comeonbro

As a record of how likely people considered this outcome:

Prevost was hovering around 1% on Polymarket, and was <0.5% between white smoke and announcement.

This is not truly solvable. There is an extremely strong outer loop of optimization operating here: we want it.

We will use models that make us feel good over models that don't make us feel good.

This one was a little too ham-fisted (at least, for the sensibilities of people in our media bubble; though I suspect there is also an enormous mass of people for whom it was not), so they turned it down a bit. Later iterations will be subtler, and better at picking up the exact level and type of sycophancy that makes whoever it's talking to unsuspiciously feel good (feel right, feel smart, feel understood, etc).

It'll eventually disappear, to you, as it's dialed in, to you.

This may be the medium-term fate of both LLMs and humans, only resolved when the humans wither away.

Here is probably the most well-known instance of Pre-Musk Twitter removing blue checks from the accounts of public figures for reasons other than the account not being who it claims to be:

https://techcrunch.com/2017/11/15/twitter-removes-verified-c...

Not pictured: innumerable other accounts which were never granted a blue check in the first place, despite being the easily verifiable real accounts of journalists and public figures.

It was de facto a caste system of political favor and connections.

You seem to have somehow missed one of the most significant advancements in human history suddenly exploding out of the pages of science fiction and fundamentally altering our existence forever. Minor oversight.

"Nobody goes there nowadays, it's too crowded"

If I understand you correctly, what you're claiming is:

University 1 gets $100. $10 of it goes to admin, $90 to researcher. Researcher spends $60 on supplies and equipment. This is accounted for as 10% administrative overhead.

University 2 gets $100. $20 of it goes to admin, $40 to researcher, $40 to supplies and equipment. This is accounted for as 60% administrative overhead.

Is this an accurate characterization of your claim?

It's not a technical challenge in this case, it's a technical tradeoff. You could train an LLM with single characters as the atomic unit and it would be able to count the 'r's in 'strawberry' no problem. The tradeoff is that then processing the word 'strawberry' would then be 10 sequential steps, 10 complete runs through the entire LLM, where one has to finish before you can start the next one.

Instead, they're almost always trained with (what we see as, but they literally do not) multi-character tokens as the atomic unit, so 'strawberry' is spelled 'Ⰹ⧏⏃'. Processing that is only 3 sequential steps, only 3 complete runs through the entire LLM. But it needs to encounter enough relevant text in training to be able to figure out that 'Ⰹ' somehow has 1 'r' in it, '⧏' has 0 'r's, and '⏃' has 2 'r's, which really not a lot of text demonstrates, to be able to count the 'r's in 'Ⰹ⧏⏃ correctly.

The tradeoff in this is everything being 3-5x slower and more expensive (but you can count the 'r's in 'strawberry'), vs, basically only, being bad at character-level tasks like counting letters in words.

Easy choice, but leads to this stupid misundertanding being absolutely everywhere and just by itself doing an enormous amount of damage to peoples' ability to understand what is happening and about to happen.

Imagine if I asked you how many '⊚'s are in 'Ⰹ⧏⏃'? (the answer is 3, because there is 1 ⊚ in Ⰹ and 2 ⊚s in ⏃)

Much harder question than if I asked you how many '⟕'s are in 'Ⓕ⟕⥒⟲⾵⟕⟕⢼' (the answer is 3, because there are 3 ⟕s there)

You'd need to read through like 100,000x more random internet text to infer that there is 1 ⊚ in Ⰹ and 2 ⊚s in ⏃ (when this is not something that people ever explicitly talk about), than you would need to to figure out that there are 3 ⟕s when 3 ⟕s appear, or to figure out from context clues that Ⰹ⧏⏃s are red and edible.

The former is how tokenization makes 'strawberry' look to LLMs: https://i.imgur.com/IggjwEK.png

It's a consequence of an engineering tradeoff, not a demonstration of a fundamental limitation.

Gary Marcus has made himself the most prominent proponent of "deep learning is a parlor trick and cannot create real AI" (note: deep learning, not just LLMs), which he has been saying almost unmodified from before LLMs even existed to now.

Though I think he might have stopped setting specific concrete goalposts to move, sometime between when I last checked in on him and now. After (often almost instantly) losing a couple dozen consecutive rounds of "LLMs/deep learning fundamentally cannot/will never", while never acknowledging any of it.

> I've tested all of ours on each of the main models

Could you list them? I've noticed even quite techy people seem to be critically behind on what has happened in the last few months.

Kind of, Deep Research is o3, which is what I meant by "(in an unusual and less directly-usable-for-that form)"

Of course "o3 hasn't even really been released yet" only strengthens the point.

1. o1 was only released to the public 2 months ago. o3 was only released to the public (in an unusual and less directly-usable-for-that form) 2 weeks ago.

The subset of people who might do that and are paying sufficient attention to this are still reeling, and are mostly otherwise occupied.

2. A lily pad is growing in a pond and it doubles in size every day. After 30 days it covers the entire pond. On what day does it cover half the pond? https://i.imgur.com/grNJAZO.jpeg

Models tested: o1, 4o (August 2024 version), 3.5 Sonnet (June 2024 version)

Notably missing: o3

Consult this graph and extrapolate: https://i.imgur.com/EOKhZpL.png

This article is about things which aren't limitations anymore!

