Training Efficiency Explained
Roland highlights the stark difference in training efficiency between RNNs and transformers, emphasizing that while RNNs can capture language effectively, their training time is prohibitively long. He suggests that an LSTM-based model could potentially match or exceed the performance of top-tier transformers if given an impractical amount of time to train. The conversation underscores the dominance of parallel processing in modern AI development.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
What’s Next in LLM Reasoning? with Roland Memisevic - 646
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