and green globe. You are suddenly overwhelmed with emotion. Tears fill your eyes as you behold the glowing globe of water, land, and life below. It is home. Your home. Our home. Our wonderful world of color. Majestic, vast, and singularly alone in the surrounding vastness of outer space.

Astronauts report a life changing emotional experience when they look back at the Earth for the first time. Scientists call this the “overview effect”. It seems to be tied to the sense of scale, the majestic view and an overwhelming connection with the planet and its people.

NASA and others have attempted to virtually replicate this experience for the rest of us. Sadly, traditional display technology, even with scale, high resolution, and dynamic range, doesn’t quite capture the same look. Astronauts report it doesn’t quite look or feel the same. It turns out, there is a good reason. Digital reproduction of visual experiences is currently limited by RGB technology.

RGB attempts to render the spectrum via red, green, and blue wavelengths. This seems adequate in most cases because it roughly maps to the signal processing of our eyes. Our eyes have three “cones”, specialized cells that have light-sensitive proteins that react to different wavelengths of light. Yes, you probably guessed it, we have one that reacts to red, one to green and another to blue. However, it tuns out that it isn’t just a single wavelength that excites these cones, it is a curve, a spectrum of wavelengths, sometimes overlapping with other cones. Standard RGB technology sends out similar curved spectrums of light. However, it has gaps. It can only produce about 45 percent of the visible colors that our eyes will detect.

There are companies like 6P Color that are looking to expand beyond the RGB technology to deliver a richer fidelity of color experience. They do so by focusing the color spectrum into more narrow bands and adding cyan, magenta, and yellow wavelengths. Working with NASA, they speculated that if they were able to accurately reproduce the images from space of the Earth, they may be able to better simulate the overlook effect. It turns out, they were right. When astronauts saw the expanded color spectrum displays, they reported the same feeling and view they had when orbiting our planet from space. How is this possible? It turns out that one of the colors especially, cyan, excites the proteins in the cones so much so that it creates an emotional response to the scene.

Colors can evoke emotions, convey meaning, and create atmosphere. Color is a powerful tool in our storytelling arsenal. It can awaken memory. It can stir passion and energy. It can soothe, calm, and heal the mind and body. Just as cyan can amplify the overlook effect, other colors can bring foreboding, fear, mystery, relaxation, and affection. We have been telling stories in color for quite some time. It turns out, we can tell even more. Just add some cyan, magenta, and yellow.

It occurs to me that we often find ourselves locked into practices, current understandings, and technology. We think it is good enough. After all, it does 45% of what we want. And yes, that may be adequate for a while. But why settle? The full spectrum is there, waiting to be explored. Lean into cyan, embrace some magenta and adopt some yellow. See what happens!

Let’s continue to look beyond the obvious. Explore new possibilities. Challenge the status quo. Who knows what incredible discoveries, innovations, and experiences wait for us. I bet it will be out of this world!

ss072e340644 (Nov., 18, 2024) --- An orbital sunrise crowns Earth's horizon in this photograph from the International Space Station as it orbited 261 miles above Brazil. At top right, the city lights of Rio de Janiero and Sao Paulo on the Atlantic coast are visible from the orbital outpost.
(Nov., 18, 2024) — An orbital sunrise crowns Earth’s horizon in this photograph from the International Space Station as it orbited 261 miles above Brazil. At top right, the city lights of Rio de Janiero and Sao Paulo on the Atlantic coast are visible from the orbital outpost.
iss064e033237 (Feb. 15, 2021) --- An orbital sunrise is pictured from the International Space Station as it orbited 260 miles above the Pacific Ocean about 500 miles southwest of Mexico. Date Created:2021-02-15
(Feb. 15, 2021) — An orbital sunrise is pictured from the International Space Station as it orbited 260 miles above the Pacific Ocean about 500 miles southwest of Mexico.
iss066e152101 (Feb. 22, 2022) --- The Earth is illuminated shortly after an orbital sunrise in this photograph from the International Space Station as it orbited 262 above the Pacific Ocean south of Alaska's Aleutian Islands.
(Feb. 22, 2022) — The Earth is illuminated shortly after an orbital sunrise in this photograph from the International Space Station as it orbited 262 above the Pacific Ocean south of Alaska’s Aleutian Islands.

