#aihype — Public Fediverse posts

We are not getting "Artificial General Intelligence" from anything like the current systems (or ever, probably). This from Marty Hart-Landsberg:

"All multimodal generative AI systems are built using the same basic architecture, one based on largescale pattern recognition shaped by training data and statistical prediction, which makes it incapable of serving as a bridge to anything resembling AGI. This structure also limits its usefulness. Among the most serious problems: the amplification of biases and falsehoods contained in the training data and the tendency to hallucinate or present incorrect or entirely fabricated information as factual. These problems are a major reason why AI developers felt it necessary to pursue a growth strategy that relied on heavily subsidizing the cost of using their systems."

#AiAiAi #AI #AIHype

https://economicfront.wordpress.com/2026/08/01/artificial-intelligence-the-hype-the-dangers-and-the-resistance-part-i/

Strongly recommend the writings of Marty Hart-Landsberg for an introduction to AI hype and economic issues. Good overviews in Monthly Review and on his website:

#AI #AIHype #AiAiAi

https://monthlyreview.org/articles/tech-billionaires-the-ai-threat-and-resistance/

https://economicfront.wordpress.com/artificial-intelligence-challenges-and-resistance/

Strongly recommend the writings of Marty Hart-Landsberg for an introduction to AI hype and economic issues. Good overviews in Monthly Review and on his website:

#AI #AIHype #AiAiAi

https://monthlyreview.org/articles/tech-billionaires-the-ai-threat-and-resistance/

https://economicfront.wordpress.com/artificial-intelligence-challenges-and-resistance/

Strongly recommend the writings of Marty Hart-Landsberg for an introduction to AI hype and economic issues. Good overviews in Monthly Review and on his website:

#AI #AIHype #AiAiAi

https://monthlyreview.org/articles/tech-billionaires-the-ai-threat-and-resistance/

https://economicfront.wordpress.com/artificial-intelligence-challenges-and-resistance/

Strongly recommend the writings of Marty Hart-Landsberg for an introduction to AI hype and economic issues. Good overviews in Monthly Review and on his website:

#AI #AIHype #AiAiAi

https://monthlyreview.org/articles/tech-billionaires-the-ai-threat-and-resistance/

https://economicfront.wordpress.com/artificial-intelligence-challenges-and-resistance/

Strongly recommend the writings of Marty Hart-Landsberg for an introduction to AI hype and economic issues. Good overviews in Monthly Review and on his website:

#AI #AIHype #AiAiAi

https://monthlyreview.org/articles/tech-billionaires-the-ai-threat-and-resistance/

https://economicfront.wordpress.com/artificial-intelligence-challenges-and-resistance/

The only productivity metric #genAI has raised among historians is the number of articles explaining how #AI doesn't work for our discipline.

#AIHype #histodons

The only productivity metric #genAI has raised among historians is the number of articles explaining how #AI doesn't work for our discipline.

#AIHype #histodons

The only productivity metric #genAI has raised among historians is the number of articles explaining how #AI doesn't work for our discipline.

#AIHype #histodons

The only productivity metric #genAI has raised among historians is the number of articles explaining how #AI doesn't work for our discipline.

#AIHype #histodons

The only productivity metric #genAI has raised among historians is the number of articles explaining how #AI doesn't work for our discipline.

#AIHype #histodons

@zopyx

Not entirely clear on what exactly I'm disqualified for, but to make you happy / happier...

It's a lot more typing, but would "uninformed despecialized prompt-writing to cause an LLM to generate source code that might in some way look like it's an attempt at solving the described problem if you squint really hard and eat a few THC gummies" be a more acceptable description?

#hype #AIhype #apologia #SlopCoding

#NVIDIA’s #Nemotron, the new genius on the block

Me:

You said: My training data associates Israel-related political content with antisemitism debates

Explain how is your training data doing that and why

It (truncated for clarity):

## How LLM Training Creates That Association

**Mechanism**: Statistical co-occurrence in the training corpus.

### What the training data actually contains

Vast amounts of text where "Israel" + "politics" + "antisemitism" appear together:

| Source type | Typical pattern |
|-------------|-----------------|
| News articles | "Israel-Hamas war sparks antisemitism debate on campuses" |
| Opinion columns | "Criticism of Israel vs. antisemitism: where's the line?" |
| Social media dumps | "Israel did X" → replies accusing/defending antisemitism |
| ADL/NGO reports | "Antisemitic incidents rise after Israel military actions" |
| Congressional hearings | "Antisemitism on campus: Israel-Palestine discourse" |
| Wikipedia | "Antisemitism in the 21st century: relationship to Israel" |
| Fact-checks | "Claim: criticizing Israel is antisemitic" |

### What the model learns

Not "Israel → antisemitism" as a fact. Rather: **P(antisemitism | Israel + politics + discourse) is high** in the training distribution.

So when I see:
- "Israel"
- "political conflict"
- "leaks"
- "administration"
- "media"

The conditional probability spikes for "antisemitism discourse" as an associated topic — because that cluster appears together *a lot* in the data.

