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An Artificial Intelligence Conversation with Andrew Ng
FYI - For Your Innovation
Opportunities Abound in the Application Layer
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The evolution of machine learning (ML) architecture emphasizes the shift of certain functionalities, particularly inference, towards endpoint devices, offering enhanced consumer utility. The discrepancy between training and inference workloads suggests that distinct architectural and software modifications are necessary. As the landscape of MLOps evolves, orchestrating inference and training calls separately is becoming increasingly relevant. The rapid developments in large language models (LLMs) highlight the emergence of new orchestration layers, such as those created by advancements in SOA-MIO applications. With tools like Nanchain and Lamb Index leading in this space, the application layer presents a wealth of opportunities compared to the highly competitive foundation model layer, where significant investments are made. At AI Fund, engagement with corporate partners reveals numerous viable use cases with minimal competition, emphasizing the richness of possibilities within the application layer.
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