I mean, not a novel insight on my part, but Feynman really is an amazing explainer. This was so much fun to listen to. He's completely right too. Everything reduced to something so easy I think anyone could comprehend it. It's also great to dig back into the fundamentals. Always keep yourself in them. They often help you think novelly about something others are taking for granted.
I love that he stopped at the transistor and my brain just kept going. A transistor works because a voltage at the gate creates an electric field that opens or closes a channel for electrons. And an electric field works because charge creates a field that exerts force on other charges. And that works because of gauge symmetry, which requires the field as the price for local phase invariance.
The problem of pattern recognition is interesting. It's true that in the last 50 years since this talk we've made significant strides in solving such problems. We're at the point we have enough computing power we can work with natural language to a really impressive degree. I'm curious what pattern recognition problems still evade us at this point. The big one that comes to mind is in reducing the amount of input data required. Right now we need an enormous amount of training data for these models relative to what a human seems to need. Reinforcement learning always seems promising, but existing techniques are so fragile and slow compared to supervised learning.
It's at least refreshing to see people freaking out about computers taking jobs a half a century ago and watching someone else try and explain to them they're asking wrong question. I find it so exhausting being asked if the word guesser will turn us all into paperclips. Same for the question about if the computer will become Big Brother. I mean, a Manhattan Project contributor is maybe not your best steward of ethical philosophy. That said, humans are adaptive advisories, so while more surveillance is happening than ever before, it still hasn't stopped dissent or régime change. We're just better now at distracting ourselves to death.
We're still trying to fix the mess we created with the car over the last century. We haven't even begun to undo the mess we've made with the smartphone. Let's give chatbots to everyone! To be clear, these technologies can be great when used in their ideal niche, but it's the forced mass adoption that unlocks chronic problems. Monied interests bending the fabric of society to perpetuate them. Large monocultures are inherently fragile. When faults occur the shock ripples system-wide, with no alternatives to absorb it.
The comments about how clueless Americans are about the rule of law being like an infallible law of physics is funny in hindsight now they have an active paramilitary kidnapping their neighbours, run concentration camps across the country, and are building out one of the largest dragnet surveillance networks in history.
With the AI bubble, maybe we're at the end of investor story time? We've got every investor locked into a race for a commodity based on the story that computers will soon become god. Sounds like we're at the end of a JRPG. I'd speculate it's the end of the road for tech VCs but it looks like they're trying to unload those assets onto pensions and retail investors.
Decentralization is the right goal, but it will require regulation to scale. Left unchecked, markets naturally concentrate power. Any initial advantage lets a player absorb competitors, compound their strength, and repeat. If we want to stop monopolies from swallowing our institutions, we need to act soon, before policy-making and even enforcement are fully outsourced.
That comment about recognizing a problem, and agreeing on the problem, is absolutely the first most important step. Without consensus that a problem exists, any attempt to fix it is doomed to derail. I have seen this fail too many times. Everyone must agree on the diagnosis and be willing to act. This will be difficult. Powerful interests profit from the status quo and will actively resist recognition, let alone solutions. The decades-long fights over the greenhouse effect and tobacco prove how hard it is. Today, manufacturers add a battery to rebrand cigarettes as blueberry vapes, while bookies run apps or games to call it a prediction market or loot boxes rather than illegal gambling. As long as exploitation is profitable, these battles will continue.
I've gone on record before to say, stop teaching sorting algorithms. They're not interesting. Teaching early Computer Science students sorting algorithms is a form of ritualistic hazing at this point. Teach them convex hulls instead. Full of graphics and tons of obvious practical applications to the beginner or interdisciplinary studier. However, this is a great talk. So watch it anyway.
The big reason is that this is what real performance looks like. This isn't some theoretical big-O notation view of the world. This is how real computers work and how they really don't align with that simple model everyone was taught.
