programjames
Joined 3 years ago
Joined 3 years ago
FTFY. Do not conflate all competition as good for the consumer.
What I learned spending a lifetime making the world a little bit worse for everyone else for fun and profit.
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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.
Say there was a Chinese artist in a room...
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.
> 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.
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.
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.
This is probably less restrictive than you are advocating for in your previous comment: as long as there is plausible deniability, the speech goes free.
[1]: https://benjaminrosshoffman.com/the-debtors-revolt/
[2]: https://www.lesswrong.com/posts/tihhx7iy8C6yyHaC2/the-corner...