You are applauding it as pushback for pushback's sake, but it's an article about limitations in biplane construction, published after we'd already landed on the moon.

> Chatbot Software Begins to Face Fundamental Limitations

> Recent results show that large language models struggle with compositional tasks, suggesting a hard limit to their abilities.

Your first question with anything like this should always be WHICH MODELS:

> For our experiments, we evaluate the performance of 6 LLMs: GPT4 (gpt-4) [58], ChatGPT (GPT3.5-turbo) [57], GPT3 (text-davinci-003) [11], FlanT5 [17] and LLaMa [75].

This is ancient. This research was done centuries ago. This is research about the possibility of isotopes, written about radium in 1903, published in 1946. It is a criminal level of journalistic malpractice to leave uninformed readers with the impression that this is where AI stands yesterday.

Wow. I thought I remembered something like that but I thought it sounded too extreme and wouldn't be easily supportable, so I left it out of my other comment. So this test:

1) was designed to statistically select for members of favored identity groups and against members of disfavored identity groups, and not in any way to measure ATC job aptitude, resulting in highly-scored questions like "The high school subject in which I received my lowest grades was" where the only correct answer was "Science", and failing the test disqualified you permanently

and

2) current FAA employees distributed the exact answer key to outside racial identity organizations to give to their members

You are conflating multiple different instances of current FAA employees providing outside racial identity groups with both hard and soft answer keys, the buzzword filter was just the first stage.

Later and probably most egregiously, there was a completely nonsensical and arbitrary biographical questionnaire which was scored like:

https://storage.courtlistener.com/recap/gov.uscourts.dcd.182...

    15. The high school subject in which I received my lowest grades was:
    A. SCIENCE (+15)
    B. MATH (0)
    C. ENGLISH (0)
    D. HISTORY/SOCIAL SCIENCES (0)
    E. PHYSICAL EDUCATION (0)

    16. Of the following, the college subject in which I received my lowest grades was:
    A. SCIENCE (0)
    B. MATH (0)
    C. ENGLISH (0)
    D. HISTORY/POLITICAL SCIENCE (+15)
    E. DID NOT ATTEND COLLEGE (0)

    29. My peers would probably say that having someone criticize my performance (i.e. point out a mistake) bothers me:
    A. MUCH LESS THAN MOST (+8)
    B. SOMEWHAT LESS THAN MOST (+4)
    C. ABOUT THE SAME AS MOST (+8)
    D. SOMEWHAT MORE THAN MOST (0)
    E. MUCH MORE THAN MOST (+10)

where current FAA employees, again, distributed the exact answer key to outside racial identity groups to give to their members.

I'm sure this is multifactorial and the other factors are probably as or more important, but especially if you are familiar with the very egregious specifics of the FAA diversity hiring scandal (https://www.tracingwoodgrains.com/p/the-faas-hiring-scandal-...), "is unsupportable" here is a strong claim that is playing the classic and well-worn role that "there's no evidence" often does in bad journalism: https://www.astralcodexten.com/p/the-phrase-no-evidence-is-a...

You already know.

https://generalstrikeus.com/aboutus

> What are your demands?

> Our broad list of demands includes, but is not limited to: Climate action. Universal healthcare. Racial justice. Reproductive rights. LGBTQIA+ rights. Living wage / raise the minimum wage. Immigration reform. Education reform. Gun safety. Tax the rich. Affordable housing. Disability rights. Welfare and child support reform. Voters rights. Constitutional convention. Paid family and medical leave. Criminal justice system reform. Workers’ rights. Permanent ceasefire in Gaza.

> Specific demands will come from leaders and experts of existing fights for racial, economic, gender and environmental justice.

Insane cope. Emily Bender and Gary Marcus still trying to push "stochastic parrot", the day after o1 causes what was one of the last remaining credible LLM reasoning skeptics (Chollet) to admit defeat.

AI will account for 99% of global energy consumption. Solve for equilibrium.

o1 can already do your job. Have you tried it?

> Nobody thinks GPT4-o1 or Sonnet 3.5 is going to change the world.

I do. AI progress could magically hit a brick wall right now and never advance any further, and o1 would still change the world more drastically than you can imagine. But AI progress will also not magically hit a brick wall.

I supposed for that reason o1 specifically will not change the world, because it will be superceded too soon to. But it would if it wasn't.

Canadian "all-purpose" flour has a higher gluten content than American "all-purpose" flour. It's closer to American "bread flour".

That's aside from whatever harder-to-measure taste differences it might have, but it makes a big difference by itself.

No, the Supreme Court wants laws to have to be made by Congress rather than the unelected bureaucracy.

Havel's Greengrocer:

https://en.wikipedia.org/wiki/The_Power_of_the_Powerless#Hav...

Don't even bring that movie into this discussion, it's a historical atrocity.

Only option is "SignUp Or Login with Google": no.

Yeah, I was surprised by that for the top recommendation on every "beginners linux" search.

The front page is a soup of meaningless babble. The installation guide is in programmers documentation style and split over 15 pages.