I was one of the early adopters of DALL·E 3.0, and I couldn’t wait to put this new AI image generator to the test. The initial results, I must say, blew me away. What set DALL·E 3.0 apart was its ability to understand not just single words or simple prompts but entire phrases and sentences. It felt like a significant leap forward in AI creativity.

The images it generated were a sight to behold – beautiful, bright, and full of life. It seemed like I could finally do away with the rigid, prompt-based language that had constrained previous AI models. DALL·E 3.0 was a breath of fresh air in the world of creative content generation.

Excitement filled my days as I used DALL·E 3.0 to create a wide array of images for a project I was passionately working on.  It quickly became an indispensable tool in my creative arsenal. However, all good things must come to an end, and in this case, it happened rather abruptly.

One fateful day, I logged onto the platform to create more AI-generated images, only to be met with a disheartening message: “Promptblocked.” I tried again, hoping it was just a minor glitch, but to my dismay, the same message appeared: “Promptblocked.”

It turned out that DALL·E 3.0 had been nerfed into existence. The issue lay in the specific prompt I had used – a celebrity’s name, Lana Del Rey, to be precise. Previously, DALL·E 3.0 had excelled in creating fantastic reference images for my project, but suddenly, it refused to cooperate. The reliable wellspring of creative inspiration had run dry.

As I reflected on my journey with DALL·E 3.0, I couldn’t help but acknowledge the rollercoaster of emotions it had taken me on. It had been an incredible tool, enabling boundless creativity with its brilliant images. But, it came with its limitations, and one had to tread carefully to avoid promptblocks.

In the end, my experience with DALL·E 3.0 was indeed remarkable, a brief and brilliant journey through the realm of AI-generated artistry. Though its limitations became evident, the potential of this technology remains undeniably promising. DALL·E 3.0 may have had its ups and downs, but it undeniably showcased the incredible power of AI in the world of creative content generation.

If you wish to try it out for yourself, a link is here: https://www.bing.com/create

It is still a fantastic tool, but not as good as it once was.

PromptMuse

<p>The post DALL·E 3.0: Is the Hype Justified? first appeared on Prompt Muse.</p>

Links:

https://beta.openai.com/docs/api-reference/completions/create

https://landbot.io/

FAQ

Q: What is an AI Image?
A: An AI image is a computer-generated image created using Artificial Intelligence (AI) technology. AI images are usually created using powerful tools such as Dalle-2 API and Landbot.io, which allow users to create stunning visuals by harnessing the power of AI.

Q: How do I create an AI image with WhatsApp?
A: You can create an AI image with WhatsApp by using Dalle-2 API and Landbot.io. First, you will need to get a Dalle-2 API key and set up a Landbot account. Then, you can use the step-by-step guidance in our YouTube tutorial to guide you through the process of creating stunning visuals with these powerful tools.

Q: What tips and tricks should I know when creating AI images?
A: When creating AI images, it’s important to pay attention to the details and make sure that your images are accurate and aesthetically pleasing. It’s also important to choose the right resolution for your images, as this will affect their quality and usability. Additionally, make sure to store your AI images for later use by using cloud storage or your own computer system.

Q: What are the best practices for managing and storing my AI images?

A: The best practice for managing and storing your AI images is to store them in an organized and secure manner. Make sure that you back up your images regularly in case of any technical issues and use good password protection techniques to keep them safe from unauthorized access. Additionally, consider deleting any unused or outdated images to keep your storage space organized.

Transcript:

Hi, guys. Welcome to another tutorial by prompt news. Today we’re going to be making a GPT-3 image creator right into your WhatsApp. So this is going to be similar to mid journey, stable diffusion, but it’s going to be powered by Dolly and WhatsApp. So no other applications in your way, just on your phone, make an image.

Yeah, do what you will. So to start with, we’re going to need a couple of things. We’re going to need a Daly, two API key and a Land Bot account. Landbot does have a I think it’s 14 day free trial, so we’re going to be using that in this demo. Before I start, I would just like to point out that we now have a new community section within our website where we can share rate and get ideas about prompts from our own images and other peoples.

