Instruction Tuning, Prompt Engineering and Self Improving Large Language Models | Dr. Swaroop Mishra

Jay Shah Podcast

Swaroop is a research scientist at Google-Deepmind, working on improving Gemini. His research expertise includes instruction tuning and different prompt engineering techniques to improve reasoning and generalization performance in large language models (LLMs) and tackle induced biases in training. Before joining DeepMind, Swaroop graduated from Arizona State University, where his research focused on developing methods that allow models to learn new tasks from instructions. Swaroop has also interned at Microsoft, Allen AI, and Google, and his research on instruction tuning has been influential in the recent developments of LLMs. Time stamps of the conversation: 00:00:50 Introduction 00:01:40 Entry point in AI 00:03:08 Motivation behind Instruction tuning in LLMs 00:08:40 Generalizing to unseen tasks 00:14:05 Prompt engineering vs. Instruction Tuning 00:18:42 Does prompt engineering induce bias? 00:21:25 Future of prompt engineering 00:27:48 Quality checks on Instruction tuning dataset 00:34:27 Future applications of LLMs 00:42:20 Trip planning using LLM 00:47:30 Scaling AI models vs making them efficient 00:52:05 Reasoning abilities of LLMs in mathematics 00:57:16 LLM-based approaches vs. traditional AI 01:00:46 Benefits of doing research internships in industry 01:06:15 Should I work on LLM-related research? 01:09:45 Narrowing down your research interest 01:13:05 Skills needed to be a researcher in industry 01:22:38 On publish or perish culture in AI research More about Swaroop: https://swarooprm.github.io/ And his research works: https://scholar.google.com/citations?user=-7LK2SwAAAAJ&hl=en Twitter: https://x.com/Swarooprm7 About the Host: Jay is a PhD student at Arizona State University working on improving AI for medical diagnosis and prognosis. Linkedin: https://www.linkedin.com/in/shahjay22/ Twitter: https://twitter.com/jaygshah22 Homepage: https://www.public.asu.edu/~jgshah1/ for any queries. Stay tuned for upcoming webinars! ***Disclaimer: The information in this video represents the views and opinions of the speaker and does not necessarily represent the views or opinions of any institution. It does not constitute an endorsement by any Institution or its affiliates of such video content.***