meowface

If we assume LLMs will continue to advance at a pretty rapid pace (relative to the current rate of advancement; so, same or faster), all these numbers look good to me.

Some people just start out with wanting LLMs/AI/Anthropic to fail or be scams and consistently try to fit any new evidence pegs into those unchanging hypothesis-shaped holes. This group ideologically despised LLMs from the start and needs them to be fake.

I think it is probably going to happen with LLMs, and I'd bet on it.

As said: 1 - 2 years, not current ones.

Yes, but I said 1 - 2 years, not current LLMs.

I would guess in a matter of 1 - 2 years, a random amateur vibe coding a brand new DB will get much better reliability and correctness guarantees than whatever this is. This is just pure laziness.

I'm sure they do. Just not necessarily for Turnstile.

I don't trust Facebook or Zuckerberg, but I also don't really care about my own personal privacy from large corporations. I will use whatever is best/cheapest, generally. And I say this as someone who hates advertising and adtech.

They're wrong. They're right about it being cope, but the cope is not from people in fear.

The people who feel fear about AI taking their jobs or doing worse things are not coping. They're saying all this is real and impressive and that that is why they are terrified.

The people saying it's bad and lies and they stole the answer and a million other things are just in tribal mode throwing whatever at the wall to defer to the pre-existing conclusion that AI is a corporate hoax. AI would have to be real to fear it in this professional and existential way, but they know it's fake, so they're not afraid.

It's sometimes done with more subtlety, like "it just comes up with some proofs by connecting existing things, it is not producing new insights, it's not creative or truly generating ideas". Which may be partly true. The denialism is shifted into refusing to acknowledge that within 20, or 2, years it probably will be producing new insights.

The reality is both are true. The code artifact on the disk and the idea object in the brain should both be treated as contingent, relative, and incomplete, and unvertain.

Prolonged conversations with humans and AIs about both ideas and code is very useful.

Good post. I like this example:

>Say you want to draw a perfect picture of an owl. You have this beautiful image of it in your mind. But you can’t draw very well, and in this analogy the drawing is the code. So what comes out is a stick-figure owl that’s barely recognizable as an owl.

>In the code-is-the-source-of-truth version, that stick figure is now the authoritative artifact. We analyze it, document it, take notes on its proportions, and spend a whole bunch of time iterating on it. We’re running in circles around a bad drawing.

My only disagreement with the post is over whether articulating is is the main bottleneck. Right now, there are still issues and oversights humans would tend not to make even if you have model context and documentation accurately and clearly capturing your full intent.

Each year will decrease the rate of this, but software engineering will probably need until maybe 2030 until we've crossed a threshold towards solely being product managers/designers. This advice still applies today, but you do need more wrangling on top.

Thiel, unlike many of these other figures, is genuinely insightful. He also has one of the best investment track records. And he knew to back Trump in 2016, not back him in 2020, back him in 2024. He's one of the rare "right-wing intellectuals" who's a genuine intellectual.

The core issue with him, in my view, is his openly anti-democratic views.

He identifies as a libertarian, yet finds democracy loathsome and either wants a monarch or finds it strategically useful to fund and support initiatives that increase the chance of there being increasingly monarchical leaders in places like the US. I don't think that is a moral ideology, and I also think it is generally not a good one for achieving positive outcomes for a majority of people.

There are genuine critiques of democracy and its tendency towards shallow populism ruling everything, but, as usual, the meme defense is the correct defense; it's better than alternatives, like permanent "rule by 'CEO-monarch'".

I bite the bullet on this one by saying we should in fact do something about that. All of it. And we will, when we can. Probably before 2400.

It should be a tiered system, IMO.

1) Where possible, don't test in animals.

2) When testing in animals, first ensure that there is reasonable confidence the risk and severity of harm from the testing will be minimal. Only begin initial in vivo testing after this has first been achieved.

3) For test animals that are or aren't harmed, allow them to live happy, (relatively) normal, natural lives. Don't end their life early unnecessarily, with exceptions for humane euthanasia if the testing has unexpectedly caused significant, persistent suffering. Treat them as a pet owner would treat their beloved pet rat.

Some may consider it extreme, but, in my view, in an ideal world, people would treat testing in animals almost like testing in humans. The researcher should first ask "would I feel comfortable testing this in a voluntary human test subject?" Non-human animals would still be the first line of testing, since harm/death in a rat/mouse/chimpanzee is less morally bad than in a human, but I think this should be the mindset.

Hmm, but is it not the case a much larger model could potentially reason more in latent space, depending on how it's set up?

I thought a looped transformer is in fact reasoning more in latent space, though "reasoning" in a somewhat different way from the standard reasoning token approach.