chriskanan

This is actually wrong. A large fraction of people do not have internal monologues. Not at a computer or I would dig up cognitive science and psychology papers, but language evolved as a means of communication not a means of thought. The vast majority of human thoughts are not verbalized. I have a strong internal monologue, too. I was surprised to learn that a non-trivial number of people do not have one.

I really hate this open weight but closed science approach. These companies just take from academics and all the Chinese companies that are doing good science, but without understanding the recipe it makes it hard to know where the failure points will be until your agent accidentally commits a crime.

Mistral doesn't publish the science.

You are conflating multiple things.

1) First, you are talking about positive forward transfer in continual learning. I've been giving talks for the past 6-7 years about how that community (I was one of the founders) went astray and wasn't focusing enough on that topic, but continual learning of the kind you are thinking isn't in any of these systems right now. I think some people left the Grok team to make a start-up to focus on that. By forward transfer, what I mean is weights update over time and past learning improves future learning such that we get better sample efficiency.

2) Psychologists distinguish among different kinds of intelligence for Spearman's g (IQ). Crystalized intelligence is using already acquired knowledge (frontier models probably have maxed out that). Fluid intelligence is reasoning and finding solutions in novel situations or without the necessary crystalized knowledge. [Giving colloquial definitions]

3) Now, interestingly, neither of those are correlated with _creativity_ (just they are independent, note some have this threshold theory but it hasn't held up in recent papers). That's what the AI's really are terrible at -- creativity. But I'd argue the vast majority of humans aren't very creative, with truly out-of-the-box ideas. Given that this is HN, and a non-trivial number of us have ADHD, creativity is positively correlated with ADHD.

I did a bunch of research on these topics for my AGI course that I teach each Spring (where I then point out conflicting definitions and start using multiple alternative terms rather than AGI to distinguish among the different definitions).

I'm an AI professor, and the same thing happened to me. I had written out contracts and specs for some novel algorithms to compare. And instead it created a new sandboxed environment with 20k lines of code to ensure we do gold standard science.... didn't implement the algorithms at all. In another case, I left it overnight with a plan, and it decided to write a 50k line new overly engineered plan. Suffice to say, I don't use any frontier models for doing coding work anymore. I use them to make detailed plans and use good worker AIs for execution, which don't overthink everything.

Same thing happened with eggs in the USA with bird flu used as an excuse.

And all those reports of Claude when asked without a system prompt what its name was in Chinese it often would say Qwen or Deepseek, etc. I'd love Anthropic to say they aren't distilling and taking from every model out there, because I'm sure they are. As my mom would say, "the pot calling the kettle black." At least Alibaba and other Chinese companies are giving back to the AI community with detailed scientific papers on how their systems work and releasing open-weight or opensource models. I believe Anthropic has released nothing, and given that they had originally configured Fable to sabotage ML related work because only they can be trusted to do it safely, is just anti-science and anti-aligned with what I would consider good human values. They are way too sanctimonious and I don't trust them at all.

They are doing ta tremendous amount of novel research where American AI companies have "war rooms" to study their papers and models and American labs publish next to nothing. They have to often do more with less. As an AI researcher, Chinese labs are doing tremendous benefit to science whereas some American companies (and I'm American) seem to think only they are able to do AI research responsibility (I've been working on neural networks for 25+ years). I'm pretty sure Fable sabotaged my research codebase (see the news stories about this).

Did you ever watch Star Trek: The Next Generation? The current trajectory is like the Ship's Computer. It know everything humanity has learned and can do a lot. But it can't explore and lacks desires and agency. That's why they made a big deal about the character Data being an entirely new kind of AI. Of course Star Trek has a very different economic system and there is a book called Trekenomics about that. So optimistically people live for themselves and don't persue labor they despise. Half of Americans hate their jobs and live for the dream of retirement when they get to actually do what they want.... But they don't have the same energy anymore.

Jobs are an invention of humanity. About 50% of people dislike their job. People spend much of their lives working. Poverty and inequality are a choice made by society if society chooses poorly.

Slightly more nuanced in that the reciprocal reviewer may have been essentially forced to sign despite having other commitments or may not have even been the lead contributor. Nowadays if a student submits a side project to a top-tier conference then it is required that if any authors have significant publication count in top-tier venues, then one must be a mandatory reviewer. Then one must sign that agreement. Students need to publish, much less so for me, where I really want to publish big innovations rather than increments, but now I get all these mandatory reviewer emails demanding I review for a conference because a student has my name on the paper and I'm the most senior, but I may have just seeded the idea or helped them in significant ways. However, many times those are not my passion projects and is just something a student did that I helped with, but now all AI conferences are demanding I review or hurt a student, where I'm the middle author.

But if anything, I think the whole anti-LLM review philosophy is wrong. If anything we need multiple deep background and research analyses of papers. So many papers are trash or are publishing what has already been done or are missing things. The volume of AI papers makes it impossible for a human alone to really critique work because hundreds of new papers come out a day.

I had lunch with Yann last August, about a week after Alex Wang became his "boss." I asked him how he felt about that, and at the time he told me he would give it a month or two and see how it goes, and then figure out if he should stay or find employment elsewhere. I told him he ought to just create his own company if he decides to leave Meta to chase his own dream, rather than work on the dream's of others.

That said, while I 100% agree with him that LLM's won't lead to human-like intelligence (I think AGI is now an overloaded term, but Yann uses it in its original definition), I'm not fully on board with his world model strategy as the path forward.

I can see some promise with diffusion LLMs, but getting them comparable to the frontier is going to require a ton of work and these closed source solutions probably won't really invigorate the field to find breakthroughs. It is too bad that they are following the path of OpenAI with closed models without details as far as I can tell.