Research Funding Allocation in the Deep Learning Era
Imagine you are an AI research lab director in the mid-2010s. You have just developed a breakthrough neural network model that generates remarkably coherent text. You have limited funding remaining for the project. Would you prioritize investing in (A) refining the model's internal structure and training process, or (B) designing more intricate and computationally expensive search algorithms to generate text from the model? Justify your decision based on the prevailing research trends of that period.
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Ch.5 Inference - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Application in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
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Renewed Importance of Inference with the Rise of LLMs
As deep neural network models grew significantly more powerful and capable of generating high-quality outputs on their own, what was the resulting effect on the research community's focus regarding the search procedures used to generate those outputs?
Model Capability vs. Search Algorithm Complexity
Research Funding Allocation in the Deep Learning Era