So dive in, enjoy that and I hope to see around there. Anyway, moving on. First of all, we’re going to need to create an account with Land Bot. The website is Landbot IO. So make your way over to their website and sign up for free.

Once in, you will be created by a wizard type thing asking your name, your company, just click pass. That not really needed. Anyway, once you’re in, go to the dashboard, little picture of the robot, click build chatbot. And we want a WhatsApp? We want a WhatsApp?

What are these called? I forgot. Flow diagram thing from scratch. So this is what it’s going to give you to start off with. Click past that.

So user input. This is going to be default. That’s fine. We don’t need to change anything there. And then we want the next one to be text.

Click on it, you don’t drag. And so this is going to be the question that the application in our WhatsApp is going to ask us. So let’s try and make it a little bit cool. What image can I make, my lord? Because I have a complex, obviously.

That’s all good. And we’re going to call that prompt. If I could spell promp and then apply. Just make sure that’s saved. Good.

Let’s drag this green line. It’s been a bit funny. Go away. Drag this green line down and connect. The next step is we’re going to need to get a web hook.

So this is basically connecting our app that we’re making on WhatsApp over to our Daly two API. So let’s just close that and type web hook and click. I always drag it. I don’t know why. So the information that we need here is going to be populated from API reference.

So the web address for this is if I can pull this down, beta openai.com, docsapi referencesimages. I’ll include that in the description. Cool. So down the side, we want to go down to images. And let me have a quick look.

Yeah, this is what we need. So it’s a post. It’s going to be posting. We need that URL. I’ll take that while I’m here.

And we’re going to need this information as well. So if I hop over to my other tab, move it up a little bit, put that in here.

Then we have our custom headers. So what we need here is pop over here again. Content type application JSON Actually, I think that’s prewritten. Yeah. So as a content type, capital type, then application Jason.

Application Jason. Awesome. Now we need our authorization. So this is going to be our key authorization. If you note here, they say Bearer and then the API key.

So make sure you type bearer before bearer and then your API key. I’m just going to pause the video while I get my API key. Hang on a second. Actually, no, I’ll do it with you guys here. So my API go over to your API keys.

So this is in your account. APIs keys at OpenAI. I’ll create a new one with you. I’ll delete it anyway. I’ve reached a max.

Revoke, revoke. Okay, there we go. There’s my new key. Get back over and paste that in.

Awesome.

Let’s save that and put that there. Okay, next we need to do send parameters, custom headers. We’ve done that. We’ve done that. Customise the body.

So go over back over to the reference page. And we want to drag this or actually just click Copy Simple Things. And we can paste that in here. So this is basically saying the prompt. This is the request that we’re sending to the API.

So it’s giving the prompt, the number of images and the resolution. So first of all, let’s delete prompt. Unless you just want an app that makes otters. I don’t judge. And we’re going to add our variable that we created earlier.

We call that prompt. We want one image, and the size is great.

We’re going to test that. 500 errors. So this is basically I haven’t added a phone number yet, so let’s click apply, Test, publish, first name, alex O.

Okay.

All right, cool. All good. So that ping you heard was my Web. WhatsApp? Just saying.

I got a message from them. Let’s close that. Once we’ve added our phone number, then we pop back over to Webhook and then test your request. We want to click the little button, load up our prompt variable, and we’re going to give it a value. The reason we’re going to give it a value now is we need to just have something there for land bots to allow us to give it a name.

That makes sense. Better in a second. So a happy man. Okay. Test or request.

Having a think. Scroll down. Here we go. So we got this information provided when it’s created. And the URL, the only information here we want is the URL.

So we need to give that a name. So click save, responses, variables, find that URL. URL will be the one without any Google lead brackets or anything before. So in this case, it’s this one for me. And we are going to give that a name.

In this case we’re going to call it Response.

There we go.

