This is very cool, thank you. I understand the choice of no account, but would have loved if my progress could be linked between devices, maybe icloud sync?

You know, I hadn't actually considered iCould sync, thank you! I didn't like the idea of not syncing devices either, but couldn't justify just eating the storage costs since it's a free app.

But using iCloud would let users cover their own storage costs for syncing practice/progress/medal/challenge data.

I'll take a look at implementing this when I get some free time so I can have high confidence in the approach. Thanks again!

Recent recording from NYU Courant institute.

This is cheap. Plenty of scientists, many of whom are my friends, are working very hard on finding new therapies for cancer, they were doing it before genomic models came along and still doing it now. The amount of times something in the media is lauded as "holy grail" that is never heard from again because it either only works in mice or turns out to be toxic or 100s of different reasons is massive. In my opinion this attitude of putting rose glasses on is detrimental to scientific progress. People outside of cancer research routinely underestimate how hard it is to find a working protocol. I think it is better to have sober attitude because it allows one to see the limitations and challenges that need to be tackled, blindly hoping AI can solve everything and deliver miracle cures is exactly the attitude that lets people sit on their asses and do nothing.

I think we need to be honest here. Author is basing it on one small experiment of picking up a block, relies on an whole IK controller pipeline to do the job, and does not compare it to full VLA or WAM models. They then proceeded to extrapolate the token throughput (mind you not the same as controller throughput) into supposed 2029 timeline, from one example.

Code as policy is a bad interface in my opinion, but VLM planning has promise. This has been tried in 2022 https://say-can.github.io/, and recently reformulated in https://lianegalanti.github.io/Pigey/

Thing is even recent Gemini Robotics 2 argues for architecture that has a VLM planner and then a VLA/WAM controller + a local small VLA model when connection disappears. And recent SOTA architectures rely on hierarchical design. I think this might be a sensible way to go about it. If you were to train GPT-X on robotics data and to output actions, congratulations! you've just made a VLA. It is enticing for people to just wish for one architecture to do it all, which is why we get stuff like this. I think there is a lot more to gain from modularity and we should not be afraid of specialization.

I think it is important to divine what currently AI is good for and what it is not even in such verifiable environments like math. Current hyped announcements about breaking conjectures are notable and are a marker of how much improvement was made. But as I read them, and maybe I am wrong, I see it as a large model+ harness executing a broad brute force search and trying solutions until something sticks. There are lots of problems like that and they should be solved, as often they are perhaps less important or overlooked, or just a slog, any field of research has these, math even more so.

However, this is very different from inventing new mathematical machinery that allows to break old problems, I think it will be a while until AI will be able to do it if at all. For now I think we will be moving to a symbiosis where an AI cracking a problem and giving a solution, inspires a human to invent new techniques.

finally someone is saying it our loud lol. mathematicans are just finding lower and upper bounds and having a computer input them into a theorem prover more times than a human is able to on their own. ai imo isnt solving anything.

Or use sticky notes! My friend annotated her favorite book with notes for me and it was awesome.

Personally found newest paperlike to be a lot like glass still, you barely get that paper feel at all and I hated it. They tried to keep clarity of the screen near glass level, but that affects the feeling a lot. Eventually I did some research and found that Japanese screen protectors that give you a feel of Kent paper are excellent for writing, so I wholeheartedly recommend those. You can find best rated ones by looking at top rated ones on jp websites, I have bellemond one.

I was considering getting M5 Max mbp with 128GB, but at that price it is just ridiculous, 64 version costs now roughly what 128 was before and that was a stretch for me. At this point might as well stick to my ol reliable M1 Pro mbp.

Edit: I'll say that now it seems also very hard to justify buying top of the line apple hardware for the enterprise. Getting top laptops for just a team of 10 people now means extra $20k just for RAM on top of already a higher base price.

Wow I'm old, I still remember working with YOLOv2.

I'm pretty sure this is not the use case at all but man do I miss bootcamp. Even for games if we could just run linux without a need for crossover, gaming on mac machines would be a dream.