What I learned spending a lifetime making the world a little bit worse for everyone else for fun and profit.
-----
Their entire mindset seems to be, "how can I take advantage of other people making mistakes to make a few dollars here and there? and how can I induce them to make even more mistakes in my realm of influence so it is even easier to profit from them?"
This is why he is always chasing the latest fad—"dropshipping massage guns, rug tufting, rainbow-loom bracelets, you name it"—people who follow fads are less likely to do their research and more likely to click buy on the overpriced TikTok ad. AI just empowers him to do more of this.
The only skill he seems to work on is his "taking advantage of others" skill. It's astounding that he got to this age without knowing even the basics of programming... and he only learned those basics once it became relevant to taking advantage of others. Rather than trying to create something new, or create a better version of something old, he just wants to disrupt efficient commerce so he can skim off the top.
I'm sure he makes a ton of money doing this. I wish that weren't possible.
It's not about buying the thing or not but about inserting oneself as an unnecessary middleman who just raises the price, which only works due to the customer's ignorance. It's essentially deceiving someone into paying more than they had to. I don't see how it could be considered positive.
I see, that makes a little more sense if you start from the assumption it isnt adding value and also raising prices, then of course it isnt positive.
I think this underappreciates that value added by having multiple sellers/retailers competing and advertising. I dont think the world where everything must be bought from a manufacturer or small set of retailers is better.
Will we? I will value output from people I personally care about, because I want to know more about them. But what about the other 8 billion people? Do you value their output because they are human or for some other reason?
In an abstract sense, I agree that I value human output because I value humans, even if I never see those humans or their output. But I only can process 10 bits/second, while there is probably a million times that much being posted to the internet. I simply don't have the capacity to care about it except in the abstract sense.
When people communicate to me I want them to maximize my comprehension bitrate. AI output is usually dense in incomprehensibility and sparse in bitrate. But the prompt they fed into the AI? Much higher bitrate. And if it's hard to understand, well I can always ask my own AI to help me interpret.
I understand it is a little selfish to want people to maximize my comprehension (what about the thousands of other readers?). I also understand there can purposes other than communication in writing (fiction -> pleasure, poetry -> art). I agree with you that we shouldn't care if it's AI or human writing for these other purposes. But when the goal is one human transferring bits from their brain to mine, playing telephone with an AI cannot be more efficient (it necessarily decreases channel capacity).
There are two exceptions.
1. When AI is good enough to "read people's minds" it can extract extra bits than what they explicitly meant to include in their prompt... but at that point why am I even bothering to listen to them, and not have the more powerful, smarter AI tell me what they think?
2. AI can run experiments or prove things, and I shouldn't have my AI duplicate that work. In this case I would want them to explain what tasks they set the AI out to do, and then provide the results. I would not complain if the results are an AI writeup, though usually I would want to know what in the results the human author felt was important.
I did have an experience with AI where I was asserting something min some text I was having it proof. And it actually said “I double checked your statement and here and I think you made a mistake. I rephrased it with the correct background and interpretation” (paraphrased). And it was completely right. I had misinterpreted some data and it went and got the data and double checked me. The final product it produced was much better than what i wrote originally (in large part because it was no longer false). So AI maybe closer than you think to those conditions.
> But the prompt they fed into the AI? Much higher bitrate.
You might be projecting from your own use of AI. IME there’s a large overlap between your exception 1 and the kind of people who copy/paste AI responses.
I.e., when you find yourself dealing with a meat proxy, the original prompt is unlikely to provide anything useful. So as you say, “Why are you even bothering to listen to them.”
> There were some technical findings along the way—for example, Kavish found that DDPM, while theoretically ideal for denoising in diffusion models, diverged, and that flow matching performed much better.
When they say "theoretically ideal" they mean a specific thing: the DDPM loss is information theoretically the number of error correction bits needed to recover an image. At very low noises, this quantity goes singular. This is not actually a problem—you should bound the log-SNR of your schedule by the image quantization level (usually 9 bits) anyway, and a trained bound lands within 10% of this.
Flow matching does not diverge because it removes the log-SNR rate from the loss. Since the rate can span several orders of magnitude over your schedule, you should importance sample during training. My guess is Kavish forgot to do this, leading to divergence.
Chess has always been "just a game". Sure, it teaches valuable life lessons, and it is fun to defeat your opponents through superior training and strategy, but it is "just a game".
Mathematics was historically "just a hobby". Much theoretical work is still "just a hobby". But, for the past few hundred years, humans that better understood the theory could find very profitable applications.
That is no longer true. Computers have solved mathematics, like they did chess two decades ago. A human will never find a better application than a computer, just like they will never find a better chess move. Yet people still play chess, and people still make money tutoring chess.
That is the future of humans in mathematics. Mathematics will become mathematics competitions. It will be just another intellectual sport. Sure, a sport that teaches valuable life lessons, but still "just a game". If you are going into mathematics today, your future career is as a competition mathematics coach.
What do you think mathematics is? "Just a hobby"? Developments in mathematics made possible the industrial revolution, the information age, everything! Do you think the world will be the same when math is "solved"?
Maybe don't take words out of my mouth. I studied math when I was younger, and got to the top 0.001% in mathematics competitions. Why did I study so hard? In order:
1. I recognized that understanding math had incredibly profitable applications.
2. It was a sport.
3. It was a hobby.
Do I think the world will look the same when math is "solved"? Absolutely not! And we're seeing it transform right before our eyes. I routinely ask Claude, "here's the general idea for a math/cs/ai problem I'm working on, can you help me figure out the maths? oh and then implement it too."
Could I figure this out myself? Of course. Having the idea is halfway to formalizing it in math. But I remember even last year working on GPU kernels by hand and having a bunch of little arithmetic or indexing errors burn me, because I'm just slower and less perfect at doing the math correctly. Now I basically just tell Claude, "go optimize a GPU kernel for this problem". I still have to tell it what to look out for (architectural, algorithmic, memory improvements), but I'm sure the next model won't even need that.
reply