The Communication Cube


They already were making the choice of killing or injuring humans, some (many?) of which where so forced to be there as the donkeys are. I'm not sure the particular species of the victim matters that much.
I mean: I understand you, that deciding whether to destroy an enemy drone is a much easier question than deciding whether t odestroy a enemy human or an enemy donkey.
But they were already destroying manned vehicles with its crew, so they're sadly beyond that point.
They'll blow up donkeys for sure, but I wonder if they'll blow them up on purpose like they do with abandoned transportation (like trucks, quads, motorcycles, etc).
I don't think mechanophilia is common under drone operators, but I could imagine even a regular operator might question blowing up a donkey on purpose (at least the first time doing it).

And the existing AI models used existing human works (code, books, web pages...) to train the models. Often without proper permission. And those human authors used the whole humanity as teachers. So the cost of the USA models should also be higher than stated.

It's funny how OpenAI, DeepSeek and all choose to draw the lines where they please.
If I rename Deepseek to Dontseek and offer it stating it only costs me $1 to create I don't think I'll cause AI stocks to crash. The reason the crash occurred was because Deepseek hinted at doing an identical job as OpenAI but only needing a fraction of hardware and costs.
If Deepseek used humanities build-up knowledge published online, like OpenAI did, they would also need way more resources compared to what they needed now. OpenAI will probably block them from using their services causing Deepseek to not be able to reproduce their trick.
The end result, a public LLM, is great for us consumers. So no complaints there.
 
The first Asterix Volume will now get translated to Ukrainian which is quite a good sign ..

I do plan to use the Asterix Comics as some sort of an Motivation Bait for my book reading : after every book I finish, I read one Asterix Comic ^^
 
They'll blow up donkeys for sure, but I wonder if they'll blow them up on purpose like they do with abandoned transportation (like trucks, quads, motorcycles, etc).
I guess they'll do. Unless they can safely steal them, or rescue them or call it what you will.
I suppose the ideal outcome would be the destruction of any fence or rope holding the donkeys with enough frightening bang that they escape. But I don't see it as likely.

I don't think mechanophilia is common under drone operators, but I could imagine even a regular operator might question blowing up a donkey on purpose (at least the first time doing it).
You're right there. Targeting an empty donkey is a different decision than an empty manned vehicle.

If I rename Deepseek to Dontseek and offer it stating it only costs me $1 to create I don't think I'll cause AI stocks to crash. The reason the crash occurred was because Deepseek hinted at doing an identical job as OpenAI but only needing a fraction of hardware and costs.
If Deepseek used humanities build-up knowledge published online, like OpenAI did, they would also need way more resources compared to what they needed now. OpenAI will probably block them from using their services causing Deepseek to not be able to reproduce their trick.
The end result, a public LLM, is great for us consumers. So no complaints there.
That's an interpretation.
Whatever the business model for DeepSeek, it doesn't seem to imply stopping your Dontseek, since it's MIT licensed (I'm not too knowledgeable on this, I just heard so).
OpenAI terms and conditions, on the other hand, prohibit these activities, but they don't seem to have teeth.
Another interpretation is DeepSeek is proving preexisting OpenAI efforts to block "Knowledge distilling" (and enforce their terms) are unsuccessful, so the money those dumb investors put in OpenAI is at risk.
 
So we all agreed that information wants to be free but now that AI's consume it all for profit we change our minds.
 
85% of successful tech companies are US based. EU is already heavily stifled.
Just for fun I poked ChatGTP-4o with the following prompts:

"Hi. Which nationalities (in terms of personnel) where involved in the breakthroughs that led to the technology that enabled you - so LLM related insights/ideas/research?"

"And when we rather look at where those individuels had been education instead of where they worked, when making these contributions?"

"And when we look at where they grew up instead of where they went to university?"

Each time it listed individuels by contribution topic and nationality as you might expect and I think you already know how the picture shifted. In the last response it concluded:

Conclusion

The origins of AI pioneers show a truly global mix:

  • UK & US dominated early AI.
  • Europe (France, Germany, Russia, Ukraine) played a major role in neural networks and deep learning.
  • Canada became a key hub for deep learning but attracted talent globally.
  • Asia (China, India, Israel) started influencing AI more significantly in the last two decades.
  • Russia and Eastern Europe produced strong theoretical AI researchers, many of whom later worked abroad.
This migration and exchange of knowledge between different regions has been crucial in the development of AI, making it one of the most internationally collaborative fields in science and technology today.