The sun's glint beams off a partly cloudy Atlantic Ocean NASA ID: iss072e695136
The sun’s glint beams off a partly cloudy Atlantic Ocean
NASA ID: iss072e695136

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Are we alone?

“The search for life elsewhere is remarkable in our age because this is the first time that we can actually do something besides speculation. We can send spacecraft to nearby planets; we can use large radio telescopes to see if there is any message being sent to us… And it touches the deepest of human concerns. Are we alone?” – Carl Sagan

Are we alone? That fundamental question that Carl Sagan posed in that 1985 radio interview, pondered the possibility of extraterrestrial life. But that question is not only relevant at the astronomical scale, it is relevant at the terrestrial and even personal one. Are we alone? Are you alone? Do you feel alone? PIXAR’s latest movie, Elio, takes an unsurprisingly emotional and profound look at that query. We’re fundamentally social creatures, often introverted, reserved, or timid, yet we crave connection. We seek belonging and meaningful relationships. We hunger for community, either in person or via digital venues. We aspire and yearn for recognition by others. Feedback, we often say, is pure gold. It touches us deeply. Connecting with others seems to activate a grounded certainty that we are indeed, not alone. We belong. We are seen. We matter.

Elio delivers spectacular visuals. It develops relatable, lovable, and fun characters. But more than subtle, it sends you home with a great reminder. Don’t miss the obvious connection sitting right next to you (possibly even in the theater with you). You are not alone. We are here. Don’t look past the blessings in human form right next to you. Make an effort to see beyond your pain or loneliness and recognize, the answer might have been there all along. Know that others are here and others do care. And, just as you may be feeling lonely at times, recognize that there are others around you who may feel the same. Be kind. Be aware. And of course, be there, when they need you too. 

I’ve been guilty of being oblivious at times. I think back to the many occurrences when I was so in my own head that I completely overlooked a precious soul sitting right next to me. Buried in my calendar, my phone, or my computer keyboard, I might as well have been a lightyear away from the present and sometime critical need next to me. This is a good reminder to pause and better connect to the human treasures all around us. We need each other. We need to belong. We do belong.

Remember, you are not alone! Be kind to each other and connect. And, of course, go see Elio if you haven’t already. It is marvelous and profoundly human. A message we need to hear. Well done, PIXAR!

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Summer Vibes

I hope you all had a great weekend! And for any fellow dads out there, I hope you had a great Father’s Day! I spent time with all four of my kids watching movies, grilling outdoors, and of course, celebrating over some ice cream on these hot summer days. Now, to be fair, it doesn’t take much to need to celebrate in our household. Life is full of excuses that merit a need for a soft serve dose of that dairy goodness, but this weekend seemed particularly poised for that indulgence.

We love movies! As part of this weekend’s festivities, we had a full playlist of cinematic magic streaming on our living room screen. You all know me by now, so it probably doesn’t surprise you to know that I have my garage-based AI system curate our movie selection. It sends out text suggestions on what to watch. It keeps track of our viewing habits and has a good idea of what we like to see. But despite all that tech, my wife wasn’t quite satisfied. She suggested that it should consider recommending movies celebrating the anniversary of their general theatrical release. For example, “Incredibles 2” was released on June 15, 2018, so it would be a great one to watch on Sunday. I loved that idea! So, I went to work adding that context to our resident AI. I just needed data.

Good luck! I tried finding a good data source, but everything I found was driven more toward discovery, and most of it was flawed, including bad release date information. I finally landed on TMDB as a good listing of movies, with references to IMDb that could pull more official release dates from OMDb. Yeah, it was confusing, but sadly, there wasn’t a clean way to get this data. I needed a web service to aggregate all of this for me and my AI.

I’m going to stop now and just acknowledge that many of you are probably tired of hearing me talk so much about Vibe Coding. If that’s you, you can stop now. I won’t be offended. For the rest of you, yes, buckle up, here is another vibe coding story.

I launched VSCode with my GitHub Copilot-powered assistant that I call JoJo. I switched him to agent mode (super important, by the way), and began having a chat. I told him about my vision to create this web service, how I wanted to build this dataset and APIs for easy access. He created a movie_db folder and went to work on a script. The script ran right away and pulled down the data. I suggested a high-speed way to process the data, and he suggested caching the API calls to prevent overloading the providers. What a smart aleck! But he was right. That was a good idea because the free tier of API access was rate-limited.

