3 Std 12 Min.
#48 - The Art of Prompt Engineering with Andrew Mayne (ex-OpenAI Creative Apps and Science Communicator) Multimodal by Bakz T. Future
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- Technologie
Discussing Prompt Engineering and recent OpenAI developments with ex-OpenAI Creative Apps and Scientific Communicator Andrew Mayne
Timestamps:
00:00:00 - Teaser Reel Intro
00:01:01 - Intro / Andrew's background
00:02:49 - What was it like working at OpenAI when you first joined?
00:12:59 - Was Andrew basically one of the earliest Prompt Engineers?
00:14:04 - How Andrew Hacked his way into a tech job at OpenAI
00:17:08 - Parallels between Hollywood and Tech jobs
00:20:58 - Parallels between the world of Magic and working at OpenAI
00:25:00 - What was OpenAI like in the Early Days?
00:30:24 - Why it was hard promoting GPT-3 early on
00:31:00 - How would you describe the current 'instruction age' of prompt design?
00:35:22 - What was GPT-4 like freshly trained?
00:39:00 - Is there anything different about the raw base model without RLHF?
00:42:00 - Optimizations that go into Language models like GPT-4
00:43:30 - What was it like using DALL-E 3 very early on?
00:44:38 - Do you know who came up with the 'armchair in the shape of an avocado' prompt at OpenAI?
00:45:48 - Did you experience 'DALL-E Dreams' as a part of the DALL-E 2 beta?
00:47:16 - How else has prompt design changed?
00:49:27 - How has prompt design changed because of ChatGPT?
00:52:40 - How to get ChatGPT to mimick and emulate personalities better?
00:54:30 - Mimicking Personalities II (How to do Style with ChatGPT)
00:56:40 - Fine Tuning ChatGPT for Mimicking Elon Musk
00:59:44 - How do you get ChatGPT to come up with novel and brilliant ideas?
01:02:40 - How do you get ChatGPt to get away from conventional answers?
01:05:14 - Will we ever get single-shot, real true novelty from LLM's?
01:10:05 - Prompting for ChatGPT Voice Mode
01:12:20 - Possibilities and Prompting for GPT-4 Vision
01:15:45 - GPT-4 Vision Use Cases/Startup Ideas
01:21:37 - Does multimodality make language models better or are the benefits marginal?
01:24:00 - Intuitively, has multimodality improved the world model of LLM's like GPT-4?
01:25:33 - What would it take for ChatGPT to write half of your next book?
01:29:10 - Qualitatively, what would it take to convince you about a book written by AI? What are the characteristics?
01:31:30 - Could an LLM mimick Andrew Mayne's writing style?
01:37:49 - Jailbreaking ChatGPT
01:41:12 - What's the next era of prompt engineering?
01:45:50 - How have custom instructions changed the game?
01:54:41 - How far do you think we are from asking a model how to make 10 million dollars and getting back a legit answer?
02:01:07 - Part II - Making Money with LLM's
02:11:32 - How do you make a chat bot more reliable and safe?
02:12:12 - How do you get ChatGPT to consistently remember criteria and work within constraints?
02:12:45 - What about DALL-E? How do you get it to better create within constraints?
02:14:14 - What's your prompt practice like?
02:15:10 - Do you intentionally sit down and practice writing prompts?
02:16:45 - How do you build an intuition around prompt design for an LLM?
02:20:00 - How do you like to iterate on prompts? Do you have a process?
02:21:45 - How do you know when you've hit the ceiling with a prompt?
02:24:00 - How do you know a single line prompt is has room to improve?
02:26:40 - Do you actually need to know OpenAI's training data? What are some ways to mitigate this?
02:30:40 - What are your thoughts on automated prompt writing/optimization?
02:33:20 - How do you get a job as a prompt engineer? What makes a top tier prompt engineer different from an everyday user?
02:37:20 - How do you think about scaling laws a prompt engineer?
02:39:00 - Effortless Prompt Design
02:40:52 - What are some research areas that would get you a job at OpenAI?
02:43:30 - The Research Possibilities of Optimization & Inference
02:45:59 - If you had to guess future capabilities of GPT-5 what would they be?
02:50:16 - What are some capabilities that got trained out of GPT-4 for ChatGPT?