That’s a string, by the way. If it does ask you what type of variable it’s a string, then apply we’re good. On to the next. So the next one is we’ve got the request from the API. It’s sending the information, it’s creating the image, it’s sending it back.

Now we want to send it to what’s up? To do that close here, go to messenger. I already have. That saved me. SS.

Click it. So the information that it’s sending is going to be an image, of course, because it’s a picture. So let’s click Media, click the pencil from URL, and then we can click our variables, actually. And we called that Response, didn’t we? Response.

So that will get the URL of our picture. Click Send, tie them up, good to go. Publish. And then we can test our application. So here we go.

Test. Let’s send the test to Alex pinged. Your chatbot is ready for testing. Send a message or click the button to start testing. Okay, what image can I make, my Lord?

Let’s make a pink unicorn on a bike. Obviously, you can do your normal things like ultra realistic, 50 millimetre lens, etc. Send the off. Wait a couple of seconds. Usually takes about five to 10 seconds.

There we go. Fantastic. We’ve got my image. So, yeah, I’d be interested to see what you can do with this. And I would like to thank Mr.

Hackathon for his his tutorial on this. This was completely his idea and yeah, awesome. Stay cool. Take care.

<p>The post Create A.I images with WhatsApp first appeared on Prompt Muse.</p>

Things you will need:

1. Google Colab Pro ($8 a month, cancel anytime) https://colab.research.google.com/signup Google colab pro will work as our computer, so you do not need any fancy PC to do this. We will be running this all on virtual machines (It’s super easy!)
2. Stable Diffusion (AUTOMATIC 111 UI)Automatic 1111 has developed a user interface that can now be installed and run locally on your machine. You need at least 4gb of VRAM to run this, otherwise, you will get out-of-memory errors. But do not fear, I will be bringing a new tutorial that enables you to run stable diffusion remotely without sign up here to find out when it’s released.

Step 1: Character Design

Log into Midjourney. You can use any Text to image generator. It’s just in this tutorial I so happen to be using Midjourney.

You can use any text to image generator you like, I just chose Midjourney as an example. When you log in, find a suitable room on the left-hand side or make your own. In the bar at the bottom type in /settings You can use any of these settings displayed, but again for the purpose of this tutorial, I will be using Midjourney version 4. I switch the Remix feature on as well to get my character close to what I have in mind. See here for more about the remix feature.

My prompt is:

/imagine head and shoulders shot of Instagram model, orange long hair, hyper detailed –v 4

My aim is to get the character facing forward. In order to get your character facing forward, you can include in your Prompt looking straight on, looking at camera, symmetrical face.

Do not be afraid to use the remix button to adjust your character.

Step 2: Make a video

The video we need to make is called a Driving video. Think if it like Texas chain saw massacre. We will be taking our characters skin and putting it on top of our animation.

You can use any face (Male/female) to use as driving video, it does not matter. What does matter is that you show an array of facial expressions. Sad, happy, confused, shocked. Also be aware not to turn your head too far left and right, but if you do you can just delete those frames later on- so no biggie.

I used my iphone, you can use webcam or what ever you have to hand.

• Make sure your video is relatively short (Under 10 secound. Mine was under 20 seconds, and 9.78 mb)
• Save your video as driving.mp4 & and your characters face image as source.png
• You can use https://ezgif.com/to crop and resize your video to 401×412 Pixels
• I matched my characters face and my face in the video up in After effects by just moving it around in place, so the eyes, chin and mouth were roughly in the same place.

Step 3 : Google Colab -Thin Plate Spline Motion

So if this is your first time using google colab, welcome. And if you are a regular user, you probably know more than me. But I think we can all agree to a newbie this looks daunting, it’s not. Use the FAQ and comments section if you have any question about this, I’ll be happy to help.

I advise signing up for the google Pro account, as you will be allocated better GPU and more RAM. Otherwise you may run into out of memory errors. Once you have made an account with google colab.

