Former Google Director explains the major AI Prompting techniques

Join us as we review various LM Prompting techniques. Get ready for an in-depth exploration of groundbreaking techniques such as Chain of Thought, complexity based, lease to most, and much more! We also uncover the pros and cons of Greedy Decoding and highlight the impact of the voting mechanism in AI.
Time Codes:
- 00:00:30 - Motivation behind creating the LM Prompting Heuristics guide.
- 00:01:27 - Chain of Thought technique
- 00:02:35 - Zero Shot technique
- 00:03:30 - Explanation of Self Consistency and its role in selecting the most likely answer.
- 00:06:00 - Explanation of the Greedy Decoding method and its limitations.
- 00:08:30 - Overview of the Self Consistency process and how multiple samples contribute to the final answer.
- 00:11:00 Complexity Based Prompting
- 00:12:16 - Merging complexity ranking and weighted voting
- 00:15:00 - Generated knowledge
- 00:17:00 - Least to most method
- 00:20:12 - Concept introduction by Jordan Thibodeau
- 00:21:00 - Jordan's project planning tips
- 00:22:03 - Re-prompting technique
- 00:22:59 - Jordan's wish for better A/B testing
- 00:23:00 - Tree of Thoughts
- 00:27:00 - Jordan's views on compute resources
- 00:27:25 - DeepMind's tree-based decisions by Joe Ternasky
- 00:30:30 - The role of multi-path reasoning
- 00:32:20 - Automatic Prompt Engineer (APE) - Finding the best prompts
- 00:35:00 - Balancing prompt latency and token cost
- 00:35:40 - Increasing prompt complexity
- 00:36:05 - The importance of intermediate steps
RUclips Hashtags:
#AIPrompts #chatgpt #ai #openai #claude #google #facebook #meta #chatgpt #claude2