--- end of conclusion ---

Me then:

"So might it be fair to say, that looking at where the contributions are finally made skews the picture in favour of money? And, when looking at where the later talent grew up it's more ... what?"

->

Yes, it would be fair to say that looking at where the contributions are finally made skews the picture in favor of money, resources, and institutional support. The dominant AI research hubs—such as Google (US), DeepMind (UK, now owned by Google), OpenAI (US), and MILA (Canada)—are in countries with strong tech economies, research funding, and high salaries that attract talent globally. Many top researchers relocate to these places because they offer the best opportunities for high-impact work.

What Does Looking at Where the Talent Grew Up Tell Us?

When we shift the focus to where key AI researchers grew up, the picture becomes more about fundamental education, curiosity-driven learning environments, and access to early intellectual challenges rather than just money. A few patterns emerge:

  1. Diversity in Backgrounds, Centralized in Opportunities
    • Many influential AI researchers did not grow up in the wealthy hubs where they later made their breakthroughs.
    • Instead, they came from a mix of backgrounds—some from highly developed, resource-rich countries (e.g., US, UK, France, Germany), while others came from regions with fewer direct AI resources early on (e.g., Russia, India, China, Israel).
  2. Strong Early Education, Especially in Math & Physics
    • A solid math and physics education seems to be a key enabler for AI talent, regardless of country.
    • Countries known for strong early math and science training (e.g., Russia, Germany, France, India, China) produced several of the major contributors, even if they later moved elsewhere.
    • This suggests that early access to rigorous problem-solving, logic, and abstract thinking is more predictive of later success than just growing up in a wealthy nation.
  3. Cultural Emphasis on Technical Skills
    • Nations that prioritize STEM education from a young age—such as France (École Normale Supérieure tradition), Germany (TUM, mathematical rigor), Russia (Mathematical Olympiads), and India (IIT system, strong theoretical emphasis)—have disproportionately contributed to AI talent.
    • Even when AI resources were limited in these countries, their emphasis on foundational knowledge in mathematics, engineering, and physics provided a strong base for later breakthroughs.
  4. Mobility of Talent
    • Many top AI researchers left their home countries in pursuit of higher education or research opportunities.
    • Example: Geoffrey Hinton (UK → Canada), Ilya Sutskever (Russia → Canada → US), Fei-Fei Li (China → US), Anima Anandkumar (India → US).
    • This suggests that AI breakthroughs don’t necessarily originate where people are born but where they are given the resources to flourish.
    • The US, Canada, and UK benefit from a "brain drain" of top minds from around the world.

So, If Money Skews Where AI Contributions Are Made, What Skews Where the Talent Comes From?

If institutional funding and corporate resources skew the location of AI breakthroughs, then early education quality, mathematical culture, and mobility opportunities skew where the talent originates from.

  • Money & Research Hubs determine where AI breakthroughs are made.
  • Education, STEM Emphasis, and Cultural Attitudes toward math and engineering determine where the AI talent grows up.
--- end of response ---

So yeah, I'd say, should the US as a big attractor vanish, I don't think the world would be lost. Maybe it could even get better at furthering humanity instead of money concentration camps.
 
Just for fun I poked ChatGTP-4o with the following prompts:
Have fun
So yeah, I'd say, should the US as a big attractor vanish, I don't think the world would be lost. Maybe it could even get better at furthering humanity instead of money concentration camps.
You would say it for fun too?
Because that's just what that LLM says, or did it give sources or you did your own research ?
It may just be saying what you're likely (in some model) to want to read.
I don't find it surprising or strange. It may be true. I might have said the same or similar. But I haven't researched it either. In any case it's not just true because an LLM wrote it.
In any case, thanks for the fun. Might be fun to ask an asiatic LLM. or an arabic one, or ...
 
So we all agreed that information wants to be free but now that AI's consume it all for profit we change our minds.
I don't have a problem (on the contrary) with changing laws so that information is freer.
I just find it hypocritical when someone says input information should be free and output information should not, because ... money.

By the way, I thought acting for financial gain was an aggravating circumstance, not a mitigating one.

And there's also some responsibility on how you use information, the noise you generate, the burden on other peoples servers (I can of take more offense for disregarding robots.txt than for disrregarding copyright), the energy expense...
 
