It is fascinating to see AI generated conversations like these and when it says 'let's take a break or take a minute to digest', -- it's just awesome. Hard to believe, this conversation is inherently synthetic in nature !!
As an analyst, I used prompt to support the design of problem questions for digital transformation it has helped me to collate the ideas and successful implement it as part of the scope of my work. Thank you for all the work this week.
Thanks for the podcast! Basically, the more predictable the prompt is the better the answer. Kind of guiding the LLM to give the best answer possible...
Anothe Great podcast. Could be better with audio-visuals to provide emphasise. a picture is worth a thousand words and multi-modal LLMs could be used to get visual outputs from audio inputs.
Whitepaper Companion Podcast - Prompt Engineering The podcast episode dives into prompt engineering, emphasizing its role in effectively interacting with large language models (LLMs). The discussion is based on Lee Boonstra's whitepaper, which outlines various techniques to create effective prompts, catering to both novices and more experienced users. The importance of understanding LLMs' behavior, various prompting techniques like zero-shot, one-shot, and advanced methods such as system and role prompts are highlighted. The hosts also touch on the ethical implications and the responsibility that comes with using these advanced tools. Key Points: Basics of Prompt Engineering The episode introduces that prompt engineering is essential for leveraging the capabilities of large language models (LLMs). The right prompts guide an LLM in generating desired outputs, much like giving clear directions to a friend. Understanding LLM Behavior A core tenet of prompt engineering is comprehending how LLMs function as prediction machines. Crafting effective prompts involves considering the model's quirks, the length and structure of prompts, and the context. Importance of Experimentation Listeners are encouraged to engage in trial and error, continually refining their prompts through experimentation. This iterative process is vital for achieving optimal results. Prompting Techniques Explained The episode discusses various prompting methods, including zero-shot and one-shot prompting, as well as advanced techniques such as system prompts, role prompts, and contextual prompts, each serving different purposes. Advanced Techniques More sophisticated techniques like step back prompting and Chain of Thought (CoT) prompting are explained, which encourage LLMs to consider broader contexts or demonstrate their reasoning process for improved outputs. Ethical Considerations The hosts emphasize the ethical responsibility underlying prompt engineering, advocating for thoughtful use of LLM technology to benefit society and prevent misuse. Multimodal Prompting They introduce the concept of multimodal prompting, suggesting future possibilities that integrate different types of input (like images and audio) to enhance LLM capabilities, exemplified by the new Gemini Vision model. Collaborative Prompt Engineering The episode concludes by stating that prompt engineering should not be a solitary activity, suggesting collaboration and sharing ideas among multiple users to refine techniques.
Great, the future of LLM is in the hands of the people who are shaping this technology, The Prompt Engineers, use your knowledge wisely by building things that are beneficial not harmful. I Like this.
I like how the podcast speakers are directed to take break, announce their come back, wrap up mentions, etc. I assume its using Audio Overview Custom Instructions. Some words and acronyms are still messed up but I definitely love were this technology is going.
It is fascinating to see AI generated conversations like these and when it says 'let's take a break or take a minute to digest', -- it's just awesome. Hard to believe, this conversation is inherently synthetic in nature !!
Creating the right prompt for the LLM to generate the accurate and best answers is a great skill to have. I'm taking this seriously
I appreciate the comments on ethics/fairness/responsibility these series of podcasts mention at the end of each episode.
As an analyst, I used prompt to support the design of problem questions for digital transformation it has helped me to collate the ideas and successful implement it as part of the scope of my work. Thank you for all the work this week.
Thanks for all the podcasts to let us learn about llm's stuff.
Thanks for the podcast! Basically, the more predictable the prompt is the better the answer. Kind of guiding the LLM to give the best answer possible...
Thanks to these beautiful podcasts, these underlying technical concepts are beginning to sink.
Real exciting... Systematic training of the models getting fine tuned with the prompt engineering techniques
First podcast was engaging, somehow I don't engaged in this podcast even after reading whitepaper.
