What Is Prompt Engineering?

okay hello hello Brian here hope everything's going well this is an interesting topic that has stuck out to me uh which is this idea of prompt engineering and the question I'm asking in this video is what is prompt engineering and the first I had thought about this before but then sort of formalized in Clarity uh maybe importance and surface of mind uh with this article from TechCrunch where it talked about a company named prompt base which I do have right here and I'll talk about in a second um which is already charging so it's basically built a Marketplace um to allow you to create better prompts specifically they're looking at dally right now and then gpt3 but are planning to expand to other platforms and those other platforms could be ones that you know we've talked about in previous videos mid-journey cohere AI 20 21 Labs like these different um sort of versions of large language models which then are typically taking place to do language generation tasks and so um what's really interesting here and what some of the challenges is that these companies are very these models are part of me are very expensive to build millions of dollars of training scraping data properly from the web uh compiling all that in together to then build these models continuing uh you know so top talent engineering lots of data lots of processing and then ongoing optimization management feedback loop feedback loop et cetera et cetera so adequate level expensive to do and then what this means is there's a trickle-down effect that trickle-down effect leads to basically there being it expensive to interact with so I should you know if I was a smart guy I would say here's the exact cost per uh um uh interaction I know for Dali for example as they've released into more of a public beta open Beta it's like 15 I believe for every 115 credits and uh from doing some tests across uh gpt3 early early stage also had you know what to me was a pretty pretty high price point for those interactions and then I've seen the same thing with coherent the challenge I think is you know we know how much work it was we know how much it trained uh you know how much cost to train this but the challenge is is that a lot of the results that are coming out of these systems are relatively unpredictable uh sometimes not valuable sometimes completely abstract ridiculous or you know just it's just useless I I basically and as a company because if you haven't built these systems yourself you are then paying for each call and so the idea here is that if you're paying for this and it is relatively expensive or you're doing high volume that you need to engineer these prompts these instructions that you put into these uh language generation systems into these big models to get more predictable reliable valuable uh responses and as a lot of these things do come out of open or sort of come into private license use whether it's uh costs coming and we are now seeing open source models I talked about Bloom I talked about other um you know areas where uh sort of Open Source versions of these are emerging and so maybe there is some uh you know uh lessening of the cost but maybe you need to want to run that yourself or or train on top of it generally there's going to be engineering Talent OR processing Talent OR server or server cost throughout this entire process and so the shift here that's going to happen what what this is going to drive towards is like uh you know refinement of the prompts that we're doing to make more business use practical value um outputs and I think you know I'm I'm I haven't been playing around as much with gpd3 just because uh you know in general I haven't found that much use from it I know there's a great company copy Ai and a couple you know ones that have built upon this to generate it around marketing copy all this stuff but in my mind I don't really see the value uh of this yet and I also have some skepticism about using uh that kind of content on my articles or on a website uh knowing that for example Google is looking across the web trying to find where people are using this penalizing it and then sharing that it's against the terms of service and so for me I've seen some people say hey it's really good for thinking of creatives or campaigns and all that stuff I haven't been as sold on that generation side of gpt3 I think classification and in NLP is much more practical and valuable and relevant in today's world not saying that that is going to change that's probably not going to change or that that probably is going to change and evolve as image generation as language generation uh gets better and so you know I the question is and I think people some people are sort of laughing at what prompt base is and then other people's talking about sort of the ethics and uh you know if this is you know a good thing uh Etc et cetera but um I've already seen whether it's in the mid-journey Discord or forums online on Reddit talking about ah if you add this to a prompt whether it's gpd3 or dally we're one of these other ones you actually get a more realistic say with the dolly a more realistic image or uh you can actually what what they've done here is you you actually can make custom emojis or you can do uh you know product basically product um uh ones that are much more maybe practical or use case and you can imagine and then create your own product um you know with these and and while there is a level of unpredictability you're sort of building some parameters around that prompt that you're doing to put it into uh a case that then allows you to have some predictability and output that you're looking for and one of the ones that sticks out to me was um I was doing Pokemon cards or and when I did Pokemon cards I could basically stack a bunch of attributes of characters or design or whatever it was into it and it but it would put it into the format of Pokemon cards and so the actual output in the end was somewhat predictable I would say still lots of edge cases around it but by putting it in that package it actually had some more uh of a refined use case for me even you know even questioning how useful that is and I've seen cohere do this with some magic I believe Magic the Gathering cards Etc et cetera so there is ways to sort of engineer these prompts that allow you to then uh make these predictions you can see you know here's this some about aerial photography nature sunsets I had done one uh a video on YouTube on my Channel about from the perspective of when I realized if I could type from the perspective of a bird from the perspective of ant from the perspective of a human you could actually get different levels of sight so if you're borrowed looking at the same tree you're looking at above where if you're an ant you're looking up and so that part was sort of a a prompt that came to me just as an idea and then I realized if added to the dowel image generation would allow you to have this more predictable output so people are already selling on this you can actually click so I had clicked on for example tiny planets and then they want this I have to register and it looks like you know they've got some they're early so they're very early in this stage but I believe that this is actually going to be a demand uh this there's going to be a market for this so the revenue split is 80 of every sale prompt base takes a 20 fee and then uh and what people are saying is hey maybe there's