
New names: Kimi K3, Llama, Nemotron, Mistral, Cohere, Deepseek, Phi-4 – these are just a few of the fast-growing open source models from major AI providers. These systems threaten the business models and financial plans of OpenAI, Anthropic, Google, and X.ai. They perform at levels close to Frontier models and the can run up to five-times cheaper on a variety of hardware platforms. What is the disruptive impact of these open source LLMs and how does this impact your AI investments? As you’ll hear in the podcast, Open Source unleashes the opportunity for lower cost AI solutions and more vertical, specialized, application-focused solutions we need. And the business model for these systems moves away from the massive investments of the Frontier providers. The result is more complicated than “open means control.” Model tuning, performance, and optimization could be in your future – as AI moves from a platform to a true layered product set we can use as we need. Lots to learn about here, let us know if you have any questions. Additional Information What’s the difference between closed, open source, and open-weight AI? A researcher explains What Is Open-Weights A.I.? Comparison of Open Source Models
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