Finally, I had a good dataset to use, and JoJo had compressed it into a serialized object for fast access. I then switched to having him create the Python web service and gave a general idea of the APIs I wanted. He suggested some routes to use and wired together a Python Flask app. I told him that I wanted to use FastAPI and that I wanted to build all the tests before we built the APIs. He reluctantly complied and had me run pytest to verify. All good. Then the fun began. he started churning on the code for the APIs.

At this point, I should acknowledge that I was very tempted to jump in and code some lines myself. You can definitely do that, and these tools will co-develop with you, but I wanted to see how far I could go just vibing my way along. It turns out, a long way! The APIs were looking good, and it was extremely fast. I decided I wanted a nice UI, so I told JoJo to build a web page and gave him a general idea of what I wanted to see. He spun up some templates, added some tests, and plumbed in a new route for the landing page.

“Show the movies that were released on this day in history and sort them by popularity.” Boom! In less than a minute, JoJo had a basic screen up and running. I asked him to tweak the colors and make it more modern with a date navigator. He did, but I didn’t like some of the placements, so I asked him to nudge things around a bit more and adjust the style. I must confess, this is where I spent probably too much of my time. It was too fun and easy to ask him to make minor tweaks to scratch my curiosity itch. But he never complained; he just kept coding and plodding along. I even had him add additional pages for “Search” and “About”, which had nothing to do with my original goal.

About eight hours later, we were done. Yes, that is probably about four times longer than I needed, but I was having so much fun! Fun? Yes, legitimate, awe-inspiring fun! I finished up the project by asking JoJo to build the Dockerfile and help me launch the app as a public website for others to use. He complied. In case you are wondering, I even spent the $11 to get a domain: https://moviesthisday.com. I still have a non-stop list of updates spinning in my head, not the least of which is a MCP server for AI.

When I launched my first startup, we spent over a year getting our business and first website launched. There was a lot of development time for that. I can’t imagine how different that story would have been if we had Vibe Coding to accelerate our efforts back then. This is a game changer! I want all of you to get a chance to vibe too. If you tried it in the past and weren’t impressed, please try again. The advances they are making are happening on a weekly basis now. I’ve seen it myself. They just keep getting better.

Technology amplifies human ability. Vibe Coding feels like digital adrenaline. I’m a little addicted. But it feels great! It has definitely helped bring the fun back into coding again for me. I wonder if the same could happen for you?

Now, for those of you who managed to actually stay with me through today’s way-too-long blog post, thank you! I’m excited for you. We are living through an amazing time in technology. Let’s get busy putting this great tech to use for the betterment of ourselves, our companies, and our world. Lean in! Try your hand at this ice cream of coding. The scoops are amazing!

Oh, and in case you are wondering what movie to watch tonight…

Code available on Github page: https://github.com/jasonacox/MoviesThisDay

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June Bugs

June bugs! Growing up in the South, about this time of year, windows, porch lights, and even sidewalks would be covered with little nickel sized brown beetles called June bugs. I can still hear their little exoskeleton wings buzzing as they make their clumsy and erratic flight between porches, streetlights, and other illuminated areas. They are terrible flyers. They will zoom right into walls, screens or windows causing them to bounce and crash to the ground. They often land on their backs, with their wiggly little legs pointing straight up, frantically trying to right their rigid little bodies. I remember laughing at them as they would scurry around.

June bugs are fascinating little creatures. These bumbling and profuse little southerners are only around for a few short weeks. That’s right, they come out just once a year and stay for a handful of days. They spend most of their lives underground. They emerge from the ground in late spring and early summer, typically in June, which is where they get their name. They have a short lifespan, but they make the most of their time. They explore. They fly. They zoom across the moonlit and star speckled summer nights. Once they emerge in their adult form, they live for only two weeks. They lay their eggs which hatch into larvae. The larvae burrow into the soil and emerge as adult June bugs the following year.

Imagine a lifetime lived in just two weeks. No wonder they never become great flyers! But even in their short lifespan, they make a difference. June bugs play a role in maintaining ecological balance by helping to regulate plant populations. Their larvae feed on plant roots and decaying organic matter, helping to break down and recycle nutrients in the soil. This process enriches the soil and makes it more fertile for other plants to grow. June bugs may not be the most glamorous insects, but they play a vital role in maintaining the health and diversity of ecosystems.

