> As for the Fermi's Paradox, I think the Occam's answer is Adam's Observation: "space is big. Really, really big..."

Right, and and given a failure to find the evidence we're looking for in a given neighborhood (~50 light year radius perhaps - SETI 50 years old), there are multiple ways to interpret this, including:

1) There is a) no life where we've been looking, and so b) we assume (why??) there is none in the almost infinitely bigger entire universe

2) There may be tons of life in this radius, just no advanced life

3) It seems more logical to assume that alien life does exist than not exist, so use this data to estimate an upper bound on how common it is

etc

We exist and have only been transmitting radio shows into space for 100 years or so, so put the shoe on the other foot and imagine an alien species in our own galaxy looking for life and not finding it. The Milky Way is 100,000 light years in diameter, and our measly "we're here" beacon has only spread out 100 years. Even if they are our neighbors only 50 light years away, are they looking for an ultra faint radio signal in Earths FM radio band ?!

It has apparently only fairly recently dawned on SETI researchers, or at least they are only starting to take it seriously, that maybe we are looking for the wrong signal in the wrong place.

The most scientific guess would have to be that primitive life - replicating metabolic soups - exists pretty much anywhere with the right conditions (it's just chemistry - why wouldn't it?!) - must be very common even within our own galaxy, even if it depends on a bit of luck (meteors hits delivering key elements). Complex multi-cellular life may be much rarer (on earth primitive life appears almost immediately, multi-cellular takes another 2B years), and complex life evolving human-level intelligence much rarer still (basically didn't exist for all of earth's 4.5B yr existence until "yesterday").

But, yeah, the visible universe is big enough, maybe ~1T galaxies, and then there is the non-visible universe beyond which is unimaginably bigger (maybe 10^20 times as big, at minimum).

This isn't what the article is saying.

LUCA (the single common source of all modern life) already had RNA/DNA.

The article is talking about LACA and LBCA - the archaea and bacteria lineages that both evolved from LUCA.

What the article says is the LUCA had an "incomplete" (partly still external) metabolism, and LACA and LBAC each completed it in their own way.

I don't know if the Chinchilla scaling law (which is what I assume you are referring to) includes RL-based post-training, or even non-text input tokens for that matter?

The base model certainly makes a difference, but for areas like math, coding and hacking (to compete with and counter Mythos) the power of the end model mostly comes from the RLVR post-training, and these are all areas where they can generate synthetic data, as well as pay for human-generated data if they care/need to.

So much for the US attempt to starve China of compute! We've now already got ~3T open weight models from both Moonshot (Kimi 3) and Alibaba (Qwen 3.8), and now apparently another 10T one here from ByteDance.

> If this is accurate, this suggests that abiogenesis is easy once one has a stable, watery environment

It obviously takes a bit more than that, but it's probably fair to say that simple life is inevitable when all the necessary pre-conditions are there. Chemistry is going to happen.

The necessary pre-condiitons do include things like an energy source, maybe more than just sunlight, certain rarer chemicals such as phosphorus that earth acquired via asteroid/meterorite impacts. For complex life a metallic core and magnetosphere to protect you from ionizing radiation may be necessary.

This summary of "life evolved twice" is just click-bait.

The article it is referring to has the much more sober title of "Intermediate stages in the origin of metabolism at a
phosphorylating hydrothermal vent".

This doesn't change the understanding of LUCA as a single last universal common ancestor cell that gave rise to LACA (last archea common ancestor) and LBCA (last bacteria common ancestor).

What the article is saying is that the metabolism of LUCA was "incomplete" and not yet self-contained, still relying on external catalysts and reactions. LUCA then branched off into LACA and LBCA which evolved (completed) their own differing metabolisms.

Obviously it's a bit arbitrary how exactly you define life - where do you choose to say that complex chemistry is "alive" due to being able to self-replicate etc. Maybe better to regard the origin of life as a gradual process of environmental metabolic soup complexification and eventual encapsulation in the form of protocells and cells. By the time you get to LUCA, a cell with RNA and DNA, it seems this is already well past the point of any fuzzy chemisry-life distinction. LACA and LBCA don't represent "life evolving twice" - they are just early evolutionary steps giving rise to the distinct archea and bacteria branches of life.

> You likely replicated the sort of calculation they did. Demonstrated how to get oneself into trouble.

Yes, that was the entire point of my post, to give a specific example of what these LLMs are saying!

Not sure what you mean by that ?

I was just confirming the abysmal advice that AI, even something well regarded such as Sonnet 5, is dishing out.

Of course the teens would have been better off consulting a specialized hiking app and not AI, but there again adults have been following Google Maps and GPS directions and driving into lakes, so not so surprising.

The "add 30 mins" if you are doing it hopping one one leg is, well, interesting ...

Here is Sonnet 5's rather bad take on it:

> what would be a respectable time to walk 18 miles?

For an 18-mile walk, times generally break down like this:

        Casual/relaxed pace (~20 min/mile, 3 mph): around 6 hours
        Average brisk pace (~15â"17 min/mile, 3.5â"4 mph): around 4.5â"5 hours
        Fast/fit pace (~13â"14 min/mile, 4.3â"4.5 mph): around 4â"4.2 hours
        Competitive race-walking pace: could dip toward 3â"3.5 hours, but that's serious effort

For most reasonably fit people doing this as a single long walk (not a race), finishing in around 5 hours, including a few short breaks, would be a solid, respectable result. If you're doing it on hilly terrain, in heat, or with a loaded pack, add 30â"60+ minutes.

***

So .. 18 miles on the flat - nice brisk 5 hour walk.

Doing it on hilly terrain, with a loaded pack, on a hot day ... add 30 min.

