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Home > Briefs > Mistral CEO confirms ‘leak’ of new open source AI model nearing GPT-4 performance

Mistral CEO confirms ‘leak’ of new open source AI model nearing GPT-4 performance

The past few days have been a wild ride for the growing open source AI community — even by its fast-moving and freewheeling standards. Here’s the quick chronology: on or about January 28, a user with the handle “Miqu Dev” posted a set of files on HuggingFace, the leading open source AI model and code sharing platform, that together comprised a seemingly new open source large language model (LLM) labeled “miqu-1-70b.” The HuggingFace entry, which is still up at the time of this article’s posting, noted that new LLM’s “Prompt format,” how users interact with it, was the same as Mistral, the well-funded open source Parisian AI company behind Mixtral 8x7b, viewed by many to be the top performing open source LLM presently available, a fine-tuned and retrained version of Meta’s Llama 2. The same day, an anonymous user on 4chan (possibly “Miqu Dev”) posted a link to the miqu-1-70b files on 4chan, the notoriously longstanding haven of online memes and toxicity, where users began to notice it. Some took to X, Elon Musk’s social network formerly known as Twitter, to share the discovery of the model and what appeared to be its exceptionally high performance at common LLM tasks (measured by tests known as benchmarks), approaching the previous leader, OpenAI’s GPT-4 on the EQ-Bench. Quantization in ML refers to a technique used to make it possible to run certain AI models on less powerful computers and chips by replacing specific long numeric sequences in a model’s architecture with shorter ones. Users speculated “Miqu” might be a new Mistral model being covertly “leaked” by the company itself into the world — especially since Mistral is known for dropping new models and updates without fanfare through esoteric and technical means — or perhaps an employee or customer gone rouge.

Full story : Mistral CEO confirms ‘leak’ of new open source AI model nearing GPT-4 performance.