Published Jul 5, 2023
Ep 11: Stanford Professor Tatsu Hashimoto on AI Biases and Improving LLM Performance
Stanford Professor Tatsu Hashimoto delves into the future of AI language models, examining their specialization versus centralization, while offering insights on compute efficiency, AI biases, academic teaching strategies, and the ethical challenges of model performance, highlighting the surprising capabilities of smaller models.
Topics covered
Popular Clips
Episode Highlights
Related Episodes
Ep 18: LlamaIndex CEO Jerry Liu on Trends in LLM Applications
Answers 383 questions
Ep 4: Fixie.ai CEO Matt Welsh on How LLMs Will Change the Way We Work
Answers 383 questions
How to Think about Building an AI Startup in 2023
Answers 383 questions
Bonus Episode: Sam Altman (CEO, OpenAI) Talks GPT-4o and Predicts the Future of AI
Answers 383 questionsTrends in LLM Applications that Every AI Engineer Should Know
Answers 383 questions
Ep 22: Notion AI Engineer Linus Lee: Behind the Scenes of Notion AI
Answers 383 questionsLeading AI Scientist Discusses Elon Musk, Thought Cloning, and Open-Source Models
Answers 383 questions
Ep 36: Behance Founder Scott Belsky on How AI Will Transform Creative Workflows
Answers 383 questions
Ep 40: CEO of Speak.com Connor Zwick on How AI Will Change the Way we Learn
Answers 383 questions