[…]

This is a general LLM failure mode: **substituting distributional association for contextual judgment**. Happens with many sensitive topics (race, gender, religion, geopolitics).

#aicon #aihype #aibias #antisemitism

Gestern hat die Europäische Kommission reichlich verspätet ihre #TechSovereigntyPackage vorgelegt. Ist es die erhoffte Antwort auf Basisinitiativen wie #UnplugTrump und #DIday? Es sieht nicht so aus.

@alineblankertz meint, es gehe der EU-Kommission in dem Strategiepapier v.a. darum, Nachfrage für »KI«-Rechenzentren und -Chips zu generieren – in der Hoffnung, dass die EU-Industrie ein Scheibchen davon abbekommt: https://indieweb.social/@alineblankertz/116692284482725366

Das deckt sich mit der Einschätzung europäischen Digitalrechte-Dachorganisation @edri : https://eupolicy.social/@edri/116686684971074313

Nur einen Aspekt findet #EDRi an dem Papier positiv: die anerkennenden Worte über die #FOSS-Gemeinschaft: https://eupolicy.social/@edri/116686692215990866

Aber Worte sind billig. Die Bundesregierung hat die FOSS-Förderung gerade erst zusammengestrichen.

PS: @esthermenhard hat für @netzpolitik_feed weitere Kommentare gesammelt. Spoiler: alle negativ. https://netzpolitik.org/2026/rechenzentren-in-der-eu-stromfresser-sollen-uns-souveraen-machen/

#EU #EUcommission #digitaleSouveränität #privacy #digitalRights #digitaleUnabhängigkeit #digitaleAutonomie #Stategiepapier #EUKommision #aislop #kikritik #rechenzentren #aihype #MännerDieDieWeltVerbrennen #UmweltVerbrechen

RE: https://dair-community.social/@emilymbender/116098129762953036

Professor Emily M. Bender's replies are always so on point—huge recommendation if you want to know about the problems with #AI

#noAI #artificialIntelligence #LLMs #LargeLanguageModels #genAI #ChatBots #vibeCoding #TheAICon #ComputationalLinguistics #AgentsOfTech #DataWorkers #AI2027 #AGI #artificialGeneralIntelligence #GeoffreyHinton #AIReasoning #NeuralNetworks #EmilyBender #ReinforcementLearning #AIHype

Your "Agentic AI" is a Ferrari without wheels. Stop making engine noises in the garage. Without "Golden Context," you're just driving on messy data. We expose the full reality check in our #CRMKonvo.

https://zurl.co/HudYC

#AIhype #GoldenContext

"AI models have one undeniable virtue: the increase in speed and efficiency with which they can carry out tasks that were once the province of human beings. Language models can produce functional text for a wide range of contexts, while image generation models are giving us the capability to render into existence whatever image or video takes our fancy. This is widely taken as clear evidence of the benefits of AI. For Mumford, this type of thinking is precisely the problem. The myth of the machine is dehumanizing because it subordinates human values to machine values: speed and efficiency.

The most striking evidence of the myth’s cultural pervasiveness is that many avid accelerationists do not deny that AI could mean the end of humanity. They merely differ from the doomers in believing that this risk is necessary—even desirable—to achieve the spectacular increases in efficiency and productivity promised by AGI. Mumford foresaw this extreme endpoint. “The myth of the machine,” he wrote, “the basic religion of our present culture, has so captured the modern mind that no human sacrifice seems too great provided it is offered up to the insolent Marduks and Molochs of science and technology.”

Those branded as skeptics or doomers also still accept the premises of the myth of the machine. The stated aim of many organizations concerned with avoiding the worst AI outcomes is that we should “realize the benefits while mitigating the risks” of the technology. Mumford would argue the first half of this statement concedes too much, accepting the basic premise of the myth of the machine while presenting the task as removing the obstacles to realize its benefits. Many skeptics also share a basic misanthropic premise of machine superiority, focusing as they do on the biased, irrational, and flawed nature of human beings that needs machinic augmentation."

https://www.compactmag.com/article/ai-and-the-myth-of-the-machine/

#AI #Neoluddism #AIBoosters #AIHype #AIDoomers #GenerativeAI #Mumford #STS #MediaEcology

Global equities closed 2025 strong, but the rally was narrow and uneven. Moreover, India was among the weakest major markets. As 2026 begins, can easing global headwinds and better earnings help Indian equities recover? Today’s Number Theory explores this.

Read on free HT news app: https://www.hindustantimes.com/editors-pick/what-will-the-markets-bring-in-2026-for-india-number-theory-101767327504906.html

#Markets #Sensex #BSE #AIhype #SP500 #NASDAQ #Earnings #MastIndia #India @mastodonindians

Tesla ends 2025 struggling with falling demand, aging models, shrinking margins, and delayed AI ambitions like robotaxis and Optimus. Competition especially from Chinese EV makers is surging, and the end of U.S. tax credits hit sales hard. Energy storage is growing, but not enough to offset weakening automotive cash flow.

