Open challenges in LLM research

Never before in my life had I seen so many smart people working on the same goal: making LLMs better. After talking to many people working in both industry and academia, I noticed the 10 major research directions that emerged. The first two directions, hallucinations and context learning, are probably the most talked about today. I’m the most excited about numbers 3 (multimodality), 5 (new architecture), and 6 (GPU alternatives).

Related Keywords

Vietnam ,Republic Of ,China ,Guanco ,Aklan ,Philippines ,Kenya ,Bangladesh ,Chinese ,Bangladeshi ,Filipino ,Vietnamese ,Dan Grover ,Jeremy Howard ,Graphcore Ipus ,Google Tpus ,Linus Lee ,Nvidia Ne ,Situatedqa Zhang Choi ,Jerry Liu ,Twitter ,Google ,Nvidia ,Natural Questions ,Retrieval Augmented Generation ,How Language Models Use Long Contexts ,Model Compression ,Designing Machine Learning Systems ,Efficiently Modeling Long Sequences ,Structured State Spaces ,Monarch Mixer ,Ayar Labs ,Luminous Computing ,Generative Agents ,Interactive Simulacra ,Human Behavior ,Reinforcement Learning ,Human Preference ,