L'IA c'est de la merde, épisode trouze-mille-douze :
ChatGPT consomme jusqu'à 25 fois plus qu'une recherche Google.
De plus, beaucoup d'eau est également utilisée pour refroidir les serveurs qui exécutent tous ces logiciels. Après une conversation d'environ 20 à 50 questions, un demi-litre d'eau est partie en vapeur
L'IA devrait consommer deux fois plus d'énergie que la France entière d'ici 2030
there’s a big need for something stronger than #RAG, but more flexible and cheaper than a giant all-knowing #LLM.
A great part about RAG is that it’s just a database. You just issue INSERT/UPDATE and yeah, that’s how you maintain knowledge. No million dollar training process
Ruszyła zbiórka fundacji non-profit @ftdl na dodatkowy sprzęt dla generatora napisów i transkrypcji po polsku 🇵🇱 czyli NapiGen 🚀 oraz kolejnych projektów LLM.
Pomożecie rozwiązać problem braku polskich napisów w większości treści na YouTube i transkrypcji w podkastach?
P.S. Wszystko jest lub będzie open-source, we własnej serwerowni fundacji w Krakowie, na własnym sprzęcie, żadnych "wycieków" na zewnątrz czy "darmowego" douczania amerykańskich korpo ejajów.
Yay, I too got my 7-day suspension badge from Stack Overflow from adding an #LLM#AI disclaimer back after it was first reverted to my four (4) answers!
A study that confirms what I’ve been suspecting for a while: fine-tuning a #LLM with new knowledge increases its tendency to hallucinate.
If the new knowledge wasn’t provided in the original training set, then the model has to shift its weights from their previous optimal state to a new state that has to accommodate both the previous and new knowledge - and it may not necessarily be optimal.
Without a new validation round against the whole previous cross-validation and test sets, that’s just likely to increase the chances for the model to go off the tangent.
I just found out one actually useful use case for #LLM (a.k.a. “AI”).
There is thousands of tonnes of documents from #german#nazi#regime detailing basically everything what happened, who was involved and who participated what and said what.
Feed ALL of that to an LLM and ask it “how can we avoid this happening ever again”. I have a pretty good guess my self but some people aren’t that convinced. Perhaps this is The Key. #history#sciense#neverAgain
(1/2) Prompt Fuzzer - a new open-source project for LLM security 👇🏼
Prompt Fuzzer is a new open-source project that provides a set of functions for assessing the security of GenAI applications. This CLI-based tool enables you to run and test your system prompts to identify security vulnerabilities against potential dynamic LLM-based attacks.
I just issued a data deletion request to #StackOverflow to erase all of the associations between my name and the questions, answers and comments I have on the platform.
One of the key ways in which #RAG works to supplement #LLMs is based on proven associations. Higher ranked Stack Overflow members' answers will carry more weight in any #LLM that is produced.
By asking for my name to be disassociated from the textual data, it removes a semantic relationship that is helpful for determining which tokens of text to use in an #LLM.
If you sell out your user base without consultation, expect a backlash.
What happens when China builds an #LLM? DeepSeek just released v2 of its model, which is open source.
I tried it on deepseek.com. Ask it about Tiananmen square, and the chatbot self-censors its answer while it is generating (that presumably is limited to their deployment). On variations not caught by the filter, it refuses -- and replies in Chinese:
"The content of your question is not in line with the core values of socialism, nor is it in line with China's laws, regulations and policies."
LLMs looting the internet will lead to a significant increase in insularity, barriers to entry, suspicion, and siloing by its users.
Expect to see an increase in invite-only forums and communities which vet everyone who applies for access to make sure they aren’t a scraper in a human suit. An increase in experts refusing to help newbies, for fear of their help being copied, mulched, and resold by massive corporations. A decrease in the “social” part of the net.
Come funzionano gli #LLM, spiegato senza matematica
Da dove proviene l’apparente intelligenza di questi modelli. In questo articolo, cercherò di spiegare in termini semplici e senza utilizzare la matematica avanzata come funzionano i modelli di testo generativi, per aiutarti a pensarli come algoritmi informatici e non come magia.
"When I was asked to beta test its AI research bot, I informed a major legal research provider that it worse than sucked. It was dangerous. Not only did it hallucinate... but it conflated almost all the critical distinctions that make law work. It failed to distinguish between jurisdictions, both states and state and federal, as well as majority, concurrences and dissents. To AI, it was all the same, words about law..."