When thinking about #AI, I think it is worth recalling where language models came from. It explains a few things.

The first mention of a language model can be found in a 1983 paper by three IBM employees: Lalit Bahl, Frederick Jelinek and Robert Mercer. The paper sensibly suggests a statistical method to improve automatic speech recognition: whenever the audio system is too bad to distinguish between "*The cat sleep" and the "The cat sleeps", the language model should come to the rescue to say that the grammatical sentence "The cat sleeps" is probabilistically much more likely.

By 1990, with the popularisation of personal computers, IBM is looking for opportunities to sell their mainframes. A research team (incl. Jelinek and Mercer) extends the statistical approach used in speech recognition to machine translation. The paper makes it very clear that the technology relies on sheer computing power -- something that IBM happens to have a lot of and is very keen to sell. It also makes for interesting close-reading: after deploring the so-called 'impotence' of earlier computers, the authors go on introducing mathematical measures such as the evocative 'fertility' to describe how many words the model spawns for each lexical item in the source text. (No women were involved in the making of this paper.)

Statistical language models are properly born, and with them the advent of large text corpora. They prefigure the Large Language Models we are now used to.

Jelinek will become famous for his disdain of linguistics and is often quoted as saying “Every time I fire a linguist, the performance of the speech recognizer goes up.” Mercer will go on donating millions of his personal fortune to the Brexit campaign, the 2016 election of Donald Trump and the super PAC in support of J.D. Vance.

So should we really be surprised when scale is confused with intelligence? When Alex Karp says that AI will be bad for women? Or when prominent technology companies display fascistoid tendencies? It seems to me it was all there at the beginning.

References:

Bahl, L. R., Jelinek, F., & Mercer, R. L. (1983). A maximum likelihood approach to continuous speech recognition. IEEE transactions on pattern analysis and machine intelligence, (2), 179-190.

Brown et al (1990). A statistical approach to machine translation. Computational linguistics, 16(2), 79-85.

Project Glasswing and open source software: The good, the bad, and the ugly https://theregister.com/2026/04/10/project_glasswing/ via @theregister & @sjvn

Anthropics Mythos is an automated #AI zero-day code-discovery engine. Sure, finding #opensource security holes is great, but who's going to fix them?

This should infuriate any citizen of British Columbia.

"OPENAI IS THROWING its support behind an Illinois state bill that would shield AI labs from liability in cases where AI models are used to cause serious societal harms, such as death or serious injury of 100 or more people or at least $1 billion in property damage.”

This is the kind of company OpenAI is. These companies want to be free to corrupt and damage our minds. (like Meta has done)

https://www.wired.com/story/openai-backs-bill-exempt-ai-firms-model-harm-lawsuits/
#AI #tumblerridge

If you're feeling discouraged fighting against this fresh "AI" hell we're dealing with daily now,

I recommend listening to this awesome podcast by @DAIR to lift your spirits.

You're not alone in this battle
Available on PeerTube!

https://peertube.dair-institute.org/c/mystery_ai_hype_theater/videos

#NoAI #AI #MysteryAIHypeTheater3000 #PeerTube #Podcast #Fediverse

This should infuriate any citizen of British Columbia.

"OPENAI IS THROWING its support behind an Illinois state bill that would shield AI labs from liability in cases where AI models are used to cause serious societal harms, such as death or serious injury of 100 or more people or at least $1 billion in property damage.”

This is the kind of company OpenAI is. These companies want to be free to corrupt and damage our minds. (like Meta has done)

https://www.wired.com/story/openai-backs-bill-exempt-ai-firms-model-harm-lawsuits/
#AI #tumblerridge

The whole ‘our AI model is too dangerous to be released to the public’ is brilliant marketing; now they’ve created artificial scarcity and you just know there will be people with deep pockets scrambling to be included in the ‘exclusive club’ of orgs that are ‘allowed’ to access the technology.

And of course the media are willing accomplices in driving the hype cycle.

#AI #AIScam #AIBubble

The whole ‘our AI model is too dangerous to be released to the public’ is brilliant marketing; now they’ve created artificial scarcity and you just know there will be people with deep pockets scrambling to be included in the ‘exclusive club’ of orgs that are ‘allowed’ to access the technology.

And of course the media are willing accomplices in driving the hype cycle.

#AI #AIScam #AIBubble

When thinking about #AI, I think it is worth recalling where language models came from. It explains a few things.

The first mention of a language model can be found in a 1983 paper by three IBM employees: Lalit Bahl, Frederick Jelinek and Robert Mercer. The paper sensibly suggests a statistical method to improve automatic speech recognition: whenever the audio system is too bad to distinguish between "*The cat sleep" and the "The cat sleeps", the language model should come to the rescue to say that the grammatical sentence "The cat sleeps" is probabilistically much more likely.

