As I reported last month, Microsoft has entered into a $2.1 billion partnership with Mistral, a startup known for its development of the Mistral AI, a technology comparable in performance to GPT-4. This collaboration aims to drive the adoption of artificial intelligence across Europe, leveraging the Microsoft Azure AI platform to make Mistral AI accessible to a broader audience. Despite this significant partnership, Mistral has made it clear that it will not deviate from its open-source roots, emphasizing the importance of transparency and accessibility in the development of AI technologies.
Open Source Commitment
In light of the partnership, there have been concerns regarding the future of Mistral AI's open-source model. However, Mistral's co-founder, Arthur Mensch, has told Le Monde the startup's dedication to maintaining an open-source approach. Mensch articulated the startup's strategy, stating that commercial activities would support the expensive research required for further model development, but the commitment to open source remains unwavering. This dual-product strategy aims to balance the need for funding with the ethos of transparency and community access that open source embodies.
Community Reactions and Transparency Concerns
The announcement has sparked a mix of reactions within the tech community, particularly among users on Reddit. Opinions on the social media network range from thinking Microsoft is using Mistral to gain more power over OpenAI. Some have called for Mistral to demonstrate its commitment to open source principles more concretely, such as by releasing research papers and model weights. The European Commission is also looking into the deal to ensure it does not break competition laws.
There's a sentiment that while the company professes transparency, actions—or in this case, tangible releases—would speak louder than words. Critics argue that even basic disclosures, such as the size of closed models, would go a long way in demonstrating Mistral's commitment to openness. The demand for full research papers and model weights remains a contentious point, reflecting broader concerns about the balance between commercial success and open-source ideals in the AI industry.