@pyrat Yeah for fun of course. At the same time, while I do not assume and don't expect anyone to assume an LLM's output to be as well founded as the laws of thermodynamics, it's good at giving things worth to consider. I didn't quote it to prove anything. It was meant for consideration. And I myself saw nothing in there I didn't expect. (Of course, I could've just written what I thought myself, but Ol' Chatty is better at putting things into words and recalling more aspects than I am. So why not take advantage.) And I quoted my prompts, so you may consider how much I directed the conversation.
 
Just for fun I poked ChatGTP-4o with the following prompts:

"Hi. Which nationalities (in terms of personnel) where involved in the breakthroughs that led to the technology that enabled you - so LLM related insights/ideas/research?"

"And when we rather look at where those individuels had been education instead of where they worked, when making these contributions?"

"And when we look at where they grew up instead of where they went to university?"

Each time it listed individuels by contribution topic and nationality as you might expect and I think you already know how the picture shifted. In the last response it concluded:

Conclusion

The origins of AI pioneers show a truly global mix:

  • UK & US dominated early AI.
  • Europe (France, Germany, Russia, Ukraine) played a major role in neural networks and deep learning.
  • Canada became a key hub for deep learning but attracted talent globally.
  • Asia (China, India, Israel) started influencing AI more significantly in the last two decades.
  • Russia and Eastern Europe produced strong theoretical AI researchers, many of whom later worked abroad.
This migration and exchange of knowledge between different regions has been crucial in the development of AI, making it one of the most internationally collaborative fields in science and technology today.

--- end of conclusion ---

Me then:

"So might it be fair to say, that looking at where the contributions are finally made skews the picture in favour of money? And, when looking at where the later talent grew up it's more ... what?"

->

Yes, it would be fair to say that looking at where the contributions are finally made skews the picture in favor of money, resources, and institutional support. The dominant AI research hubs—such as Google (US), DeepMind (UK, now owned by Google), OpenAI (US), and MILA (Canada)—are in countries with strong tech economies, research funding, and high salaries that attract talent globally. Many top researchers relocate to these places because they offer the best opportunities for high-impact work.

What Does Looking at Where the Talent Grew Up Tell Us?

When we shift the focus to where key AI researchers grew up, the picture becomes more about fundamental education, curiosity-driven learning environments, and access to early intellectual challenges rather than just money. A few patterns emerge:

  1. Diversity in Backgrounds, Centralized in Opportunities
    • Many influential AI researchers did not grow up in the wealthy hubs where they later made their breakthroughs.
    • Instead, they came from a mix of backgrounds—some from highly developed, resource-rich countries (e.g., US, UK, France, Germany), while others came from regions with fewer direct AI resources early on (e.g., Russia, India, China, Israel).
  2. Strong Early Education, Especially in Math & Physics
    • A solid math and physics education seems to be a key enabler for AI talent, regardless of country.
    • Countries known for strong early math and science training (e.g., Russia, Germany, France, India, China) produced several of the major contributors, even if they later moved elsewhere.
    • This suggests that early access to rigorous problem-solving, logic, and abstract thinking is more predictive of later success than just growing up in a wealthy nation.
  3. Cultural Emphasis on Technical Skills
    • Nations that prioritize STEM education from a young age—such as France (École Normale Supérieure tradition), Germany (TUM, mathematical rigor), Russia (Mathematical Olympiads), and India (IIT system, strong theoretical emphasis)—have disproportionately contributed to AI talent.
    • Even when AI resources were limited in these countries, their emphasis on foundational knowledge in mathematics, engineering, and physics provided a strong base for later breakthroughs.
  4. Mobility of Talent
    • Many top AI researchers left their home countries in pursuit of higher education or research opportunities.
    • Example: Geoffrey Hinton (UK → Canada), Ilya Sutskever (Russia → Canada → US), Fei-Fei Li (China → US), Anima Anandkumar (India → US).
    • This suggests that AI breakthroughs don’t necessarily originate where people are born but where they are given the resources to flourish.
    • The US, Canada, and UK benefit from a "brain drain" of top minds from around the world.

So, If Money Skews Where AI Contributions Are Made, What Skews Where the Talent Comes From?

If institutional funding and corporate resources skew the location of AI breakthroughs, then early education quality, mathematical culture, and mobility opportunities skew where the talent originates from.