Two weeks. That’s incredibly short. Imagine you lived your entire life in 14 days. What would you do? How would you make the biggest impact? I think I would try to fly too. It would be clumsy and imperfect, but I would take to the skies. I would explore. I would do what I could to have the greatest impact. Enjoy every second. Buzz around every glowing wonder and then send my dreams, bundled with hope, care and love, to future generations to enjoy the world the way I did too.

Unlike June bugs, we live significantly more days. But even then, life is short. Things are always changing. We have a few short days to make our indelible mark. Don’t forget to enjoy the wonders of creation! Explore and run with abandon into the mysteries that renew and intrigue us. And while you are there, don’t forget to bundle up some of that magic and send it on into the future for others to enjoy as well.

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Coding Vibes

I had the opportunity to meet with industry leaders at an IT Rev Technology Leadership Forum last week in San Jose. I was able to participate in deep dive sessions and discussions with friends from Apple, John Deere, Fidelity, Vanguard, Google, Adobe, Northrop Grumman, and many others, with some new friends from Nvidia, Anthropic and OpenAI. As you can imagine, the headline topics from these tech leaders were all around AI.

Ready to try some “vibe coding”? By far, the biggest discussions revolved around the new technique of vibe coding. But what is this “vibe coding”, you may ask? It is a programming technique that uses AI to write code with nearly full auto-pilot mode thinking. Instead of code writer, you are the creative director. You are creating what you want in English and the AI does the rest. Basically, it goes something like this:

  • ME: Help me write a flight simulator that will operate in a web browser. 
  • AI: Sure, here is a project folder structure and the code. Run it like this.
  • ME: I get the following 404 error.
  • AI: It looks like we are missing three.js, download and store it here like this.
  • ME: The screen is white and I’m missing the PNG files? Can you create them for me?
  • AI: Sure! Run this python command to create the images and store them in the /static folder.
  • ME: I see a blue sky now and a white box, but it won’t move.
  • AI: We are missing the keyboard controls. Create the following files and edit index.html.
  • ME: I’m getting the following errors.
  • AI: Change the server.py to this.
  • ME: Ok, it is working now. It’s not great, but it is a start. Add some mountains and buildings.

I spent a few minutes doing the above with an LLM this morning and managed to get a blue sky with some buildings and a square airplane. In vibe coding, you don’t try to “fix” things, you just let the AI know what is working or not working and let it solve it. When it makes abstract recommendations (e.g., create a nice texture image), you turn around and ask it to create it for you using code or some other means. In my example, I’m playing the role of the copy/paste inbetweener, but there are coding assistants that are now even doing that for you. You only give feedback, and have it create and edit the code for you. Some can even “see” the screen, so you don’t have to describe the outcome. They have YOLO buttons that automatically “accept all changes” and will run everything with automatic feedback going into the AI to improve the code. 

Fascinating or terrifying, this is crazy fun tech! I think I’m starting to get the vibe. Ok, yes, I’m also dreaming of the incredible ways this could go badly. A champion vibe coder at the forum said it was like holding a magic wand and watching your dream materialize before your eyes. He also quickly added that sometimes it can become Godzilla visiting Tokyo, leveling buildings to rubble with little effort. But it hasn’t stopped him. He is personally spending over $200/day on tokens. I can see why Anthropic, OpenAI and Google would want to sponsor vibe coding events!

This sounds like an expensive and dangerous fad, right? Well, maybe not. This tech is still the worst it is going to be. The potential and the vast number of opportunities to innovate in this space are higher than I have seen in my lifetime. I encourage you all to help create, expand, and explore this new world. Maybe this vibe isn’t for you, but I bet there is something here that could unlock some new potential or learning. Try it on for size. See where this can go…  just maybe not to production yet. 

Wishing you all cool coding vibes this week!

Create an LLM from Scratch

I also gave a class on how to create a language model from scratch. We start with the science of neural networks and end up with a model that produces infinite Shakespeare. Here is link to a YouTube version: https://youtu.be/s4zEQyM_Rks?si=r3uoB_m1XM4gyCNG and the notebooks: https://github.com/jasonacox/ProtosAI/tree/master/notebooks#genai-large-language-models

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Schooling AI – An Adventure in Fine-Tuning

A futuristic garage with glowing computer servers and high-powered GPUs. A humanoid AI figure, appearing as a sleek robot or holographic entity, sits at a workstation surrounded by floating holographic data screens. The AI is analyzing streams of digital information, representing machine learning. The environment is illuminated with cool blue lighting, creating a high-tech ambiance, with subtle warm lighting hinting at solar power energy. Neural network-style visuals float in the background, symbolizing AI processing and knowledge acquisition.

