In this episode of Artificially Unintelligent, hosts William and Nicolay delve into the intricate world of foundation models in AI. They discuss what these models are – large-scale, machine learning models trained on vast, diverse, and often unlabeled data – and their growing importance in various AI fields. From the complexities of handling unlabeled data to the evolution of foundation models across text, image, and audio domains, the conversation covers a range of topics. They examine models like GPT, Dolly, and Whisper, providing insights into their functionalities and impact. Looking ahead, they speculate on the future of AI, imagining a world with domain-specific AGIs and advanced multimodal models. This episode offers a comprehensive look at foundation models, making it a valuable listen for AI professionals and enthusiasts eager to stay abreast of key developments in the field.
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