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#largelanguagemodels

5 posts5 participants0 posts today
Public
Michael Martinez :verified:

Large Language Models do not crawl the Web but apparently the SEO community is now going to tell the world they do.

The credibility of this industry just takes a nosedive every time something new comes along - not because of our ignorance of what is new, but because of the rush to become "expert" in things about which we know virtually nothing.

#seo#searchengineoptimization#llms
Public *
AJ Sadauskas

If you have the time, please watch the clip below.

It's a detailed explanation of how Elon Musk is causing lung disease and death in a mostly black, working class community in Memphis, from pollution from the 35 methane gas turbines powering his AI data centre.

https://www.youtube.com/watch?v=3VJT2JeDCyw

#ClimateChange #ClimateCrisis #ElonMusk #ChatGPT #Tesla #Grok #largelanguagemodels #artificialintelligience #Trump #GlobalWarming #tech #environment

YouTubeElon Musk Built an Al Super Computer in Our Backyard: It's Poisoning UsBy More Perfect Union
Public
.:\dGh/:.

That's it, I'm going against AMD for recommending computers for #AI.

I don't even know how to start running something on their NPU via Linux, or check it's running at all. Windows fares better but it's `llama.cpp` doesn't work there.

So, if you want to run AI on your computer: RTX, Mac, or don't bother at all.

#ML#LLM#LargeLanguageModels
Public
Lin Chiao

#IA #LLM #LargeLanguageModels #DataCenter

Actualmente, debaten si la "IA" reemplazará a los desarrolladores. Aunque a las empresas se les vende como que eso va a pasar, no es lógico. Te explico por qué.

La "IA" no es IA, no razona ni tiene conciencia como un ser humano. Nos da los resultados por una síntesis estadística de una enorme cantidad de recursos (libros, sitios web, código). Éste es el problema principal porque el trabajo del desarrollador es PENSAR en la forma de resolver los problemas y necesidades del software. ¿Cómo va a reemplazar a los desarrolladores si la "IA" no puede pensar?

Lo que la IA podría hacer, quizás con el tiempo, es automatizar la escritura del código, una vez que un ser humano le dicte lo que quiere. Aunque tener una IA que lo escriba por mí podría ser cómodo (si no tuviera que sufrir para que me entienda), igualmente no ahorraría mucho tiempo porque el desarrollador es más lo que piensa que lo que escribe.

Otra forma en que podría ayudar la "IA" es permitiéndonos consultar rápidamente sin tener que buscar en la documentación, pero es peligroso porque la IA a veces da información falsa. Los problemas que puede causar por mentirnos yo preferiría evitarlos simplemente tomándome el tiempo de revisar la documentación, que además va a ser más completa y puedo ver a simple vista en su organización otras cosas que me interesen para mirarlas más tarde. La "IA" ahorraría tiempo en el momento (en el mejor caso) pero a la vez impediría el aprendizaje y detectar cambios en el framework/librería. Entonces, es cuestionable si sería un bien.

Public
N-gated Hacker News

🎩🚀 Ah, the age-old quest for the perfect large language model – because who doesn’t relish the thrill of navigating a labyrinth of jargon just to find out which AI tool will best misinterpret your intent? 🧩 Naturally, this "expert" guide is the Rosetta Stone for anyone who thought choosing an LLM was as simple as picking the least-worst option. 🙃
oblivus.com/blog/choosing-the- #largeLanguageModels #AItools #expertGuide #LLMlabyrinth #techJargon #HackerNews #ngated

oblivus.comOblivus Blog | Aligning LLM Choice to Your Use Case: An Expert’s GuideOblivus Blog | Discover how to choose the best (LLM) for your specific use case. This guide compares top LLMs like GPT-4.5, Claude, Llama, and more, aligning each model’s strengths with real-world applications in AI, coding, content creation, enterprise, and more.
Public
Hacker News

Large Language Models Are More Persuasive Than Incentivized Human Persuaders

arxiv.org/abs/2505.09662

arXiv logo
arXiv.orgLarge Language Models Are More Persuasive Than Incentivized Human PersuadersWe directly compare the persuasion capabilities of a frontier large language model (LLM; Claude Sonnet 3.5) against incentivized human persuaders in an interactive, real-time conversational quiz setting. In this preregistered, large-scale incentivized experiment, participants (quiz takers) completed an online quiz where persuaders (either humans or LLMs) attempted to persuade quiz takers toward correct or incorrect answers. We find that LLM persuaders achieved significantly higher compliance with their directional persuasion attempts than incentivized human persuaders, demonstrating superior persuasive capabilities in both truthful (toward correct answers) and deceptive (toward incorrect answers) contexts. We also find that LLM persuaders significantly increased quiz takers' accuracy, leading to higher earnings, when steering quiz takers toward correct answers, and significantly decreased their accuracy, leading to lower earnings, when steering them toward incorrect answers. Overall, our findings suggest that AI's persuasion capabilities already exceed those of humans that have real-money bonuses tied to performance. Our findings of increasingly capable AI persuaders thus underscore the urgency of emerging alignment and governance frameworks.
#HackerNews#LargeLanguageModels#Persuasion
Public
Jorge Guerra Pires, Ph.D.

It has been about four years since chatGPT was launched. it is less than one decade, but things changed a lot.

We have learnt a lot about chatGPT, its limitations and strenghts. We also had new AIs coming out.

Let's dive into chatGPT current state.

#podcast #chatGPT #machinelearning #artificialintelligence #largelanguagemodels #programming #coding

=

chatGPT: what can we learn from the large language models? | Computational Intelligence

youtube.com/watch?v=Qto391uJNM4

YouTubechatGPT: what can we learn from the large language models? | Computational IntelligenceBy Jorge Guerra Pires, Ph.D.
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