This topic is normally only taught at the master's degree level. But I'm sure you can learn it!
Click and drag to rotate the paraboloid!
Drag to orbit the valley. The person stays visible as you compare the terrain from different angles.
Yes! The world is messy and we can't just plug stuff into equations. As we have a bunch of data, we can't rely on the quadratic formula, completing the square, etc. I mean it would be insane to solve quartic equations by hand with this nightmare formula:
So what in the world do we do? We use computers!
At each point, we can calculate the slope at that point and use it to decide which downhill step to take.
Spoiler for Q10: Computers can think like someone standing at the edge of a paraboloid, and make small steps downward until it knows the slope is flat. Remember that line we drew through the vertex of the parabola from Q4? Computers can figure that out, but in 3D too.
In Algebra II mode, we can say the slope is flat when the secant plane has no incline, like a perfectly level sheet across the bowl.
Computers really just make a bunch of educated guesses until it gets close enough to the result we want: the lowest point of the paraboloid.
This is the concept of Gradient Descent, a foundational reason why ChatGPT works!!
Below is a 3D version of our weird bowl. The "best" result is the deepest part of the bowl (the Global Minimum). But sometimes, a marble gets stuck in a shallow dent on the side (a Local Minimum). The slider controls Stochastic Noise: the middle gives a useful shake that fades over time, while the far right can shake marbles right out of the bowl.
A little shaking helps the marbles escape shallow dents, but the shaking has to calm down. If the bowl keeps shaking forever, the marbles never settle into the best spot.
Loop running: marbles reset automatically.
You just learned the concept of Stochastic Gradient Descent! This concept is not normally taught until 500-level graduate math classes 😱!
Stochastic is a fancy word for random.
To summarize, adding a bit of random "shakiness" helps computers better approximate to the best "local minimum" compared to going straight down.
Some shakiness is good, but too much causes the marbles to fall out, so we need just the right amount.
In AI training, this "shakiness" is usually called noise or stochasticity. Shaping the bowl is one analogy for training AI. Temperature is different: it matters later, when ChatGPT is actually writing its response.
Instead of marbles in weird bowl holes, instead picture the depth of the hole as reducing pollution, saving resources, etc.
You think that’s crazy? It’s about to get nuts.
Drag to rotate. Move the slider to scan the 4th dimension (Edibility). Watch as words morph into view and grow in size when the "Flavor-Scanner" hits their specific coordinate.
This animation is a depiction of how ChatGPT is "trained" to know what to say. Words coming into place and a bowl being shaped are both analogies for what it means to train AI.
After training, the model uses the patterns it learned to choose one word after another. The word space helps represent possible next words, and the shaped bowl is an analogy for the trained model already being ready to guide the output.
P.S.: What we talked about today is exactly why TikTok and Instagram Reels are so addicting and the Oxford Word of the Year is “Rage Bait”. The “marbles at the bottom of the bowl” for social media have to do with watch time, comments, and shares. Outrage and dishonesty is more effective at this than positivity and the full truth.
One last note: examples like walking down a hill blindfolded, shaping a bowl, and dropping marbles into a bowl are analogies. They are not a perfect representation of how AI works, but they help get the general ideas across.
Thank you so much for listening and participating!!
I am a graduate of Santa Fe Prep and a Bachelor and Master of Science in Computer Science Graduate from Colorado School of Mines. People say I have "golden retriever energy", and I love being physically active. I am an avid weightlifter, trail cyclist, snowboarder, runner, and more. I moved back to Santa Fe to work a remote position as an AI Research Engineer. I was a member of the Alpha Tau Omega fraternity as Philanthropy Chair, and I lived in the frat house basement for two years (at the expense of my GPA). I also love to sing, write, and enjoy long conversations with friends and family.