LLAMA 3, the new standard for Open Source LLMs?

Nebuly CTO, Diego Fiori gives his thoughts about Meta's latest LLM - LLAMA 3.

Diego, What separates Llama-3 from the other major models?

"Compared to other Open Source models, I would say the main difference is the amount of data these models are pre-trained on. LLaMA-3 was trained on 15 trillion tokens, which corresponds to approximately 22 billion pages.It's seven times the size of Meta's last model and exceeds the 13 trillion tokens rumored for OpenAI's GPT-4 training set. However, GPT-4 likely still has a significantly higher number of parameters. Generally, a larger set of high-quality tokens correlates with improved model quality."

What made this launch significant?

"There is two main points:- 7B-sized models are the most used today across a broad range of applications due to their manageable size and simplicity in fine-tuning. They can be fine-tuned on a single A100 GPU for downstream applications. Introducing a new state-of-the-art (SOTA) model of this size could enhance model quality across various sectors.- Meta also announced a GPT-4 level model that is currently under training and will be released as open-source later this year. This could become the first open-source model to outperform the best closed-source models. "

Do you see use cases or industries where LLAMA 3 will be most suited for?‍

"Considering its multilingual capabilities, I expect all use cases where an LLM is used to process data from different languages will greatly benefit from the LLaMA update."

Is there something particularly interesting in the LLAMA 3 launch from your personal perspective?‍

"Yes, definitely. This opens up opportunities to improve our own models at Nebuly too. Furthermore, I believe that the release of larger-sized models will be interesting for all companies currently developing AI agents, helping them bring their products to production more quickly."Thank you, Diego!

About Nebuly

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