The importance of AI models is evolving, moving beyond mere technical prowess to encompass their integration into functional products. Matt Rickard's assertion, 'the model is not the product,' has gained traction with the rise of AI chatbots and autonomous agents. For example, having real-time fact-checking capabilities and the ability to control computer systems significantly increase the utility of language models. Innovations such as Butterfly Effect's Manus exemplify this, demonstrating that the true potential of AI lies in its application and operational capacity, not just its foundational model.
The race to build the smartest AI model continues, but success increasingly depends on surrounding technologies and functionalities that enhance the model's practical applications.
Today, the real value lies in what happens around the model, such as integrating LLMs with real-time data and enabling them to perform more complex tasks.
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