• Open the Thin Spline plate motion model notebook and make sure you are signed in.
• Click on the play button. This will run the cell which installs everything you need remotely on your computer.
• You will get a message letting you know this is not authored by Google, click Run anyway

• Once a cell has executed successfully you will see a tiny green tick next to the button.
• We now need to upload our driving.mp4 and source.png.
• This easiest way to do this is to mount your google drive to this notebook (But I understand for security reasons if you do not want to do this. Please refer to the FAQ here for an alternative method here.
• Click the files icon to the left of the screen. This will expand you file panel out.
• Click on Mount drive icon, as seen in image below

• Once a cell has executed successfully you will see a tiny green tick next to the button.
• We now need to upload our driving.mp4 and source.png.
• This easiest way to do this is to mount your google drive to this notebook (But I understand for security reasons if you do not want to do this. Please refer to the FAQ here for an alternative method here.
• Click the files icon to the left of the screen. This will expand you file panel out.
• Click on Mount drive icon, as seen in image below

• Once you have clicked the Mount drive icon, a new cell will appear in your code section of you notebook. Click run (The play icon)
• You will now be asked to connect your google drive to this notebook. Click connect to google drive, and log into your google drive.
• Once this cell has sucessfulyl excuted, you should now see a new file appear in your files panel on the left hand side (Might take a few secound to appear. If not you can press the go up a folder icon, this will refresh your folder list. Now navigate to: Content > Thin-plate-spline-motion>Drive

• Now, go back to you google drive in Drag and drop your driving.mp4 and source.png into your google drive folder making sure it’s not in a folder. Right click on each file and click Get link. On the general access drop down select Anyone with Link and then Done.

• Navigate back to your Thin Plate Spline notebook and Right click on your driving.mp4 (Located in the left hand file structure) and click Copy Path

Paste the path into Step2 settings,

source_image_path:
/content/drive/MyDrive/source.png

driving_video_path:
/content/drive/MyDrive

Run cell Step 2

• The next steps are easy, just run the cells in order and wait for them to complete before moving onto the next cell
• Once all cells are complete you will have all you assets that you have created saved in the folder structure on the left hand side. All you now need to do is download the up scaled frames. Save about approx 20 of the best frames, showing various facial movements.

Step 4 : Outpainting

Hey, I’m just finishing this documentation up, so bare with me whilst I work on it. The rest of the tutorial Should be up within 24hours 

<p>The post Consistent AI Characters in any pose first appeared on Prompt Muse.</p>

I think Darley Two probably has the most simplistic and intuitive interface. I feel like the data set was definitely trained on stock images. The outpaint feature is really cool. It allows you to imagine we it allows you to imagine what outside the boundary of an image would look like using artificial intelligence. You can also direct the imagery outside the boundary of the image using prompt.

For me, I’ve been using it for when I create images imagery, and they’re perfect, apart from they’ve copped the outside areas off or half a face or a nose or whatever. And then I can bring it into Dali Two Out Painting and then reimagine the outside of the image. You can also increase the aspect ratio of the image, giving you wallpaper or portrait style. I’m really excited to bring you this video today because I think it’s such a cool feature and obviously it’s going to be developed on within the future. Just log in or sign up for an account absolutely free.

I could be using my brother’s account today. Thank you. So this is the introduction screen, which you see where you can generate your prompt from here. We’re not going to be using this prompt section today, or we’re going to be heading over to the outpainting section. So you see this new button.

Try out painting open editor. So if we quickly look at the interface, there’s not much to look at. I’m just going to close this window down, letting us know about the beta version. All our tool sets are here. You’ve got five tools.

You pan button, an eraser tool and add generation frames so you can add sections onto your image. And then we have an upload image where you will upload your image that you want to add onto. So this is our generation frame. By default, it’s 1024 by 1024. So I’m going to take a picture of this room and we can use AI to imagine what is in this area and this area only.

I know the secrets of this room, but AI can use its imagination and with the help of prompting, we can sort of steer it into a direction. So I’m going to click on the upload image to upload the photographs that I took with my camera and then place it anywhere in the canvas. And once I’m happy, press the tick button to place or delete and then start again and upload another image. So I’m just going to place that there in the canvas. You can move the generation frame around your image.

