Why Open Source Models Might Just Win The AI & LLM Race
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Why Open Source Models Might Just Win The AI & LLM Race
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In this episode, Jonathan and I dive into the rapidly evolving world of open source AI models.
We explore why the industry is seeing a significant shift toward "open weight" models like Meta’s Llama / Meta AI (the names are changing rapidly) and China’s DeepSeek, particularly as businesses grapple with the "token budget crisis" where annual AI spend is being exhausted in mere weeks.
I argue that open source is not just a cost-saving measure but a strategic move for any leader who wants to maintain control over their data and their tech stack as venture capital subsidies for AI begin to dwindle.
The discussion highlights the trade-offs involved, including the critical need for governance.
While open source models offer incredible flexibility, they also require a "Verify and Validate" (The Two Vs) approach to manage potential biases and ensure output quality.
Whether you are a startup building a new product or an SMB to enterprise leader looking to optimise operations, this episode provides a roadmap for why and how to start integrating open source into your AI portfolio.
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