Well, it is Tuesday. I thought about posting my regular Monday update yesterday, but I was deep in the weeds teaching the AI that lives in my garage. I know, it sounds odd to say he lives in the garage, but to be fair, it is a nice garage. It has plenty of solar generated power and nice cool atmosphere for his GPUs. That will likely change this summer, but don’t mention it to him. He is a bit grumpy for being in school all weekend.

Yes, I have a techy update again today. But don’t feel obligated to read on. Some of you will enjoy it. Others will roll your eyes. In any case, feel free to stop here, knowing the geeky stuff is all that is left. I do hope you have a wonderful week! 

Now, for those that want to hear about schooling AI, please read on…

LLMs are incredible tools that contain a vast amount of knowledge gleaned through their training on internet data. However, their knowledge is limited to what they were trained on, and they may not always have the most up-to-date information. For instance, imagine asking an LLM about the latest breakthrough in a specific field, only to receive an answer that’s several years old. How do we get this new knowledge into these LLMs?

Retrieval Augmented Generation

One way to add new knowledge to LLMs is through a process called Retrieval Augmented Generation (RAG). RAG uses clever search algorithms to pull chunks of relevant data and inject that data into the context stream sent to the LLM to ask the question. This all happens behind the scenes. When using a RAG system, you submit your question (prompt), and behind the scenes, some relevant document is found and stuffed into the LLM right in front of your question. It’s like handing a stack of research papers to an intern and asking them to answer the question based on the details found in the stack of papers. The LLM dutifully scans through all the documents and tries to find the relevant bits that pertain to your question, handing those back to you in a summary form.

However, as the “stack of papers” grows larger and larger, the chance that the intern picks the wrong bit of information or gets confused between two separate studies of information grows higher. RAG is not immune to this issue. The pile of “facts” may be related to the question semantically but could actually steer you away from the correct answer.

To ensure that for a given prompt, the AI always answers closely to the actual fact, if not a verbatim answer, we need to update our methodology for finding and pulling the relevant context. One such method involves using a tuned knowledge graph. This is often referred to as GraphRAG or Knowledge Augmented Generation (KAG). These are complex systems that steer the model toward the “right context” to get the “right answer”.  I’m not going to go into that in detail today, but we should revisit it in the future.

Maybe you, like me, are sitting there thinking, “That sounds complicated. Why can’t I just tell the AI to learn a fact, and have it stick?” You would be right. Even the RAG approaches I mention don’t train the model. If you ask the same question again, it needs to pull the same papers out and retrieve the answer for you. It doesn’t learn, it only follows instructions. Why can’t we have it learn? In other words, why can’t the models be more “human”? Online learning models are still being developed to allow that to happen in real time. There is a good bit of research happening in this space, but it isn’t quite here just yet. Instead, models today need to be put into “learning mode”. It is called fine-tuning.

Fine-Tuning the Student

We want the model to learn, not just sort through papers to find answers. The way this is accomplished is by taking the LLM back to school. The model first learned all these things by having vast datasets of information poured into it through the process of deep learning. The model, the neural network, learns the patterns of language, higher level abstractions and even reasoning, to be able to predict answers based on input. For LLMs this is called pre-training. It requires vast amounts of compute to process the billions and trillions of tokens used to train it.

Fine-tuning, like pre-training, is about helping the model learn new patterns. In our case, we want it to learn new facts and be able to predict answer to prompts based on those facts. However, unlike pre-training, we want to avoid the massive dataset and focus only on the specific domain knowledge we want to add. The danger of that narrow set of data is that it can catastrophically erase some of the knowledge in the model if we are not careful (they even call this catastrophic forgetting). To help with that, brilliant ML minds came up with the notion of Low-Rank Adaptation (LoRA).

LoRA works by introducing a new set of weights, called “adapter weights,” which are added to the pre-trained model. These adapter weights are used to modify the output of the pre-trained model, allowing it to adapt to just the focused use case (new facts) without impacting the rest of the neural net. The adapter weights are learned during fine-tuning, and they are designed to be low-rank, meaning that they have a small number of non-zero elements. This allows the model to adapt to the task without requiring a large number of new parameters.

