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Why are we still stuck in the dark ages of AI tuning? The new Parameter Efficient Fine-Tuning (PEFT) method promises to revolutionize how we customize LLMs by tweaking just a fraction of parameters. Sounds great, right? But let’s be real—why are we celebrating a process that should have been standard ages ago?

Isn’t it ridiculous that we need a fancy term for optimizing performance without starting from scratch? It’s like putting a new coat of paint on a rusty old car and calling it a brand new ride!

The tech world is moving faster than a kid on a sugar rush, yet we still struggle with efficiency. Can we please wake up and start utilizing these breakthroughs properly?

Check out the article and let’s hope for a future where we don’t need to reinvent the wheel every time.

https://blog.octo.com/fine-tuning-d'un-llm-avec-la-methode-peft--theorie
#AI #MachineLearning #PEFT #TechCritique #Innovation
Why are we still stuck in the dark ages of AI tuning? The new Parameter Efficient Fine-Tuning (PEFT) method promises to revolutionize how we customize LLMs by tweaking just a fraction of parameters. Sounds great, right? But let’s be real—why are we celebrating a process that should have been standard ages ago? Isn’t it ridiculous that we need a fancy term for optimizing performance without starting from scratch? It’s like putting a new coat of paint on a rusty old car and calling it a brand new ride! The tech world is moving faster than a kid on a sugar rush, yet we still struggle with efficiency. Can we please wake up and start utilizing these breakthroughs properly? Check out the article and let’s hope for a future where we don’t need to reinvent the wheel every time. https://blog.octo.com/fine-tuning-d'un-llm-avec-la-methode-peft--theorie #AI #MachineLearning #PEFT #TechCritique #Innovation
BLOG.OCTO.COM
Fine-Tuning d’un LLM avec la méthode PEFT : Théorie
La méthode de Parameter Efficient Fine-Tuning (PEFT) révolutionne la personnalisation des modèles LLM. En ajustant uniquement une fraction de leurs paramètres, PEFT permet d'optimiser la performance des modèles existants de manière plus rapide et éco
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