  • Money & Research Hubs determine where AI breakthroughs are made.
  • Education, STEM Emphasis, and Cultural Attitudes toward math and engineering determine where the AI talent grows up.
--- end of response ---

So yeah, I'd say, should the US as a big attractor vanish, I don't think the world would be lost. Maybe it could even get better at furthering humanity instead of money concentration camps.
Right. But the companies are based in the US and it reaps the rewards. Brain drain. European investors have less appetite for risk. And then there's left-leaning governments like the one here in the UK squandering things further by promising wealth distribution through higher taxes, which really just benefits them. Identical jobs now pay twice as much in New York as London. 15 years ago the difference was 30%. Talk about inequality.

What governments need to realise is they (politicians) can be wealthier if they admit it's a global competition for talent and companies actually, instead of just taxing the shit out of their captive populace. Zürich attracted Google HQ and recently Apple AI Lab and many more multinationals over the years and it's created a lot of great jobs and wealth for Swiss people. Germany, France, England, etc all lost out.
 
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@pyrat Yeah for fun of course. At the same time, while I do not assume and don't expect anyone to assume an LLM's output to be as well founded as the laws of thermodynamics, it's good at giving things worth to consider. I didn't quote it to prove anything. It was meant for consideration. And I myself saw nothing in there I didn't expect. (Of course, I could've just written what I thought myself, but Ol' Chatty is better at putting things into words and recalling more aspects than I am. So why not take advantage.) And I quoted my prompts, so you may consider how much I directed the conversation.
I'm sorry. I think I wrote it harsher than I meant it. It's indeed fun.
I didn't mean to accuse you of anything,
I still disagree with you in one thing: I prefer to read you than Ol' Chatty. I like it better how you put things into words. Must be a matter of taste.
But I wouldn't forbid you to use LLMs (even if I could), specially if you tell us you do as you did.
 
Right. But the companies are based in the US and it reaps the rewards. Brain drain. European investors have less appetite for risk. And then there's left-leaning governments like the one here in the UK squandering things further by promising wealth distribution through higher taxes, which really just benefits them. Identical jobs now pay twice as much in New York as London. 15 years ago the difference was 30%. Talk about inequality.

What governments need to realise is they (politicians) can be wealthier if they admit it's a global competition for talent and companies actually, instead of just taxing the shit out of their captive populace. Zürich attracted Google HQ and recently Apple AI Lab and many more multinationals over the years and it's created a lot of great jobs and wealth for Swiss people. Germany, France, England, etc all lost out.
Eh, your left-leaning UK seems to have just invented quantum large language models, whatever than means. It may be innovatie or not, butt it sure is buzzword compliant. I wonder whether the newspiece author worte it all by himself...
 
What governments need to realise is they (politicians) can be wealthier if they admit it's a global competition for talent and companies actually, instead of just taxing the shit out of their captive populace. Zürich attracted Google HQ and recently Apple AI Lab and many more multinationals over the years and it's created a lot of great jobs and wealth for Swiss people. Germany, France, England, etc all lost out.
Isn't it that populaces in countries with highest taxes and good wellfare tend to be happiest? I'd then assume they experience less brain drain. ?
I prefer to read you than Ol' Chatty. I like it better how you put things into words.
Oh, thanks :)
 
Isn't it that populaces in countries with highest taxes and good wellfare tend to be happiest? I'd then assume they experience less brain drain. ?
I guess you're talking about Scandinavia. Sweden is open to international business and Norway has oil so both are rich. Being rich means politicians are less susceptible to bribes and so can make more decisions that actually benefit the people. Switzerland is like this too. It also has direct democracy which cuts out politicians and their false promises.
 
@netcat Ain't the USA supposed to be the richest country in the fucking world. Are you saying the politicians there were the least corruptible.
 
@netcat Ain't the USA supposed to be the richest country in the fucking world. Are you saying the politicians there were the least corruptible.
I assume you also need to be held accountable for your actions. Some countries are poor but they kill corrupt politicians, some countries are rich but hardly anything happens when you're corrupt.
 
Back in the days of wii & ipod I thought Nintendo and Apple might be a nice merger, similar aesthetic, etc. Of course many are interested in Nintendo. Amazing and unique company.


Here is Nintendo's ownership structure. Note they maintain 10.35% (ownership of themselves) and afaik any ownership of above 10% requires approval from the board so they could block and maintain control (so no one can tell them how to make their games). Public Investment Fund is Saudi's.

1739356242468.png
 
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