02:51:10 - Is there any specific capability you could im
Discussing Prompt Engineering and recent OpenAI developments with ex-OpenAI Creative Apps and Scientific Communicator Andrew Mayne
Timestamps:
00:00:00 - Teaser Reel Intro
00:01:01 - Intro / Andrew's background
00:02:49 - What was it like working at OpenAI when you first joined?
00:12:59 - Was Andrew basically one of the earliest Prompt Engineers?
00:14:04 - How Andrew Hacked his way into a tech job at OpenAI
00:17:08 - Parallels between Hollywood and Tech jobs
00:20:58 - Parallels between the world of Magic and working at OpenAI
00:25:00 - What was OpenAI like in the Early Days?
00:30:24 - Why it was hard promoting GPT-3 early on
00:31:00 - How would you describe the current 'instruction age' of prompt design?
00:35:22 - What was GPT-4 like freshly trained?
00:39:00 - Is there anything different about the raw base model without RLHF?
00:42:00 - Optimizations that go into Language models like GPT-4
00:43:30 - What was it like using DALL-E 3 very early on?
00:44:38 - Do you know who came up with the 'armchair in the shape of an avocado' prompt at OpenAI?
00:45:48 - Did you experience 'DALL-E Dreams' as a part of the DALL-E 2 beta?
00:47:16 - How else has prompt design changed?
00:49:27 - How has prompt design changed because of ChatGPT?
00:52:40 - How to get ChatGPT to mimick and emulate personalities better?
00:54:30 - Mimicking Personalities II (How to do Style with ChatGPT)
00:56:40 - Fine Tuning ChatGPT for Mimicking Elon Musk
00:59:44 - How do you get ChatGPT to come up with novel and brilliant ideas?
01:02:40 - How do you get ChatGPt to get away from conventional answers?
01:05:14 - Will we ever get single-shot, real true novelty from LLM's?
01:10:05 - Prompting for ChatGPT Voice Mode
01:12:20 - Possibilities and Prompting for GPT-4 Vision
01:15:45 - GPT-4 Vision Use Cases/Startup Ideas
01:21:37 - Does multimodality make language models better or are the benefits marginal?
01:24:00 - Intuitively, has multimodality improved the world model of LLM's like GPT-4?
01:25:33 - What would it take for ChatGPT to write half of your next book?
01:29:10 - Qualitatively, what would it take to convince you about a book written by AI? What are the characteristics?
01:31:30 - Could an LLM mimick Andrew Mayne's writing style?
01:37:49 - Jailbreaking ChatGPT
01:41:12 - What's the next era of prompt engineering?
01:45:50 - How have custom instructions changed the game?
01:54:41 - How far do you think we are from asking a model how to make 10 million dollars and getting back a legit answer?
02:01:07 - Part II - Making Money with LLM's
02:11:32 - How do you make a chat bot more reliable and safe?
02:12:12 - How do you get ChatGPT to consistently remember criteria and work within constraints?
02:12:45 - What about DALL-E? How do you get it to better create within constraints?
02:14:14 - What's your prompt practice like?
02:15:10 - Do you intentionally sit down and practice writing prompts?
02:16:45 - How do you build an intuition around prompt design for an LLM?
02:20:00 - How do you like to iterate on prompts? Do you have a process?
02:21:45 - How do you know when you've hit the ceiling with a prompt?
02:24:00 - How do you know a single line prompt is has room to improve?
02:26:40 - Do you actually need to know OpenAI's training data? What are some ways to mitigate this?
02:30:40 - What are your thoughts on automated prompt writing/optimization?
02:33:20 - How do you get a job as a prompt engineer? What makes a top tier prompt engineer different from an everyday user?
02:37:20 - How do you think about scaling laws a prompt engineer?
02:39:00 - Effortless Prompt Design
02:40:52 - What are some research areas that would get you a job at OpenAI?
02:43:30 - The Research Possibilities of Optimization & Inference
02:45:59 - If you had to guess future capabilities of GPT-5 what would they be?
02:50:16 - What are some capabilities that got trained out of GPT-4 for ChatGPT?
02:51:10 - Is there any specific capability you could im
3 Std 12 Min.