Buzzy Startup Just Uploaded an AI Model Into a Torrent Link That Beats the GPT-3.5 โ€“ The Open News

Some AI companies seem content to simply throw their latest offerings into the digital void, akin to a pirate ship unloading dead weight, while most of them are eagerly revealing their latest algorithms through blog posts and press tours. Mistral is a French AI startup that falls into the latter category. Over the weekend, Mistral posted a nondescript Torrent link to X containing its latest large language model, without any explanation.

Mistral has been making waves with his fast, effective LLMs and his happy-go-lucky hacker mentality. He recently raised $415 million in a series A funding round and is currently valued at $2 billion. The memes and praise for X emerged in response to the company's abrupt announcement of its new show. One commenter wrote: โ€œNo blog, no sizzle, no description; just a torrent with the model filesโ€ฆ Mistral understands that his main audience is engineers and he knows their erogenous cultural zones.โ€

The program, known simply as Mixtral-8x7B, received additional details in a blog post published by the company on Monday, the day after its first announcement. Benchmarks published in that blog post show that Mistral's algorithm performs better than some of its American rivals, such as OpenAI's GPT-3.5 and Meta's Llama 2 family. Online users seem to agree that Mistral's new algorithm is really great. Nowadays many people brag about how fast and fun the program is.

Unlike the ironically named OpenAI, which kept its most recent LLMs closed source and consequently sparked some backlash, Mixtral-8x7B is open source, which is an added benefit. In fact, Mistral is committed to making all of its AI software open source, placing it squarely on one side of the unfolding culture war within the AI โ€‹โ€‹sector. Arthur Mensch, CEO and co-founder of Mistral AI, recently commented on this choice, stating that his organization was dedicated to following "an open, responsible and decentralized technology approach."

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