By 1990, with the popularisation of personal computers, IBM is looking for opportunities to sell their mainframes. A research team (incl. Jelinek and Mercer) extends the statistical approach used in speech recognition to machine translation. The paper makes it very clear that the technology relies on sheer computing power -- something that IBM happens to have a lot of and is very keen to sell. It also makes for interesting close-reading: after deploring the so-called 'impotence' of earlier computers, the authors go on introducing mathematical measures such as the evocative 'fertility' to describe how many words the model spawns for each lexical item in the source text. (No women were involved in the making of this paper.)

Statistical language models are properly born, and with them the advent of large text corpora. They prefigure the Large Language Models we are now used to.

Jelinek will become famous for his disdain of linguistics and is often quoted as saying “Every time I fire a linguist, the performance of the speech recognizer goes up.” Mercer will go on donating millions of his personal fortune to the Brexit campaign, the 2016 election of Donald Trump and the super PAC in support of J.D. Vance.

So should we really be surprised when scale is confused with intelligence? When Alex Karp says that AI will be bad for women? Or when prominent technology companies display fascistoid tendencies? It seems to me it was all there at the beginning.

References:

Bahl, L. R., Jelinek, F., & Mercer, R. L. (1983). A maximum likelihood approach to continuous speech recognition. IEEE transactions on pattern analysis and machine intelligence, (2), 179-190.

Brown et al (1990). A statistical approach to machine translation. Computational linguistics, 16(2), 79-85.

I use ChatGPT every day, but I’m careful about what I share.

Many users treat AI tools like a private space — which can lead to serious privacy risks.

I follow 3 simple rules:
• Don’t share sensitive data
• Remove personal details
• Use privacy settings

If you use AI regularly, this is worth reading:
https://techputs.com/chatgpt-privacy-rules/

#ChatGPT #Privacy #AI #CyberSecurity #DataProtection #tech #technology

"The percentage of respondents ages 14 to 29 who said they felt hopeful about A.I. declined sharply since last year, down to 18 percent from 27.

Young adults’ excitement about artificial intelligence dropped, too, and nearly a third of respondents indicated that the technology made them feel angry."

That's rough.

https://www.nytimes.com/2026/04/09/style/gen-z-ai-gallup-study.html?unlocked_article_code=1.ZlA.wN1w.cqoDFMOIp-qT&smid=url-share

#news #technology #TechNews #AI #LLMs

We knew, but the proof is nice.

"Apple just proved that AI models cannot do math. Not advanced math. Grade school math. The kind a 10-year-old solves"

The guess-the-next-words machines don’t actually understand anything.

https://nitter.poast.org/heynavtoor/status/2041243558833987600#m

#math #ai

If a human right is in the way of your "innovative" technology, the expected solution should be to modify your technology to respect this human right, not to reduce the protections to this human right.

Technology and innovation must be in service of humanity, not the other way around.

#HumanRights #DigitalRights #Privacy #AI

"The percentage of respondents ages 14 to 29 who said they felt hopeful about A.I. declined sharply since last year, down to 18 percent from 27.

Young adults’ excitement about artificial intelligence dropped, too, and nearly a third of respondents indicated that the technology made them feel angry."

That's rough.

https://www.nytimes.com/2026/04/09/style/gen-z-ai-gallup-study.html?unlocked_article_code=1.ZlA.wN1w.cqoDFMOIp-qT&smid=url-share

#news #technology #TechNews #AI #LLMs

@EUCommission

Burning the planet to generate unverified bullshit; stealing from creators; poisoning the whole process of generation, presentation, teaching, and usage of knowledge; helping to fire qualified professionals by the thousands, to replace them with unqualified babbling machines; inflating an irresponsible investment bubble until it bursts, resulting in unprecedented damage.

You're proud of your work of utter destruction? You fools. You're enemies of humankind.

" #AI" #EU #EUpol

@EUCommission

Burning the planet to generate unverified bullshit; stealing from creators; poisoning the whole process of generation, presentation, teaching, and usage of knowledge; helping to fire qualified professionals by the thousands, to replace them with unqualified babbling machines; inflating an irresponsible investment bubble until it bursts, resulting in unprecedented damage.

You're proud of your work of utter destruction? You fools. You're enemies of humankind.

" #AI" #EU #EUpol

@arstechnica

Human flight is a waste of resources. I'd rather have real results now then wait another 30 years while politicians fight about the huge expense.

One of the better uses for #AI is to send semi-autonomous devices to locations around the solar system.

Until we have something like nuclear rockets, sending people into space is not a cost effective method of deep space exploration.

If a human right is in the way of your "innovative" technology, the expected solution should be to modify your technology to respect this human right, not to reduce the protections to this human right.

Technology and innovation must be in service of humanity, not the other way around.

#HumanRights #DigitalRights #Privacy #AI

"Japan relaxes privacy laws to make itself the ‘easiest country to develop AI’"

"Opting out of personal data use won't be an option because Minister says that's a 'very big obstacle' to AI adoption"

https://www.theregister.com/2026/04/08/japan_privacy_law_changes_ai/?td=rt-3a

#ai #llm