So let’s say I wanted to know what’s over here. It will use this big square here and reimagine with AI what this area looks like the same for going from the side or down there or up there. Let’s reimagine what’s over on this side over here. I’m not actually going to tell you because it’s a secret and it will remain with me off this room and we’ll see what it will generate. I’ll bring it slightly and it’s going to be pulling the information from the photo.

Then using an algorithm to determine what suits the imagery best. I’m going to click Generate here on the prompt and then a blue bar will appear at the bottom of this generation box. And once it’s gone across, that means your image will complete. It takes a few seconds, it doesn’t take long at all. Okay, so that’s apparently what this room looks like behind me accordingly to the algorithm.

And you see on this toolbar down here you’ve got Council and Accept that you can cancel the generation and restart it if you’re not happy with the options it gives you. It gives you four generations at the bottom here and you just use the arrow here to toggle through the options.

This is quite cool. That could be the area. There’s the person who edits these videos rather badly in the background. And I’ve got a nice laptop, somebody’s desk over there, a really big arm with a hairband on. I don’t actually have any hair bands on, but good try, good try.

I like this. It looks like I’m working in some sort of corporate environment, not my home. So we’re going to click Accept and then we’re going to move the generation frame over here to see what’s on my desk or what Darley Two thinks is on my desk. So let’s generate that image. And you can see here it’s generated the top of my hair as well.

It’s not a perfect programme and it’s not going to give you exactly what you want every time, but it’s really cool. For again concepting and then using to overpaint in other pieces of software. It’s got my monitor in, it’s finished to the edge of my iPad, which is cool. It’s put a window in front of me here and then if I skip through the options I’ve got some drafting paper here. Excellent.

Bigger desk there’s, my receptionist there. I quite like that one. That seems to fit the theme nicely. So you will get errors like this blue bar here. But what you can do is use this eraser tool and just erase.

And I think you do fill works in the image very well and then regenerate again. And there you go. I’ve got several more options because I erased those sections I didn’t like, so it’s given me some alternative options there. Now, it’s not a perfect tool, but it’s really powerful and it shows you what we’ll be getting in the future. And what’s frustrating is that you do have to use a lot of credit.

Another cool thing that we can do, we don’t have to use the outpainter section by section. We can import an image that has transparency around it. And let Dolly to reimagine the entire area. To show you how I do that, I’m going to open that midjourney image in Photoshop. You can use GIMP, Ms, Paint, any programme that you can rescale an image in.

And I’m just going to rightclick on the image window at the top. On the top bar and canvasize. Change that to pixels. I’m going to make it the same canvas size as in Darley, so it’s 124 by 124 pixels. So that gives me an outsized area.

I’m going to switch the background off or delete that completely. It doesn’t matter. All you want is the transparent area around the edge. So this is a bit of a cheating way to be able to get more credit for your buck. So I’m going to scale it down slightly into the middle.

Doesn’t have to be too accurate. And so now when I import this image back into Darley, I can run one generation frame over the top of it, because the generation frame is 124 by 124. If you wanted a higher res image, I wouldn’t suggest doing this, I would suggest just adding the pieces on so it would increase the size of your image. But if you’re like me and boring somebody else’s account, this might be a better way of saving credits. So I’m going to save that image back as PNG with transparency.

And then we want to load that same image that we just created in Photoshop with the transparency around the edge. I’ve shrunk the image so it’s within the 124 by 124 frame. I will allow Darley to now reimagine the entire background of this cat. So let’s place that guy there. Let’s put cute cat in Science Lab and generate.

So this might actually save you on credits, rather to do section by section. That can be really costly. There you go. That is a pretty sweet image now, and it looks like it all fits in. The cat is nicely blended into the background and again, it will give me the four options that I could use that looks really cool and would work really well as a wallpaper.

You can then let’s see what my favourite is. That’s cute.

