ALittleLight

The big difference is that Altman et al aren't just, or even mainly, pundits or prognosticators. Zitron's whole thing is commentary and predictions about AI and his predictions are almost all wrong.

Altman and friends are mainly actually making and delivering AI. If they also hype their timelines/valuations, they also seem to make directional progress on the goals.

Surely this is realistic now (or soon) in the form of LLM curation. A few auto-librarians reading everything, looking at different versions side by side, making choices, etc.

"AI, please cure cancer."

"Okay, all humans dead, technically a 100% cure."

I hate not being able to use the latest models. There needs to be a much faster resolution to whatever is happening with the federal government.

Hmm. I also recently got a subscription to the NYT. I noticed they sent me a lot of email so I just filtered it with the click of a couple buttons. It's obnoxious but in the minor way that having to click a couple buttons one time is.

The paper says the professors have a median of 200 comparisons each. It also says they only used 2 models because using more models would require more comparisons and they selected Google models because Google was branded/advertised as being education focused. When you see other models show up elsewhere, that's because they extended the main idea to other models but using LLMs to judge instead of human professors.

I don't understand the "deathbed" perspective. Are you going to wish you made more hackernews comments on your deathbed? Probably not. Does this mean you should stop using hackernews?

If you optimized for minimizing deathbed regret perhaps you'd regret that on your deathbed!

If I have cogent thoughts on my deathbed I expect they'll be along the lines of "I wish I wasn't dying" and not regretting the many ways I enjoyed my time on Earth (which includes vibe coding apps nobody uses).

This just says 60% of systems, but not the frequency for those systems. They were evaluating 20 systems, so for 12 systems there were mistakes in the prescriptions, but there isn't information about how common those mistakes were and it's hard to judge relative to a human system.

Now that there is proof of communication while dreaming, it is only a matter of time before someone manages to vibe code while sleeping.

Think of it as paying for tokens. The tokens you could buy 3 years ago are better and two orders of magnitude cheaper today. If that happens again over the next 3 years then the tokens you can buy today to do a job for 20k will cost 200.

This isn't optimistic in my opinion. It's not even fully realistic because Gemma 4, which you can run on local hardware, is even better and another few orders of magnitude cheaper. A 20k job today might a few dollars in a few years.

3 years ago the best model was DaVinci. It cost 3 cents per 1k tokens (in and out the same price). Today, GPT-5.4 Nano is much better than DaVinci was and it costs 0.02 cents in and .125 cents out per 1k tokens.

In other words, a significantly better model is also 1-2 orders of magnitude cheaper. You can cut it in half by doing batch. You could cut it another order of magnitude by running something like Gemma 4 on cloud hardware, or even more on local hardware.

If this trend continues another 3 years, what costs 20k today might cost $100.

For what reason would they attack a single school? Some strikes being well some doesn't mean others can't be mistaken.

Now, I guess. They aren't releasing this one generally. I assume they are using it internally.

The difference is you can appeal or ignore a game result. If Ukraine lost a strategy game tournament, would they give up their territory? Or fight to hold it still?

Europe is currently being invaded by Russia and your idea for a "hardliner" course is to start sending Russia money?