Scaling Language Models
The discussion highlights the significant performance improvements observed with increasing parameters in language models, particularly with GPT-3 and Wu Dao 2.0. As the gap between artificial and human brain capabilities remains vast, the potential for further scaling up models seems promising, especially given the clear correlation between parameter size and performance gains. Exploring alternative avenues alongside this scaling could also be crucial for achieving human-level language understanding.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 559: GPT-3 for Natural Language Processing — with Melanie Subbiah
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