That’s cute. I’m going to go accept on that one. You can add a generation on the frame to extend the resolution of the image. So if you wanted to make a wallpaper and then you can edit the prompt further. So cheat cat in science lab.

If I press generate on that, it might create me an extra cat. So I just put science lab and generate. And what it will do is blend the seams of the generation frame to the image that’s already created and calculate what would work best in that area. That’s giving me just a blank wall and some sort of science Lab experiment. That looks really cool.

I’m not sure what that is. Sometimes these geratrons can be a bit funky and you’re paying for them, which is slightly annoying, but there you go. I think that looks quite cute. Or you could go simple and not really have anything there or that works quite well. We can accept that.

So let’s say you don’t like these beakers here. Again, you can use this eraser tool and just erase the areas that you do not like in the image. So I’m just going to take that bad boy out and then use the generation frame and regenerate. So it’s keeping the speaker that was in the last generation and then regenerating the area that I rubbed out with something that should work a bit better. So you can do this with any areas of the image and I think that eraser tool is really, really powerful.

But again, you’re using your credit just to fix things. And yes, that’s the annoyance, that these things that aren’t free, but people are working hard on getting these tools out and a beautiful interface, so we’re going to have to pay for their work somehow. You can use the arrows to go across and sometimes Dali Two really, really wants to put text in and it never comes out nice. Well, not yet anyway. So it just will randomly plunk some text in.

Give me some options. I actually just like Simplistic Blue there, except it got a really cute image. And then you just click Download here and that will download the image to your downloads folder. You can then take it into Photoshop, or if you don’t need to, for instance, this image is quite good, I can just generate the other side and then I’ve got desktop wallpaper if you ever want to return back to your images. All your images are saved in my collection on the Dali Two website.

So you can go back to them and I hope, as always, this video has helped you. Actually, it was the second time I filmed this video. The first time I filmed it, I had the flu. I rewatched it and I was not making any sense at all. I was completely delirious for any reason.

If anybody wants a scared cat sitting in a laboratory, feel free to download this wallpaper from my website, which is promptmuse.com. Again, I’d like to say thank you very much for my brother for sponsoring this video. And when he sees my face in his collection and how many credits have used he’s probably going to kill me. So hopefully this isn’t my last video. But thanks very much again.

Until next time. That will do it. Bye.

<p>The post DALL-E 2 Outpainting Feature – Super Simple AI Tutorial first appeared on Prompt Muse.</p>

<p>The post How to fix AI art faces : Midjourney, Stable Diffusion, Dalle 2 first appeared on Prompt Muse.</p>

You can try out different subjects, you can try out different styles, cyberpunk, steampunk, art nouveau, anything you can think of and add different artists to the mix and different mediums and styles and lighting. It blows my mind every time I use it and it’s only going to get better. This is an exciting time to come on board and learn how to write prompts. If you’re thinking, oh, this sounds very complicated, I don’t know where to start, start here. Literally, the secret is writing prompts is the same as writing. In Google Search, you are writing a text description of what you want to see and then hitting return and then midjourney. It brings you back an image result that it thinks you want to see based on your text description, exactly like a Google Search. So I’m going to break the prompt down into four simple, understandable components. So first you’ve got your concept and your subject. This is where the most weight is going to be at the beginning of the font. This is where you will define what it is. The next section is style. So you can style your artwork with a genre or a particular artist or mix in different artists.

You can use multiple artists and or different medium of art. So you could try photography, charcoal, sculpture. Just have a play around with all these different styles and you’ll be able to come out with some pretty cool images. So next is the quality inputs. HD stands for high Definition. You can add cinematic lighting. You may have seen Octane Render, which is a 3D renderer. The last and final part of your prompt is the composition. So how you want your output to look like. Do you want an Ultrawide shot? Do you want a wallpaper, like a desktop wallpaper. Do you want a macro shot or a specific headshot of your concept or subject? Put that in here. You can also put your aspect ratio so you can add the ratio size or the pixel size that you want your image. This will change your composition and sometimes gives you better images. So play around with the aspect ratio. Now, if there’s any words that you don’t understand on this screen, google it. Get used to all these different terminologies AI.