a way that people actually get paid for discovering and debugging and figuring out what prompts are valuable and then selling it in a different ways so I'm I this this again this story stuck out to me and I'm I'm really fascinated to watch this as it grows and I think people might laugh at this right now but I do believe in this future of prompt engineering I think there's a huge use case for this in need and I do believe in this uh you know prediction that there are going to be a lot more um sort of large language models and image generation and language generation systems that are being used uh and and I think we're just at the very early stage of discovering how can we best uh create you know sometimes just works of art but in other cases uh reliable uh business friendly business valuable um uh outputs uh within this so I have a bunch of links here as always I love my links the question today really is just like what what is prompt engineering and and you know from you know my own understanding and then some research from this is It's almost like defining the set of instructions uh to reliably accomplish language generation tasks and one of the Articles here I had shows just how many um tasks there are possible just in a system like gpd3 as an example q a blah blah blah movie to Emoji class like so many different versions and each of these could all be just played around with a little bit to make a better output uh and with that better output means you might not have to do another one which means you're saving money you're saving time you're saving human brain power to refine it and I think over time we will see more machine learning applied to this system to engineer prompts better I think the people working on the end you know ends of dally and uh and gpt3 and stuff they're going to try to make these um these sort of uh pieces more predictable but then there's this weird conflict which is is some of the fun around this and fun you know again might not be what businesses are looking for is that that unpredictable almost chaotic nature of putting in a prompt and getting back what you you know something that you you you're looking for but can almost uh execute yourself or looking for a machine with so much data to then help imagine this and this is where I'm you know see this sort of Line in the Sand where it's like if I am trying to if I'm trying to engineer prompts and I can't seem to get the output that I'm looking for how many prompts do I do and how many Engineers minds or strategist Minds do I do to try to get that output versus just say if it's dally and I'm trying to get an image versus just hiring an artist to make that image who's obviously talented and you know knows uh you know uh Adobe Illustrator or whatever tools they're using or Unity or whatever it is to accomplish that same task and so there's this sort of uh sort of yeah just split and divide between where that happens in these use cases where AI can be used and if with the right prompts and with engineered prompts can produce something that is beautiful and valuable for if done right at a very inexpensive cost and it's completely original now you have commercial rights to this et cetera et cetera versus then going hiring maybe a talented artist having the back and forth uh you know drafts multiple drafts over and over again requiring human input and labor maybe expensive labor et cetera et cetera so I do see this really uh interesting divide emerging um between these two and again I think this uh speaks to the value of prompt engineering and a future Market that we talk about like maybe our artists get eliminated or you know with every advancement in technology some jobs disappear and in other cases uh many more that you couldn't even predict come and so with these you know just this exponential increase of interaction with these large language models I do think that we're going to see more and more jobs titles uh use cases emerge that we just didn't expect that are completely new that are novel that are exciting that bring something in that we just uh couldn't even imagine just a few years ago and I think that's a very exciting uh time and one of those is uh you know prompt prompt engineering and I'm just looking at you know if there's any other things uh sort of in these uh you know a couple links and a couple notes that I've made here but one of the bigger pieces here is this idea of sort of zero shot learning versus few shot learning which is generally and this is where prompt engineering comes in again generally you're not going to get the output that you want on First Response unless you maybe have a you know a lot of experience with these systems and a set of sort of uh parameters or instructions that are extremely specific allowing just enough creativity or creation that gpt3 or dally or any of these systems create the output that is highly valuable generally what is happening is there's this idea of few shot learning dally where we can now see that where you can pump it you can put in an image but then you can make edits to that image with more text prompts instructions and so this idea that it's going to take a couple shots to create the output that you want that engine then learns from those a few shots that actually happen so um there will be I think more challenges with this one of the things that I'm thinking about is just like uh and is these these will continuous continually uh change because the engines the language that they're doing may change so maybe a prompt that you've engineered works one day the next day there's an update that's rolled out and that prompt no longer works so um that's another sort of risk I think in these systems and in the people who are working on this so I do think we're going to see this grow I think it's going to be a competitive Advantage if you can do it I think it can reduce the r d efforts that you do to have to discover a new prompt uh I think there's gonna be people who are trying to reverse who are looking at images who are with specifically with Dolly and trying to reverse that and then figure out how to create that for their own business I do think that there will be a lot of people who emerge in this market and maybe a couple people are accelerate or maybe it's the people like open AI who are leading this charge who just continue to refine internally and then reduce the burden on other outside parties to create these uh you know engineered prompts that are doing really well I think it's probably going to sit somewhere in the middle so if you're asking what is prompt engineering I hope this gave you some insight I'm still exploring this myself I'm going to publish more videos and content on this if you like it feel encouraged send me a message like comment subscribe comment for the algorithm all that stuff I really do appreciate it helps me know that I'm on the right track exploring topics that you're interested in that you're excited about and that you're finding Insight in so this has been Tyler Bryden talking about what is prompt engineering I hope you enjoyed this video thank you very much for tuning in I hope you have a great rest of your day bye

Channel: Tyler Bryden

Views: 42,006

Keywords: Prompt Engineering, DALLE, GPT-3, DALL·E, DALL·E prompts, OpenAi, Midjourney, AI21 Labs, Cohere, PromptBase, AI, Large Language Models, LLMs, Hugging Face, Bloom

Id: sztL7rp_TkY

Length: 14min 43sec (883 seconds)

Published: Mon Aug 01 2022