LLM Trade-offs
Ross discusses the inherent trade-offs in new technologies like LLMs, emphasizing the balance between factual accuracy and creative synthesis. He reflects on the evolution of these models and their reputational challenges, particularly for larger organizations. Nathan highlights the significance of understanding the latent space in scientific language models, underscoring the need for better representations of scientific information.In this clip
From this podcast
Interconnects Audio
Interviewing Ross Taylor on LLM reasoning, Llama fine-tuning, Galactica, agents
Related Questions
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses as discussed in the episode "Neurosymbolic AI in Search with Professor Laura Dietz - Weaviate Podcast #49!" and the clip "Knowledge Graph Queries"?
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses as discussed in the episode 'Neurosymbolic AI in Search with Professor Laura Dietz - Weaviate Podcast #49!' and the clip 'Knowledge Graph Queries'?
What's your opinion on using large language models (LLMs) for scientific research, especially for generating new ideas for hypotheses as discussed in the episode Neurosymbolic AI in Search with Professor Laura Dietz - Weaviate Podcast #49! and the clip Knowledge Graph Queries?