Art is not an exact science.

You can become a director and by using the correct prompts, you can get closer to the feeling or the vibe that you want from the image. So all of that in practical terms, it’s all well and good. So let’s put the theory into Practise. Let’s type in sitting black hat, wearing glasses, art by Art Germ, cute cinematic style, HD detail, octane render, and the aspect ratio of two by three. This is the result of our prompt. I did a couple of variations on this image and when I was happy with the variation, I upscaled the image and this was the result. And I think you can agree it’s pulling all the information from the prompt. It’s a black sitting cat with glasses on. It’s cute, it’s got a cinematic style, it referenced the artist nicely, and the aspect ratio is two by three. In this circumstance, Mid Journey has understood the brief and I know it’s not always a way. And you might have to reroll your gift closer to what you want. So you might be wondering what would happen if I just took all the fancy pants descriptions out and just put black cat in glasses.

Well, this is what my journey would give me. It is a black cat in glasses, but there’s no stylization and it quite literally is a black cat in glasses. So you can see how the prompt really influences the output that midjourney will retrieve for you. So hopefully, from this point forward, by watching this video, your prompt structure has improved. Now, to improve on your language, you can go and get inspired by heading over to the Midjourney.com website. And if you go below home and see Community Feed over on the left and click on that, you can see what images are trending, what images are popular, what images are new. What’s really cool is you’re on the standard subscription. If you click on any image and scroll down, ignore this text here, that’s not the prompt. If you click on the two dotted lines, three dotted lines here, and click on Copy Command and open Notepad, Word, whatever you got and just paste, you can see the exact command that they used for that image. Now, if you put this into Midgenit, you will not get a same image because it’s re rolling the dice. It’s not the same seed number, which I can explain in another video, but you will not get the same image, but you’ll get something similar.

But you can see that they have used pretty much all the structures that I explained earlier on in the video. So they put their main concept subject. Their artists actually use the same artist reference and what kind of design, what kind of quality they want from the image. As well, you may notice no watermarks. So if you want to subtract something from your prompt, you put in no glasses and that would remove the glasses from my cat. Or if you were doing a landscape, I’ve been hyping no trees and that would remove all the trees from your image. So that is a pretty cool trick. They also don’t want any borders, they don’t actually want any signature on their image. As you notice, some images from midjourney will show them swinging line a signature and you usually have to photoshop those out. But if you request no signatures, your image won’t have that in. That’s a really cool thing to learn as well. So, as I said, when you come over to the midjourney community, you’ve learned so much by looking at other people’s artworks. So we spoke about all the good things to put into your prompt and how to structure them.

There are things that you should not include in your prompt and those are banned words. You can go to the Journey Discord server and on there you can find the Rules channel. And on the channel the statement goes as follows do not create images or.

Use text fonts that are inherently disrespectful.

Aggressive or otherwise abusive. Violence or harassment of any kind will not be tolerated. No adult content or gore. Please avoid making visually shocking or disturbing content. We will block some text inputs automatically. So there you go. That’s everything you need to know in a nutshell. But if you are still unsure, just head over to the Rules section on the Discord Server and you will find their terms and conditions. I try and keep these videos as bitesized as possible because I know it is a lot to take in and I do have other videos that expand further on prompts, but I hope of every video I do, I improve and get you the information that you need clearly and concisely. I would really, really appreciate it if you follow my channel and subscribe.

And just before we go, I don’t want to say I have a prompt music Instagram page where we can interact over there and you can see prompts and images that I post. I pick a muse a day, so it’s worth following. And if there are any tips you feel I’ve missed out, please feel free to put in the comments section so other people can see and learn. Thank you so much guys, for joining me for another video and I’m looking forward to making another one. And that’s it for now.

Thanks a lot. Bye.

<p>The post How To Write Prompts  first appeared on Prompt Muse.</p>

What is DALL-E?