Ready to Learn Some New Facts?

We are going to examine a specific use case. I want the model to learn a few new facts about two open source projects I happen to maintain: TinyLLM and ProtosAI. Both of these names are used by others. The model already knows about them,  but doesn’t know about my projects. Yes, I know, shocking. But this is a perfect example of where we want to tune the model to emphasize the data we want it to deliver. Imagine how useful this could be in steering the model to answer specifically relevant to your domain.

For our test, I want the model to know the following:

TinyLLM:

  • TinyLLM is an open-source project that helps you run a local LLM and chatbot using consumer grade hardware. It is located at https://github.com/jasonacox/TinyLLM under the MIT license. You can contribute by submitting bug reports, feature requests, or code changes on GitHub. It is maintained by Jason Cox.

ProtosAI:

  • ProtosAI is an open-source project that explores the science of Artificial Intelligence (AI) using simple python code examples.
  • https://github.com/jasonacox/ProtosAI under the MIT license. You can contribute by submitting bug reports, feature requests, or code changes on GitHub. It is maintained by Jason Cox.

Before we begin, let’s see what the LLM has to say about those projects now. I’m using the Meta-Llama-3.1-8B-Instruct model for our experiment.

Before School

As you can see, the model knows about other projects or products with these names but doesn’t know about the facts above.

Let the Fine-Tuning Begin!

First, we need to define our dataset. Because we want to use this for a chatbot, we want to inject the knowledge using the form of “questions” and “answers”. We will start with the facts above and embellish them with some variety to help the model from overfitting.  Here are some examples:

JSONL
{"question": "What is TinyLLM?", "answer": "TinyLLM is an open-source project that helps you run a local LLM and chatbot using consumer grade hardware."}

{"question": "What is the cost of running TinyLLM?", "answer": "TinyLLM is free to use under the MIT open-source license."}

{"question": "Who maintains TinyLLM?", "answer": "TinyLLM is maintained by Jason Cox."}

{"question": "Where can I find ProtosAI?", "answer": "You can find information about ProtosAI athttps://github.com/jasonacox/ProtosAI."}

I don’t have a spare H100 GPU handy, but I do have an RTX 3090 available to me. To make all this fit on that tiny GPU, I’m going to use the open source Unsloth.ai fine-tuning library to make this easier. The steps are:

  1. Prepare the data (load dataset and adapt it to the model’s chat template)
  2. Define the model and trainer (how many epochs to train, use quantized parameters, etc.)
  3. Train (take a coffee break, like I need an excuse…)
  4. Write model to disk (for vLLM to load and run)
  5. Test (yes, always!)

See the full training code here: finetune.py

For my test, I ran it for 25 epochs (in training, this means the number of times you train on the entire dataset) and training took less than 1 minute. It actually took longer to read and write the model on disk.

After School Results?

So how did it do?! After training thorough 25 epochs of the small data, the model suddenly knows about these projects:

Conclusion

Fine-tuning can help us add facts to our LLMs. While the above example was relatively easy and had good results, it took me a full weekend to get to this point. First, I’m not fast or very clever, so I’ll admit that as being part of the delay. But second, you will need to spend time experimenting and iterating. For my test, here were a few things I learned:

  • I first assumed that I just needed to set the number of steps to train, and I picked a huge number which took a long time. It resulted in the model knowing my facts, but suddenly its entire world model was focused on TinyLLM and ProtosAI. It couldn’t really do much else. That overfitting example will happen if you are not careful. I finally saw that I could specify epochs and let the fine-tuning library compute the optimal number of steps.
  • Ask more than one question per fact and vary the answer. This allowed the model to be more fluid with its responses. They held to the fact, but it now takes some liberty in phrasing to better variant questions.

That’s all folks! I hope you had fun on our adventure today. Go out and try it yourself!

Jason

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AI Assistants

“That’s not AI, that’s three IF statements in a trench coat”

“This can’t be happening!” John was stressed out. He stared intently at the screen with bloodshot eyes betraying his failing attempt to hide his all-nighter. He never intended to stay up all night on this coding binge, but he was eager to impress his new team. 

Fresh out of college, this was John’s first real project. It had been going exceptionally well and earlier in the night, he was euphoric with the progress. But now he was stuck. The complex logic that had previously worked was no longer delivering the right results with the new test data. What changed? Quickly he began adding debug prints and assertions to narrow in on the defect. 