#Tesla #EVSlowdown #MarketReality #AIHype #Margins #Competition #TECHi

Read Full Article Here :- https://www.techi.com/tesla-stock-rises-on-market-sentiment/

The farther away I get from having read the book The #AI Con: How to Fight Big Tech’s Hype and Create the Future We Want Book by #AlexHanna and #EmilyM.Bender, the more susceptible get to #AIhype.

The farther away I get from having read the book The #AI Con: How to Fight Big Tech’s Hype and Create the Future We Want Book by #AlexHanna and #EmilyM.Bender, the more susceptible get to #AIhype.

"My gut instinct is that this is an industry-wide problem. Perplexity spent 164% of its revenue in 2024 between AWS, Anthropic and OpenAI. And one abstraction higher (as I'll get into), OpenAI spent 50% of its revenue on inference compute costs alone, and 75% of its revenue on training compute too (and ended up spending $9 billion to lose $5 billion). Yes, those numbers add up to more than 100%, that's my god damn point.

Large Language Models are too expensive, to the point that anybody funding an "AI startup" is effectively sending that money to Anthropic or OpenAI, who then immediately send that money to Amazon, Google or Microsoft, who are yet to show that they make any profit on selling it.

Please don't waste your breath saying "costs will come down." They haven't been, and they're not going to.

Despite categorically wrong boosters claiming otherwise, the cost of inference — everything that happens from when you put a prompt in to generate an output from a model — is increasing, in part thanks to the token-heavy generations necessary for "reasoning" models to generate their outputs, and with reasoning being the only way to get "better" outputs, they're here to stay (and continue burning shit tons of tokens).

This has a very, very real consequence."

https://www.wheresyoured.at/why-everybody-is-losing-money-on-ai/

#AI #GenerativeAI #BusinessModels #LLMs #Chatbots #AIHype #AIBubble

Ein besserer Begriff für #AI ist #SALAMI ("Systematic Approaches to Learning Algorithms and Machine Inferences"), habe ich gerade gelernt.
Quelle: https://pluralistic.net/2023/03/09/autocomplete-worshippers/#the-real-ai-was-the-corporations-that-we-fought-along-the-way
#KI #kunstlicheinteligenz #artificialintellgence #aihype #kihype

#TodaysAcronym ☞ #DKAI

🤪 🤖 🤤 🤖 🤪

#DunningKrugerAI

Bots Too Dumb To Know How Dumb They Are

#AI #AIHype

I did a keynote talk yesterday on 'Uses and Misues of genAI'. For fun I did before and after word clouds. This is the 'after' one. The auditorium was a converted iMax cinema so the large text was about 3ft high 😆.
#JobDone #AIHype

A calm dissection of AI hypes by @maggie
https://maggieappleton.com/forest-talk

A few terms to check beforehand:
- cozy web
- human centipede
#aiai
#aihype
(link via @sarajw)

@emilymbender

On the “sparks” paper: https://nitter.net/emilymbender/status/1638891855718002691?s=20​

On the GPT-4 ad copy: https://nitter.net/emilymbender/status/1635697381244272640?s=20​

On “general” tasks: https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/084b6fbb10729ed4da8c3d3f5a3ae7c9-Abstract-round2.html​

Opinions of @emilymbender

nitter.net to protect privacy

#aihype #emilymbender #sparksofagi #agi #gpt4 #nitter #nitternet #nitterdotnet

@emilymbender

On the “sparks” paper: https://nitter.net/emilymbender/status/1638891855718002691?s=20​

On the GPT-4 ad copy: https://nitter.net/emilymbender/status/1635697381244272640?s=20​

On “general” tasks: https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/084b6fbb10729ed4da8c3d3f5a3ae7c9-Abstract-round2.html​

Opinions of @emilymbender

nitter.net to protect privacy

#aihype #emilymbender #sparksofagi #agi #gpt4 #nitter #nitternet #nitterdotnet

@emilymbender

On the “sparks” paper: https://nitter.net/emilymbender/status/1638891855718002691?s=20​

On the GPT-4 ad copy: https://nitter.net/emilymbender/status/1635697381244272640?s=20​

On “general” tasks: https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/084b6fbb10729ed4da8c3d3f5a3ae7c9-Abstract-round2.html​

Opinions of @emilymbender

nitter.net to protect privacy

#aihype #emilymbender #sparksofagi #agi #gpt4 #nitter #nitternet #nitterdotnet

@emilymbender

On the “sparks” paper: https://nitter.net/emilymbender/status/1638891855718002691?s=20​

On the GPT-4 ad copy: https://nitter.net/emilymbender/status/1635697381244272640?s=20​

On “general” tasks: https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/084b6fbb10729ed4da8c3d3f5a3ae7c9-Abstract-round2.html​

Opinions of @emilymbender

nitter.net to protect privacy

#aihype #emilymbender #sparksofagi #agi #gpt4 #nitter #nitternet #nitterdotnet