mbowcut2 · HackerTrans

16 日前議論

I made myself reason it out, and came up with the exact same intuition. You need a sequence of 2n moves (n down moves, n over moves), but the sequence is completely determined by which moves are down (the others must be over). So it's 2n (moves) choose n (over).

mbowcut2

先月議論

Totally agree. Granting exemptions feels like trying to have their cake and eat it too. If regulations mean anything they need to be enforced so we can see the real downstream effects.

mbowcut2

4 か月前議論

Gotta hit that docker system prune -a

mbowcut2

5 か月前議論

Loved him in Secondhand Lions.

mbowcut2

6 か月前議論

If you thought we were getting bad bugs before, just wait until the 90% agent-coded PRs start landing. We're gonna have multiple crowdstrike-level blowups.

mbowcut2

6 か月前議論

It's an interesting concept, but I'm skeptical about how feasible this is. How much design/legwork/intervention will Seth actually contribute during the entire process? I'm thinking "growing corn" might be a little hard for a proof of concept, specifically because the time horizon is quite long. Something a little more short term like: contracting a landscaping job. The model comes up with design ideas, contacts landscapers, gets bids, accepts a bid. Seth could tell the model that he's it's agent, available to sign for things, walk people through the property, etc, but will make no decisions, and is only reachable by email or text.

mbowcut2

6 か月前議論

Wow, I didn't know about the "skills" feature, but with that as context isn't this attack strategy obvious? Running an unverified skill in Cowork is akin to running unverified code on your machine. The next super-genius attack vector will be something like: Claude Cowork deletes sytem32 when you give it root access and run the skill "brick_my_machine" /s.

mbowcut2

7 か月前議論

It makes me wonder about the gaps in evaluating LLMs by benchmarks. There almost certainly is overfitting happening which could degrade other use cases. "In practice" evaluation is what inspired the Chatbot Arena right? But then people realized that Chatbot arena over-prioritizes formatting, and maybe sycophancy(?). Makes you wonder what the best evaluation would be. We probably need lots more task-specific models. That's seemed to be fruitful for improved coding.

mbowcut2

9 か月前議論

Seems like the less sexy headline is just something about the sample size needed for LLM fact encoding That's honestly a more interesting angle to me: How many instances of data X needs to be in the training data for the LLM to properly encode it? Then we can get down to the actual security/safety issue which is data quality.

mbowcut2

10 か月前議論

I'm not surprised. People really thought the models just kept getting better and better?

mbowcut2

11 か月前議論

it looks like the 2nd and 3rd bar never got updated from the dummy data placeholders lol.

mbowcut2

11 か月前議論

It's not a new problem (for individuals), though perhaps at an unprecedented scale (so, maybe a new problem for civilization). I'm sure there were black smiths that felt they had lost their meaning when they were replaced by industrial manufacturing.

コメント