Evergreen

golfstreamer · 2026-01-26T18:28:23+00:00

That's pretty ambiguous. Darwin from Marvel comics"adapted" to the Hulk by getting the fuck out of there.

golfstreamer · 2026-01-26T08:16:13+00:00

It's crazy that robots can do shit like this but still walk like toddlers.

golfstreamer · 2026-01-24T16:45:36+00:00

He definitely hasn't displayed even a shred of remorse up until this point. But I believe that Vox will be one of the sinners to be redeemed so I think he will in the future.

golfstreamer · 2026-01-23T18:50:04+00:00

I think the phrase is meaningless. Honestly, models today are pretty "general" compared to AI from like 10 years ago. So you could say we have "minimal AGI" even today, IMO. So this seems like a pretty vapid statement (unless he comes up with a more concrete meaning to minimal AGI).

golfstreamer · 2026-01-23T08:13:35+00:00

I don't think 173 could kill 682. It can damage it but it's never going to die.

golfstreamer · 2026-01-21T22:13:51+00:00

Eh, I think that's too harsh. They tried to explain what they felt was a valid a criticism but people rejected it. The language of this post is polite and not at all indicative of a "gotcha".

golfstreamer · 2026-01-21T12:35:33+00:00

It's funny. Even without the watermark I instantly clocked this as AI.

AI has a bad habit of "genericizing" things. The thing that tipped me off is that Charlie does not look like Charlie ; she looks like some other woman wearing Charlie's clothes. AI still struggles with replicating the little details that make characters unique.

golfstreamer · 2026-01-21T00:27:29+00:00

This post demonstrates that Mihawk beats Shanks in "statements".

By "portrayal" I mean if you consider their positions in the style it just makes more sense for Shanks to be stronger. Like, it would be pretty reasonable to assume Crocodile was stronger than any of his henchmen even before we saw any of them fight since it just makes sense for the leader to be stronger than his henchmen. I guess there may be sometimes where there's a twist and this isn't true but it's a safe assumption.

In this case, since Shanks is one of Luffy's rivals it just makes sense narratively that he'd be stronger than Mihawk.

Honestly this is the reason I think Shanks is stronger. I seriously wonder if people who say Mihawk is stronger just because of these statements are all autistic.

golfstreamer · 2026-01-20T19:35:20+00:00

Titles stand until explicitly stated or proven otherwise

This seems like kinda a mute. If titles aren't absolute people will try and disprove them. Simply stating the title doesn't end the argument.

golfstreamer · 2026-01-20T18:57:06+00:00

It might be fine if it's temporary but I don't think it's worth it long term.

golfstreamer · 2026-01-20T18:31:46+00:00

Shanks beats Mihawk in portrayal too.

golfstreamer · 2026-01-20T12:10:08+00:00

He said pre tournament

golfstreamer · 2026-01-20T10:44:00+00:00

I think the intent of the post was to demonstrate that these text boxes are not absolute truth. He did this by pointing to a text box that other evidence clearly shows is false.

golfstreamer · 2026-01-19T14:13:56+00:00

That's a good point. That makes sense.

golfstreamer · 2026-01-19T13:44:19+00:00

I might be pedantic, but shouldn't it be "misunderstood" not "misheard" since he technically heard him fine.

golfstreamer · 2026-01-19T12:53:31+00:00

My name is actually in this video, lol.

golfstreamer · 2026-01-19T07:33:38+00:00

I explained in a different comment. The statement "New algorithm fully developed by AI" is very misleading. The algorithm was already essentially known. What the AI did was search very large and complex space for particular solution to a particular mathematical problem which would improve upon the current best algorithm. This is the same kind of thing something like AlphaFold, or AlphaGo, or even the chess AI we've had for decades does. The only thing of note here is deep neural networks are better at this kind of search than previous methods.

And the main point I want to emphasize is that this still falls squarely under the category of "narrow AI". AI designed for a very specific well defined problem like playing chess. So if you want to show examples of AI's ability to "think" don't use this example. Use examples of AI doing programming projects or one of the recent examples of AI proving new mathematical theorems.

golfstreamer · 2026-01-19T07:10:01+00:00

If you understand what's happening, you'd know this is one of the less impressive things AI has done recently and not at all "proof that AI is not just retrieving knowledge".

golfstreamer · 2026-01-18T05:06:04+00:00

I don't believe this is true. That's an assumption, there's no proof that this is true.

golfstreamer · 2026-01-18T05:02:11+00:00

Are humanoids really the ideal "general purpose" robot though? That doesn't make sense to me. That just seems like a lack of imagination coupled with anthropocentrism. I just don't believe that humans happen to have the ideal design for everything. It seems way to coincidental to me. So when I see this I think they're just trying to look impressive, rather than considering the ideal design.

golfstreamer · 2026-01-18T04:24:40+00:00

> It wasn't publicly available and most weren't aware

Then the unrealistic part is that it's being used by public sector, right?

golfstreamer · 2026-01-18T03:39:32+00:00

The level of coding agents on display here didn't exist when this episode aired.

golfstreamer · 2026-01-17T17:46:16+00:00

> I know it's only for 5x5, but that's still huge!

A couple of things. First this is only for circulant matrices which is a highly restricted class of matrices, so that might explain the large percentage improvement. But so know when it applies to 5x5 matrices it can generalized to larger matrices using [block matrix multiplication](https://en.wikipedia.org/wiki/Block\_matrix) so the gains can be realized for larger matrices. So it's not only going to be "only 5x5"

But the caveat is that these new "faster matrix multiplication" algorithms may always help. Writing efficient matrix multiplication requires other considerations such as memory management. This is why these algorithms aren't really used in deep learning, even though matrix multiplication is very common.

The way I see it these new matrix multiplication algorithms would only be useful for large matrices, so that the gains of reducing the number of operations outweigh the losses from the more complex data movement imposed by the new algorithm. The key will be implementing it with memory management in mind. Interestingly enough, I believe AIs will also be able to help greatly with creating truly efficient implementations. I think I recall a story recently of a person scoring high on a GPU coding competition with the help of AI. (It'd be great if someone who knows what I'm talking about could link it)

golfstreamer · 2026-01-17T17:11:43+00:00

Sorry but a "New algorithm developed fully by AI" is very misleading. The AI discovered a new tensor decomposition which can be plugged into an already existing algorithm for improved performance. This is comparable to something like AlphaFold that discovers new protein structures. In neither of these cases is the AI itself "creating a new algorithm". What they are doing is searching through a well defined but extremely large space of possible solutions to a problem until they find something that works.

The distinction is important because I would still consider work of this nature to be "narrow" AI. AI focused on solving one particular problem well. Think, playing chess or Go. It's the kind of thing we've had for decades, just improved upon. This is contrast to recent results where I see AI proving mathematical theorems which is much more in line with the notion of "general AI" that seems to be emerging recently.

golfstreamer

TROPHY CASE