Prompt Engineering the human language that is changing the way we see programming and coding
Anothe Great podcast. Could be better with audio-visuals to provide emphasise. a picture is worth a thousand words and multi-modal LLMs could be used to get visual outputs from audio inputs.
Whitepaper Companion Podcast - Prompt Engineering
The podcast episode dives into prompt engineering, emphasizing its role in effectively interacting with large language models (LLMs). The discussion is based on Lee Boonstra's whitepaper, which outlines various techniques to create effective prompts, catering to both novices and more experienced users. The importance of understanding LLMs' behavior, various prompting techniques like zero-shot, one-shot, and advanced methods such as system and role prompts are highlighted. The hosts also touch on the ethical implications and the responsibility that comes with using these advanced tools.
Key Points:
Basics of Prompt Engineering
The episode introduces that prompt engineering is essential for leveraging the capabilities of large language models (LLMs). The right prompts guide an LLM in generating desired outputs, much like giving clear directions to a friend.
Understanding LLM Behavior
A core tenet of prompt engineering is comprehending how LLMs function as prediction machines. Crafting effective prompts involves considering the model's quirks, the length and structure of prompts, and the context.
Importance of Experimentation
Listeners are encouraged to engage in trial and error, continually refining their prompts through experimentation. This iterative process is vital for achieving optimal results.
Prompting Techniques Explained
The episode discusses various prompting methods, including zero-shot and one-shot prompting, as well as advanced techniques such as system prompts, role prompts, and contextual prompts, each serving different purposes.
Advanced Techniques
More sophisticated techniques like step back prompting and Chain of Thought (CoT) prompting are explained, which encourage LLMs to consider broader contexts or demonstrate their reasoning process for improved outputs.
Ethical Considerations
The hosts emphasize the ethical responsibility underlying prompt engineering, advocating for thoughtful use of LLM technology to benefit society and prevent misuse.
Multimodal Prompting
They introduce the concept of multimodal prompting, suggesting future possibilities that integrate different types of input (like images and audio) to enhance LLM capabilities, exemplified by the new Gemini Vision model.
Collaborative Prompt Engineering
The episode concludes by stating that prompt engineering should not be a solitary activity, suggesting collaboration and sharing ideas among multiple users to refine techniques.
Prompt Engineering- a way to guide AI in understanding and responding more accurately to human language.
This podcast is more cool than real ones.
Great, the future of LLM is in the hands of the people who are shaping this technology, The Prompt Engineers, use your knowledge wisely by building things that are beneficial not harmful. I Like this.
I like how the podcast speakers are directed to take break, announce their come back, wrap up mentions, etc. I assume its using Audio Overview Custom Instructions. Some words and acronyms are still messed up but I definitely love were this technology is going.
This is Notebooklm it has podcast generation based on sources.
Beautifully explained
the art of asking the right questions
Great podcast and amaze to see AI generated content close or better than humans.
Great podcast. Thanks!
Nice podcast! Thanks for sharing the same!
Prompt Engineering very well explained.
Amazing Podcast!
Oh my God. This is incredibly excellent
its really great podcast. Thanks for it.
Nice done. I love it.
Thank you for this thoughtful podcast.
Great podcast.. Thanks very much
This is amazing! They need to work on the tone. They sound a bit monotone, but an amazing conversation!
Thanks for the lesson.
Thanks for this lesson
Great explanations
Amazing! AI creating content of how-to AI, it's voices, and it seems that creates its own comments.
That's amazing
great stuff.........thanks
amazing
Thanks❤
This is great
Crisp introduction to prompt engineering
wondering how nicely these AI spocs mention "Boonstra" says this and that...Boonstra is actually the expert host in upcoming sessions.
future is exciting with AI
Great !
informative
HELLO❤ BRASIL🇧🇷🌎🤳
Assignment anyone?
I also want.If you get to know then reply here.
This sounds like it was AI generated :)
It's an AI that can take a document and create a podcast from it. Quite efficient and interesting . They highlight on key points of the paper.
seems more like LLMs teaching LLMs...
I'd focus on personal gain. Duh! Who wouldn't.
this is second video to watch
interesting
Great!