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.
Would be nice to have a LLM that you can train locally with your organization documentation, to be able to have an interface to easily find that information buried in decades of documents #LLM#MachineLearning#documentation#FOSS
"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..."
Replay Crew! We had a fun romp through tech headlines this week! https://somegadgetguy.com/b/44j
Jack Dorsey is no longer on the board of BlueSky. We're wrapping up the closing arguments in Google's anti-trust case. The Rabbit R1 is an app. Sony's marketing materials for the next XPERIA leak.
And we should probably chat about this next iPad thing-y...
Le thème : les modèles de language et la robotique open hardware. Si ça vous intéresse de découvrir une autre facette que Skynet et la machine à billet,
I just came across this (h/t to Peter Krupa), and it blew my mind. It highlights the problem with LLMs in general with pinpoint accuracy, and wraps it in a well known metaphorical idiom that everyone understands — which instantly becomes a meta reference. …
I created a multi-needle in a haystack test where a randomly selected secret sentence was split into pieces and scattered throughout the document with 7.5k tokens in random places. The task was to find these pieces and reconstruct the complete sentence with exact words, punctuation, capitalization, and sequence. After running 100 tests, llama3:8b-instruct-q8 achieved a 44% success rate, while llama3:70b-instruct-q8 achieved 100%! #LLM#AI#MLhttps://github.com/chigkim/haystack-test
For inference, the best option right now is llama.cpp with quantized LLM in GGUF format. There are several high-lever wrappers around llama.cpp that makes it easy to use: ollama, vllama...
For inference with very big LLM and very small RAM, the only option is airLLM: it's slow, but you can run llama3-70b
For finetuning quantized LLM with LoRA, the only option afaik is also llama.cpp (look for "finetune"). It's a work in progress but usable and promising!
This kind of thing gets me going. These sort of reversals of agency. Also, the idea that things get caused by dreams. There is something in me that wants to explore all these things that don’t fit the not modernity
„Dzieje się tak dlatego, że LLM, niezależnie od tego, jak dobrze wyszkolony, nie potrafi ani abstrahować, ani rozumować jak człowiek. (...) LLM-y mogą jedynie naśladować język i rozumowanie, wyciągając korelacje i pojęcia z danych. Mogą często poprawnie naśladować ludzką komunikację, ale bez umiejętności internalizowania i z powodu olbrzymiego rozmiaru modelu nie ma gwarancji, że ich wybory będą bezpieczne albo etyczne" #ai#llm#wojsko
I really like the convention of using ✨ sparkle iconography as an “automagic” motif, e.g. to smart-adjust a photo or to automatically handle some setting. I hate that it has become the defacto iconography for generative AI. 🙁
Je bosse au 4/5 sur les modèles de langage (LLM, parfois appelées IAs) et à 2/5 sur la robotique open hardware AMA (jlai.lu) French
Hello!...
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After a full year of not thinking about printers, the best printer is still whatever random Brother laser printer that’s on sale.