A.I Artificial Intelligence AI

POSTED BY: JAYNEZTOWN
UPDATED: Monday, September 7, 2026 07:08
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JAYNEZTOWN

Thursday, June 5, 2025 2:31 PM

Google’s Veo 3 AI video generator is a slop monger’s dream

https://www.theverge.com/ai-artificial-intelligence/673719/google-veo-
3-ai-video-audio-sound-effects

Veo-3

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JAYNEZTOWN

Monday, June 9, 2025 3:13 PM

video 'removed by uploader', beats the days when the machine was banning people for questions about 6 feet, 2 meters, social distance


"Godfather of AI" warns that today's AI systems are becoming strategically dishonest - Yoshua Bengio says labs are ignoring warning signs
https://www.techspot.com/news/108171-godfather-ai-warns-today-ai-syste
ms-becoming-strategically.html

Can A.I. be Moral?

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JAYNEZTOWN

Tuesday, June 10, 2025 4:04 PM

China shuts down AI tools during nationwide college exams

https://www.theverge.com/news/682737/china-shuts-down-ai-chatbots-exam
-season

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SIGNYM

Thursday, June 12, 2025 4:30 AM

Quote:

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Do AI Models Think?
Wednesday, Jun 11, 2025 - 10:40 AM

Authored by Thomas Neubeger via "God's Spies" Substack,


AI can’t solve a problem that hasn’t been previously solved by a human.- Arnaud Bertrand

A lot can be said about AI, but there are few bottom lines. Consider these my last words on the subject itself. (About its misuse by the national security state, I’ll say more later.)

The Monster AI

AI will bring nothing but harm. As I said earlier, AI is not just a disaster for our political health, though yes, it will be that (look for Cadwallader’s line “building a techno-authoritarian surveillance state”).

But AI is also a disaster for the climate. It will hasten the collapse by decades as usage expands.

(See the video below for why AI models are massive energy hogs. See this video to understand “neural networks” themselves.)

Why won’t AI be stopped? Because the race for AI is not really a race for tech. It's a greed-driven race for money, a lot of it. Our lives are already run by those who seek money, especially those who already have too much. They've now found a way to feed themselves even faster: by convincing people to do simple searches with AI, a gas-guzzling death machine.

For both of these reasons — mass surveillance and climate disaster — no good will come from AI. Not one ounce.

An Orphan Robot, Abandoned to Raise Itself

Why does AI persist in making mistakes? I offer one answer below.

AI doesn’t think. It does something else instead. For a full explanation, read on.

Arnaud Bertrand on AI

Arnaud Bertrand has the best explanation of what AI is at its core. It’s not a thinking machine, and its output’s not thought. It’s actually the opposite of thought — it’s what you get from a Freshman who hasn’t studied, but learned a few words instead and is using them to sound smart. If the student succeeds, you don’t call it thought, just a good emulation.

Since Bertrand has put the following text on Twitter, I’ll print it in full. The expanded version is a paid post at his Substack site. Bottom line: He’s exactly right. (In the title below, AGI means Artificial General Intelligence, the next step up from AI.)


Apple just killed the AGI myth

The hidden costs of humanity's most expensive delusion
by Arnaud Bertrand

About 2 months ago I was having an argument on Twitter with someone telling me they were “really disappointed with my take“ and that I was “completely wrong“ for saying that AI was “just a extremely gifted parrot that repeats what it's been trained on“ and that this wasn’t remotely intelligence.

Fast forward to today and the argument is now authoritatively settled: I was right, yeah!

How so? It was settled by none other than Apple, specifically their Machine Learning Research department, in a seminal research paper entitled “The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity“ that you can find here ( https://ml-site.cdn-apple.com/papers/the-illusion-of-thinking.pdf).

“Can ‘reasoning’ models reason? Can they solve problems they haven’t been trained on? No.”

What does the paper say? Exactly what I was arguing: AI models, even the most cutting-edge Large Reasoning Models (LRMs), are no more than a very gifted parrots with basically no actual reasoning capability.

They’re not “intelligent” in the slightest, at least not if you understand intelligence as involving genuine problem-solving instead of simply parroting what you’ve been told before without comprehending it.

That’s exactly what the Apple paper was trying to understand: can “reasoning“ models actually reason? Can they solve problems that they haven’t been trained on but would normally be easily solvable with their “knowledge”? The answer, it turns out, is an unequivocal “no“.

A particularly damning example from the paper was this river crossing puzzle: imagine 3 people and their 3 agents need to cross a river using a small boat tha

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