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Bringing open AI models to the frontier
September 27, 2023
By Mistral AI team
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Generative AI, particularly large language models, is revolutionising content creation, knowledge retrieval, and problem-solving by generating human-quality text, content and commands based on human instructions. In the coming years, generative AI will completely redefine our culture and our lives, the way we interact with machines and with fellows.
As in the previous ages of software, proprietary solutions were developed first—and we’re grateful they revealed the power of generative models to the world. Yet, as with the Web, with web browsers ( Webkit ), with operating systems ( Linux ), with cloud orchestration ( Kubernetes ), open solutions will quickly outperform proprietary solutions for most use cases. They will be driven by the power of community and the requirement for technical excellence that successful open-source projects have always promoted.
At Mistral AI, we believe that an open approach to generative AI is necessary. Community-backed model development is the surest path to fight censorship and bias in a technology shaping our future.
We strongly believe that by training our own models, releasing them openly, and fostering community contributions, we can build a credible alternative to the emerging AI oligopoly. Open-weight generative models will play a pivotal role in the upcoming AI revolution.
Mistral AI’s mission is to spearhead the revolution of open models.
Generative AI needs open models
Working with open models is the best way for both vendors and users to build a sustainable business around AI solutions. Open models can be finely adapted to solve many new core business problems, in all industry verticals—in ways unmatched by black-box models. The future will be made of many different specialised models, each adapted to specific tasks, compressed as much as possible, and connected to specific modalities.
In the open model paradigm, the developer has full control over the engine that powers their application. Model sizes and costs can be adapted to fit specific task difficulty, to put costs and latency under control. For enterprises, deploying open models on one’s infrastructure using well-packaged solutions simplifies dependencies and preserves data privacy.
Closed and opaque APIs introduce well-known technical liabilities, in particular IP leakage risks; in the case of generative AI, it introduces a cultural liability, since the generated content is fully under the control of the API provider, with limited customization capacities. With model weights at hand, end-user application developers can customise the guardrails and the editorial tone they desire, instead of depending on the choices and biases of black-box model providers.