Hmmm ...

FWIW, he (and his fund) haven't lost everything. After this recent rout, his fund is still up 80% for far this year (before this huge drop it had been up 400%).

No doubt his risk management is going to be better going forwards. It'll be interesting to see how he does going forwards - his bets to date seem to have consisted of going all-in on everything related to datacenter growth, which was pretty obvious at least as a short term bet. Let's see if he can predict the effect of AI on the economy and continue to do well.

True, but there were (and still are) at least two reasons for investors to stick with SALP and Aschenbrenner.

1) He is extremely well connected in SV. He's ex-OpenAI, and shares a house with Sholto Douglas (high level Anthropic employee), Dylan Palel (of Semi Analysis - who are essentially doing the research that SALP, and others, are investing on), and Dwarkesh Patel.

2) Despite this setback, he has still made tons of money for his investors, even this year, and may well continue to do so. Many high profile investors such as George Soros have also made large strategic bets that lost tons of money, but still recovered from it. Aschenbrenner has no doubt learned a painful lesson in risk management and use of leverage.

Even after this 67% drop, SALP is still up 80% so far this year, having been up over 400% earlier. I'm sure many investors are sticking with him.

How about rather than trying to be a smart ass, or the president trying to blame a Democratic governor for an Iranian state-sponsored attack, the president actually does his job?

Is that too much to ask?

Ask like a president - be a leader, not a whiner. Take charge. Tell your cyber-Tsar to have a meeting with the state governors, or appropriate representatives, and get appropriate protection measures in place for all critical infrastructure (not just water treatment plants).

Yeah, it's not rocket science, unless you are a complete fucking idiot.

But it doesn't line up.

There is an old paper (by Bernard Barrs) "In the Theatre of Consciousness" that likens the mind full of ideas to a theater's stage, with consciousness being the spotlight that illuminates some ideas, leaving others dark. This theory of consciousness refers to itself as "Global Workspace Theory".

All Anthropic have done here is choose to call the middle layers of a Transformer a "Global Workspace" (may as well have called it a "Pink Wombat") and say "wow, look, we've got a workspace too, so it may be conscious".

The spotlight of Barr's theory is the bit corresponding to consciousness, so does a Transformer have anything that can be called a "Spotlight" to try to make some analogy here? No.

Necessarily a transformer has many language patterns/predictions internally that aren't in the output it generates, since it is trained to predict all possible continuations of the input and therefore predicts a bunch of alternate next tokens, from which the framework calling the model picks one AT RANDOM.

So Baar's workspace/theatre of ideas has consciousness shining a spotlight on one idea, and a Transformer has a freakin' random number generator picking one.

Do you consider that "lining up"?

It'd be like saying that a banana and a car are similar because you can call a banana skin a "car body", and ignore the fact that the banana has no engine and can't move.

Nah - completely wrong.

Find a model that does this, and ask it to SPELL strawberry instead, and I'll guarantee it will get it right.

The problems some models have (esp. if you don't allow them to think out loud) is COUNTING, not "mapping tokens to letters".

The reason they don't have a problem doing this mapping is because to them it's not mapping - it's prediction, which is the one thing they have been trained to do. They are predicting that the input "how do you spell strawberry?" will be followed by 'S', 'T' ,etc. It makes no difference to them that "strawberry" may be 6 tokens - it's just one sequence of tokens predicting another sequence of tokens. It is what they are trained to do.

> neural networks are definitely doing something

No shit, Sherlock !

And what language models have been trained to do is find language patterns that help predict next token.

Anthropic : Holy fuck! This thing is finding language patterns that help predict next token! It's alive! It's worth a bajillion dollars!

Yes, although Baars' "Global Workspace Theory" (pertaining to the human brain and consciousness) is really irrelevant here. Anthropic only refer to it because they want, as usual, to make grandiose claims and want you to believe that LLMs may be conscious (while of course not being willing to commit to an actual definition of consciousness).

Of course Baar's theater (not ocean) metapor is central to his theory of consciousness which he compares to a spotlight in a theater drawing attention to some players on stage while ignoring others.

OK, so if you strip away Anthropic's poorly applied comparison to Baars' GWT, and appeal to you to believe that LLMs may be conscious, then what are we left with? What is the actual technical content of their blog post (which the Slashdot story doesn't even bother to link)?

https://transformer-circuits.p...

Their title "Verbalizable Representations Form a Global Workspace in Language Models" cuts to the heart of it.

The "Workspace" that Anthropic are referring to (fig 2) is just the the activations of the middle layers of a Transformer which is where most of the high level pattern recognition and prediction occurs (since the input/output layers need to convert word sequences to/from these richer middle layer embeddings).

OK, so why call it a GLOBAL workspace (which is central to their grandiose brain analogy)? A: Because the diagram of a Transformer you are likely familiar with puts all the focus on the stacked Transformer blocks with their attention and feed-forward components, and presents the residual connections as more of a technicality (maybe you think of these as just to help gradiant
propagation as in a ResNet). In fact the residual connections are really central to a Transformer, which may be better thought of as an embedding highway (the "residual" connections) passing thought the layers, with the job of each layer being to incrementally augment these embeddings by adding data to them (derived from attention and feed-forward blocks).

So, what makes these middle layer "workspace" activations (i.e. embeddings) global is that the residual highway interconnects all layers and anything added in lower layers will therefore be globally accessible to all layers above it.

So, there you have it: Surprise surprise (NOT) Transformers share embedding values across layers (woo hoo - global) which represent high level concepts, some of which (depending on random output token selection) may manifest in the output, and others just representing internal abstractions and output paths not taken.

Anthropics PR spin: brainz.. brains.. it's alive! it's conscious!