My intuition is the opposite. My favorite example is the patent situation around flight in the 1910's, which ensured that the USA entered WWI without its own fighter aircraft industry. The US actually ended up buying french machines.
Roughly about Eur 3-4K right this minute I think? The graphics card, ram and storage are punishing. Under more normal circumstances (hopefully late 2027) it'd be 1500-2500 depending on what you think is realistically useful.
Possibly it's the same price range, allowing for inflation.
I looked into GmbH (german) , BV (dutch) , and OU (estonian) . GmbH seems very unpleasant. BV and OU are easier to obtain. But BV requires your primary place of business to be the Netherlands, which isn't always practical when you're trying to extend your activities internationally. OU is supposed to be better for international operations, but -because it's a single country initiative- creates new and interesting tax problems.
At this time, the whole system seems to revolve around geographic location. As long as you stay put you're sort of fine, but if you move around within the EU, the law doesn't stay stable around you. This is impractical.
This is not a very useful property for an encyclopedia, so you're going to need a different system for determining outcomes.
Preferably you need a method that is somehow still somewhat fair. And that's how we get to the concept of rough consensus. It's absolutely not perfect, and it's not meant to be, because nothing is. Improvements welcome.
I took a quick look at what the "Wikiproject intellectual diversity" was actually monitoring. Specific articles or categories about things Mr Sanger finds interesting,right? Well, indeed: specifically it's all arbcom, admin elections, policy pages. You can check it out here: https://en.wikipedia.org/wiki/User:Larry_Sanger/WikiProject_...
Then he canvassed people from outside wikipedia to help with that project.
So he claimed to be doing one thing, but in reality it was more of a thinly disguised power play by the look of it.
Coming from a certain european country, you never know what answer on the census might get you into trouble.
"What is your religious affiliation". Seems perfectly innocuous, but turned out to be retroactively fatal if your answer could be attributed to you by a certain foreign occupier in the 1940s .
A) I am allergic to the word Just ;-) It means you stop being curious. How about one or more of the following?
B) Say you have a slow optimizer in a fast world: a lot of the time the optimal solution is going to be some form of computational generalization. Now you have meta-optimization. Life seems to enjoy doing this recursively.
C) Crow intelligence is clearly highly evolved, so you're technically correct, best kind of correct. Though here I'd argue that a very parsimonious answer is single-lifespan learned behavior. You're applying an existing learning system, no new mechanisms needed. (As opposed to positing some new evolved fixed action pattern).
D) There's not even anything stopping it from being planned behavior. Searle is struck out because it is biological; and no one can accuse us of anthropomorphism HERE!
E) Actually, for sparse events, planning using a world model can be more parsimonious. Apply existing model to new problem, again no extra mechanism needed. Which one works better for a particular entity in a particular situation depends on tradeoffs. (For a human example: see eg Memory items vs checklists vs airmanship in eg aviation)
F) That said, I'd even count evolution as a form of intelligence (well... it's an optimizer at least). I will literally die on this hill, and so will you O:-) (unless you represent optimums as valleys) ---> Plot evolution as a dynamic system in phase space, or with your typical hill-climber/gradient descent representations. How much does the trajectory differ from other optimizers? What happens if the 'terrain' is very bumpy with many local optimums? What if it deforms as you cross it?
Buried lede (if the title is the actual promise), the sources don't seem to back the title either. Someone with more patience can correct me if I accidentally missed a bombshell anyway.
Edit:
> If you’re wondering what the story is, [...] I expect it to be out in the next two weeks [...] I can guarantee you it’ll be worth it, and you’ll be stunned by what I report.
Ok, this takes clickbait to new lows. The headline is trying to sell the teaser here, with very limited meat in the middle of the sandwich.
So the other month, I made a quick and dirty Eliza implementation; bolted on the crappiest numeric sentiment classifier I could get away with (regex), and integrated the output of the classifier over time in a 'functional affect vector' (aka. emotion vector)
Anyone's intuition will tell you that this cannot POSSIBLY have 'Real Feelings (TM)'; and that's the whole point.
A) It was still capable of quite a bit of functional affect though; to wit I got it to trigger fireworks when happy, and rain when unhappy. This was the actual point of the exercise. Functional Affect Does The Thing, QED, yay me.
After that it gets annoying though.
B) Am I allowed to say it's happy or sad? Well... I mean emotion.happy=0.995 and emotion.sad=0.001. "It's really happy" is a prosaic description of a real numeric value representing a real functional state. What else am I supposed to call it? I swear I never meant to go there, and now I'm stuck with it.
C) So, we all know that it's a crappy demo, not the real thing. So I ducked into the psychology literature to try and find a protocol to disprove. For Science! And this is where the psychology literature really let me down.
So now I'm stuck with the crappiest thing that can plausibly still chat, and where I can't actually disprove it has emotions. Not properly, at least. And I'm not saying it's because it has emotions, because that would be really funny, but no.
I'm saying that -despite lots of people having fun debates at the local pub- it doesn't seem like anyone actually scientific has done anything about it in the last century or so. I might be searching in the wrong places. Some Help Here?
> Second, there is no reason to suppose that Claude experiencing those qualia
I'd argue the qualia question is a red herring. Functional Affect is a thing, regardless of ontological status. It's all fun and games until someone gets hurt.
To paraphrase Dijkstra: "The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.". If you're building a navy: you care about displacement, propulsion, navigation and whether it can fire torpedoes. Whether your submarine has some "biological essence" of swimming is not really relevant to the fact that it is currently moving through the water and can collide with things. Turing also rejected the question "Can Machines Think" as posed, and replaced it with an operationalization (something else that we can actually usefully measure and work with).
To reiterate, functional affect is a concrete phenomenon. Whether or not there is a what-it-is-to-be is interesting in the abstract, but engineering a system means looking at how the inputs influence the outputs. A next token predictor working on a language that communicates affect needs to be able to predict affect or it is simply not going to be accurate. Given an 'angry' version of an input and a 'friendly' version of the same input, LLMs are likely to provide a different output, especially if there's a non-objective element. You can diff this.
Searle argues "A simulation is not the real thing", which is great and all... but if you hook up say an autopilot to the real world (as llms increasingly are) , you'd best hope the simulation was accurate in the first place (utterly regardless of where you stand on Searle).
Right now we're seeing situations where LLMs can be helpful or a real nuisance. Ignoring functional affect out of sheer ideology means you can't properly predict what they'll do, and that causes trouble, as we've already seen stories about.
This gets especially interesting when you start feeding the output back into the input (autoregression) , because now you have a highly non-linear dynamic system and you've introduced some amount of sensitivity to initial state. There's some interesting mathematical intuitions to be had there.