I'm not sure why lane keeping requires and automatic, it seems to me turning the wheel would be fine.

My manual does fine for emergency braking (though it's a little touchy when someone in front of me is turning or if I'm accelerating to speeding under 20mph). I feel like if the emergency brake slows me down so much I need to shift the problem is me, not the manual (it hasn't over the last 10k miles I've had the car).

It'll certainly never self drive, and is useless for stop and go traffic cruise control (20-60mph heavy traffic is fine).

The higher end performance is shifting towards dual clutch since it's objectively better for performance.

The economy cars are getting automatics to simplify production lines now that automatics are basically the same cost to make and essentially as efficient as manuals.

So the only manuals getting made are in the budget low tech sportscar market where people aren't going for performance, but fun on a budget.

What does Afghanistan have to do with any of the "Gulf War"s?

The first two were Iraq, the third is Iran.

I may want to use the code modified and not share my modifications. The GPL prevents this.

Aside from the corner case of libraries incrementing proposed standards I think this is a plus, but it certainly is a restriction that a copy left license has and a BSD/MIT one doesn't.

You're right. It's the BSD part of the name that is the clue, not the Free part.

At least in the past "Free" was the copy lefted part of OSS software, with many OSS puriwta believing a BSD type licence was more Free as others thought it was less so.

Wasn't the advertising clause determined to be non free and long since removed?

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!

I read it more as "we're already in compliance, no changes"

And now we'll have another long lawsuit about whether or not they're in compliance. They'll need to make changes in 9 years when that suit plays out and a year later it's irrelevant.

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!

You default to a windows user agent as of earlier this year?

I've had to tweak it on a rare occasion, bit I haven't left the default as lie and be windows for a long long long time.

I imagine the stats website is more likely to capture my default than the random site I've tweaked.

I guess you could frame it like that, but knowing how it works doesn't help if you don't have the know-how to build it.

How do you increase your EUV power from 100W to 1000W (this took ASML years to figure out)?

How do you make mirrors smooth to within a single atom deviation?

How do you make chemical etch pure to the parts-per-trillion level?

No doubt the Chinese will figure these things out by themselves if they have to, but I'm sure there are a few secrets to be had that would speed that up!

EUV would be nice to have, but at the end of the day it all comes down to cost. Without EUV your chips will be larger and slower, so you'll need more of them (more expensive) to build a cluster of the same power.

The cost of serving (not price to you) an AI model is mostly hardware depreciation cost, not operating cost, with the accelerator chip cost being a large part of that.

NVIDIA's H100 chip costs $25-40K

Huawei's comparable Ascend 950PR costs $7-16K

As you can see, lack of EUV is not stopping the Chinese from being price competitive.

That's irrelevant. Sure China has been blocked from buying ASML EUV machines, but they are doing just fine with DUV and companies like SMIC (Chinese semicondustor fab cf TSMC) have pushed it to ~7nm node size.

The Chinese are making their own AI accelerators, such as Huawei's Ascend series, which DeepSeek are using, but just like OpenAI making their own chips to avoid the NVIDIA tax, DeepSeek now want to make their own presumably at least in part to avoid the Huawei tax (as well as perhaps to gain even greater efficiency).