Challenges

While compute and algorithms may appear to be the bottleneck for model advancement, that is no longer the case. The focus has shifted from proving that LLMs work to making inference faster and improving output quality.

Topics

• Data curation – automated/manual
• Alignment
• Efficiency
• Evaluation
• Learning without forgetting.
• Continual Training (trading off search, cache, and fresh)