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My read is that they're criticizing moving the reasoning (more) into the latent space, such that not even researchers/safety-evaluators can actually see what's going on.

Of course this still then has a 'trust me, bro' feel to it, but making it outright impossible to reasonably inspect the CoT is a significantly larger and riskier step, IMO.

Apart from getting 16 sq. km of solar arrays and radiators into orbit - and without jumping to conclusions about whether this is a borderline scam - I can imagine 2 obvious showstoppers:

1) Space debris. This is proposal is several orders of magnitude larger than the biggest things in near-Earth orbits. Thus equally many orders more likely to be hit by, and create, space debris

2) Heat transport - this isn't my home turf, but I can't imagine building something lightweight enough to be launched, yet also capable of transferring enough heat away from the 5 GW core, without it melting/breaking

It's been a while since I read their whitepaper, but I don't recall either of those points being addressed.

... what tf?

On top of studying engineering at uni, his "side-gig" is being creative, empathetic, and fantastic at communication - and your prime recommendation is to "hire" him to be a specialist hidden away in the back office? Which interwebz forum are you on?

EDIT: My last question is clearly an echo-chamber statement. But that doesn't subtract from the fact that, yeah, should he found a business, yes, he'll deal with certain "BS". That is the weight we'll all carry. But he's quite likely capable of moving civilization forwards, so... :shrug:

That's quite the statement. What makes you so certain that we won't have AGI within 30-60 years?

Because "AI" is a well-established academic field, and the definition by your quoted comment is in line with this.

It's a very broad umbrella term, machine (and deep) learning are only subsets - although the main drivers these days.

Glad you found it useful.

A small caveat, though: The correlation is linear with the logarithm of compute. So here's hoping Moore's law & friends live on a tad longer!

And a somewhat unrelated fun fact: The authors surprisingly found the lowest correlation between compute and the performance in the domain of Go (and not the real world). Although the data is very sparse, I suspect that it's due to algorithmic advances.

Small correction:

Net income: 0.524 bb

So 19.6% profit margin. Still nice.

Taking GP's point to less of an extreme: Are all humans always right in everything that they state?

Yeah, nah, I beg to differ: Just because the broader population might not (yet!) have an intuitive understanding of the field, and its shortcomings, I don't think we should rename decades of academic consensus. I have more faith in entire fields of research, at least.

I can't make up a good counterexample, so here's a so-so one: Fusion vs. fission power.

I've extremely rarely encountered the term "fission" outside of talks about fission power. Yet, I don't think we should call Fusion Power "Star-like energy generation" and Fission Power "never practically encountered power generation, but somewhat like star-like, except the opposite underlying mechanism"

I don't think anybody serious in the machine learning community has any delusion as to when a model says "A" with "99% confidence", that actually truly means that the model is fundamentally outputting "A" correctly 99% of the time.

Robustness and interpretation of machine- & deep learning models is a quite active field of research.

I don't know if I'm asking for too much, but maybe it's a question of educating people on these tools? I mean, even though most people aren't electricians, nor probably have a good intuition about how electricity works, we wouldn't touch a live wire

Sure, or you know... Rather than ranting on twitter, one could look up "Large Language Model" (LLM), "Deep Learning", "Machine Learning" as well as "Artificial Intelligence" on Wikipedia, and realize that historically the following has been the norm in terminology for decades:

Artificial Intelligence > Machine Learning > Deep Learning > LLMs

I.e. LLMs are indeed a subset of what is classically considered Artificial Intelligence. Just as well as route planning in Google Maps or getting beat by a non-machine-learning chess algorithm.

EDIT: Regarding "for decades" doesn't apply to LLMs, of course :-) and barely to deep learning. But for the time they've been around, this inequality holds

Except you don't have astronauts going to the vast majority of the 1000s of satellites orbiting the planet.

So apart from the 1-2 active space stations, where people go without having to do a full $100 million launch, I'd say laser transmission is a pretty good option for transferring data