In today’s episode, I delve into the fascinating world of generative AI systems like ChatGPT, GPT-4, Bing, Bard, and more. Remember, AI models aren’t all created equal, each has unique quirks and requirements when it comes to crafting prompts. Just like different operating systems require different apps, so do AI models. And if you want to get the best results from them, you need to understand this. I’ll also share some essential tips on how to build your prompt libraries based on the specific system, and where to find the most reliable information to do so. You might also want to join the bustling AI communities on Discord, where you can trade prompts and learn from each other. Tune in to understand why “prompts aren’t 100% portable”, how you can optimize for each AI model, and why this knowledge is vital for anyone dabbling in AI. Don’t forget to hit that subscribe button if you find this episode valuable.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.
In today’s episode, a brief reminder that prompts are not portable.
This is, of course, in reference to generative AI systems like ChatGPT, GPT-4, all Bing, and Bard as well as image systems like Stable Diffusion, dolly to mid journey, etc.
All of these systems use AI models and remember that a model in an AI parlance is really just a piece of software.
It’s software that was made by a machine made for machines.
The interfaces like ChatGPT, are the ways that we as humans talk to these models.
But these models themselves are essentially their own self contained pieces of software.
They’re all built differently.
They’re all trained differently, they’re all constructed differently.
And so what works on one system will not necessarily work on another system, you may get good results, but not great or optimum results.
For example, the model behind ChatGPT, the GPT-3, point five and the GPT 4.0 models.
These work best when you have a very structured prompt, that is role statement, background action.
And you can download the there’s a PDF that explains all this go to trust insights.ai/prompt sheet, nothing to fill out no forms, just grab the PDF.
That structure works really, really well, because aligns with the way that OpenAI has said, the engine behind it works.
That same structure, if you move it to like llama, doesn’t work as well, if you look in the llama instructions for, for developers, they tell you, it’s a user, and then to statement.
So there’s no it’s not for parts that are easily interpreted.
And the use of sections typically pretty short and Allama statement.
Other systems like Bing, and Bard, you know, tell us, there’s no developer API.
So there’s no way to look at the underlying system and say, This is exactly how this thing works.
Think of think of AI models like operating systems, right? If you have an iPhone, and you have an Android, they are very similar, right? They are very similar in that you can do a lot of the same stuff on each one may have similar apps, they have kind of a similar interface, but they’re not the same.
You can’t go on Android phone to the Apple Store and, and buy and install iOS apps on your Android phone and vice versa just does not work.
at a fundamental level, even though from our perspective as end users, they seem like nearly the same thing.
So what does this mean? What should you do with this information? Fundamentally, as you start to Britt to build out your prompt libraries, which is something I very strongly encourage everyone to do.
You’re going to want to separate your prompt libraries by system.
So you’re going to have prompts that you know or have tested or have experimented with, and work well on Bard, you’re gonna have prompts that work well on GPT-4.
All you got to have prompts that work well on mid journey.
And when you start with a new system, or a new model, or even an upgraded model, you will, you can use pre existing prompts that you’ve written in the past, but understand it’s probably going to take some time to sort of tune in to how each new model works and how that model works best in terms of prompts.
Generally speaking, if you want prompts to do really well look for developer documentation, look for the instructions given to coders as to how to talk to their those systems behind the scenes.
This is how, for example, we know that the structure of OpenAI system is designed to work they published a very detailed instructions in GPT, for all and all the systems around that there’s detailed instructions.
The other thing you can do is that there are huge communities available online, that people are sharing prompts, which I think they need to be careful because a prompt is nothing more than software and you might not want to share your intellectual property, your specific software but that’s an that’s a talk for another time.
There are these different places you can go where people have huge prompt libraries, you can go and grab prompts from other people who have gotten them to work well on other systems.
For example, if you are working with mid journey, there’s a mid journey Discord server has a whole Discord community, you can join that community and see a library of things that work really well.
You can join one of the many many love llama community so gnomic AI has a huge community and there’s people trading prompts there, you can join OpenAI cert Discord server.
You’ll notice by the way, kind of a theme, most of the big AI tech places and company He’s in startups.
They’re all on Discord.
So if you’re not comfortable with Discord, now would be the time to become comfortable with Discord because that’s where a lot of the action is happening.
That’s where a lot of the cutting edge stuff is happening and is where in many cases, announcements are made first to the most devoted members of the community, so that they can take advantage of things like new betas or new new things to opt into new tools, as they’re announced.
Before that news spreads to other parts of the internet.
So prompts aren’t 100% portable, but they are, they do have a lot of commonalities.
They are not necessarily one to one system system.
And if you want to know what works best, join one of the many, many communities out there that people are just trading these things like like Pokemon, and and find stuff that works best for the use case that you want.
That’s the show for today.
Thanks for tuning in.
I’ll talk to you soon.
If you’d like this video, go ahead and hit that subscribe button.
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