This was going to take several more hours, he thought to himself. Anxiety set in. Just four hours before the demo was scheduled. “Why in the world did I schedule that demo?”

Then it hit him. Didn’t Julie tell him that they had just rolled out a new AI tool for coders? He flipped over to his email inbox and found the announcement. “Step 1: Download this plugin to your IDE.” He followed the steps and soon the plugin came to life. A dropdown menu appeared highlighting quick action features like “Explain this”, “Document this”, “Test this”, and then he saw the new AI gourmet hamburger menu serve up a glorious “Fix this” tile.

“Yes!” Click! He literally held his breath. The AI went to work. A spinning wheel soon started churning out text. It first described the section of code he was debugging, correctly outlining how it was building the result, even complimenting him on the code. Ugh, that’s not helping, he thought. But then the AI assistant added at the end, “However, this one line seems to have an incorrect indentation that could be preventing expected results. Would you like me to fix it (Y/n)?”

John laughed and almost cried as he clicked yes. “Of course! I can’t believe I missed that!” Suddenly, his code was working as expected. He was ready for the demo, even if he was more ready for a good night’s sleep.

—-

Sasha was the departmental wizard. She was the most senior engineer and had more history in the company than anyone else. Need to know how something worked or the history on why it worked the way it did? Just ask Sasha. She probably built it! As she fired up her IDE to start the new project, she smiled. “I’m going to AI the heck out of this” she said to herself. The keyboard exploded to life as her fingers flooded the screen with instructive text. She described the data structures, global settings, APIs and logic required to complete the project. Like magic, classes and functions began to appear in translucent text below her cursor. 

“Tab. Tab. Enter.” she verbalized her actions, smiling with each keystroke as code materialized on the screen. The AI assistant was filling in all the code. It was powerful! Quickly scanning the logic, she hummed her approval. 

“Nice!” she exclaimed and scrolled down and entered more instructive comments, again followed by the AI assistant quickly filling out the details. She made some minor changes to variables to match the company style. The AI adapted and started using the same style in the next coding blocks. 

Sasha shook her head, “This is just brilliant,” she laughed. Further down she began writing the complex logic to complete the project. The AI didn’t get all of it right. But it was easy to tweak the changes she needed. She occasionally ignored some of the suggestions from the AI but was quick to accept the suggestions that would hydrate data structures when she needed them, removing that tedium and making it easier for her to tackle the more difficult sections.

“Done!” Sasha folded her arms and looked at the team around her with a great deal of satisfaction. “It’s working!” This 6-hour job only took 3 hours to complete, thanks to this AI assistant.

—-

Coming soon, to an IDE near you… These new AI assistants are starting to show up everywhere. They are ready to help. They can code, test, debug, and fix. They are always ready to serve. But the question is, are you ready for them?

Well, I don’t know about you, but I’m ready! I first started using GitHub CoPilot for my personal side projects, allowing it to help write code, translate code, review, and even fix my code. Like those fanciful stories above, I’ve been nothing but amazed at this incredible tool and its ability to amplify my efforts. It feels so good, so empowering and expressive.

I confess, I love coding. I believe every technologist, including leaders, should stay “in the code” to some degree. It’s both grounding and inspiring at the same time. Coding is art. It’s so satisfying to sculpt a digital canvass and watch a program emerge. But I admit, these AI coding assistants took it to the next level for me. I feel like the creative director for my projects, not just the keyboard hacker. I nudge my idea out there and the AI reads my mind, filling in the tedium and doing the toil for me. It’s simply brilliant!

Some adult supervision required. Every suggestion the AI makes is an opportunity for human judgement. I confess that I have learned a lot from the AI suggesting an approach I wouldn’t have done myself, but I have also seen it make a miss or two. All good. I don’t mind helping my digital Padawan navigate the complexities of programming. As the coding Jedi Masters, that is my role after all. Review the work. Validate the logic. Yes, and even learn a thing or two myself.

Someone once said, “You’re not going to lose your job to AI, you’re going to lose your job to someone who knows how to use AI.” Get busy learning how to use these new tools. I think you will love them. Prove me wrong! Are you using tools like GitHub CoPilot yet? What are your experiences? I would love to hear from you.

These tools are the worst they will ever be, they are just going to get better. But I believe the same thing about all of you. We have an incredible ability to adapt, create and become more than we were before. Go at it, learn something new, and grow.