DALL-E 2 is an AI image generation platform developed by Open AI. It allows users to create realistic images from text prompts, running on an advanced deep learning model. DALL-E 2 is the successor to DALL-E, a generative language model that takes sentences and creates corresponding original images. With its state of the art technology, this cutting edge AI system has been able to provoke both horror and awe in many people online with its amazing creations.

How Does DALL-E Work?

DALL-E 2 is an AI system developed by OpenAI, which enables it to generate digital images from natural language. It works in a two-stage process: first, it generates the gist of the image, and then it fills in the remaining details to create a realistic image. DALL-E 2 utilises neural network algorithms, such as Stable Diffusion, to comprehend language and create accurate pictures from short phrases provided by the user. By analysing image embeddings and running them through its Diffusion decoder, DALL-E 2 is able to generate completely new images that combine distinct and unrelated objects in semantically correct ways. This allows for a wide variety of creative applications and has been utilized by Google’s LaMDA chatbot to produce words and images with remarkable resemblance to real artwork.

The Impact of DALL-E

The potential impact of DALL-E 2 on designers, artists, photographers and creatives is huge. Many traditionally rely on their own creativity and skill to create artworks that have the power to move people emotionally. With DALL-E 2, they could be replaced by AI software that is able to generate an infinite number of images without any human input or effort. This could severely disrupt the work and earning power of many creatives.

On the other hand, DALL E 2 could also be seen as an opportunity for Design and Advertising companies and agencies who can use it as an image bank resource for projects or campaigns quickly without having to employ multiple designers or artists for a single job. Additionally, with its ability to produce multiple variations of one image it can help create high quality visuals faster than ever before.

How is DALL-E Different from Other AI Programs?

DALL-E 2 is an advanced AI system developed by OpenAI that can generate realistic images from short text prompts. Unlike other AI programs, DALL-E 2 combines distinct and unrelated objects in its creations. The model uses a diffusion process to break down and rebuild the images in order to find statistical patterns. It also has the ability to create photos in the style of cartoonists, daguerreotypes, or any other desired style. DALL-E’s approach is unique as it focuses heavily on words and images and their relation to each other rather than creating pictures or paintings. With this system, users can ask for an image of anything from a technology journalist writing an article about a new AI system to a flying unicorn with rainbow hair and get stunning results!

What Is Generative Pre-training (GPT) and Why Is It Used?

DALL-E 2 is the latest version of OpenAI’s generative language model that takes sentences and creates corresponding images. With more than 10 billion parameters, the DALL-E 2 model utilizes the CLIP (Contrastive Language Image Pre-training) algorithm to generate realistic looking images from text descriptions. GPT, or Generative Pre-trained Transformer Version 3, is a deep learning model trained on internet data to generate text. It uses an autoregressive language model based on transformer architecture and has been pre-trained in a generative and unsupervised manner. GPT is used for natural language processing tasks such as question answering and summarization, as well as for generating creative content like music and stories.

What Are the Benefits of Use for Businesses?

DALL-E 2 is designed to generate high-quality images from textual descriptions, offering a powerful tool for creative image production. DALL-E 2 improves on its predecessor, DALL-E, by providing higher quality and resolution of output images thanks to its advanced algorithms. This has the potential to revolutionize the design process for businesses, saving time and effort in creating evocative and memorable visuals.

As well as text-to-image generation, DALL E 2 can also take an image and create captions for it. This can be used in businesses to help understand how advanced AI works and how it can be applied to various tasks such as image recognition or automated processes like customer service or marketing campaigns. Additionally, this technology provides an opportunity for people to express themselves creatively which could be beneficial in a number of ways ranging from advertising campaigns right through to ecommerce platforms or online stores.

When using DALL E 2 it is important to note that inputting long and convoluted sentences can provide better results than short ones so businesses should consider their approach carefully when integrating this technology into their existing systems. Overall, DALL E 2 offers immense potential benefits for enterprises looking to save time and gain access sophisticated visual tools at their disposal.

What Are the Potential Risks to Consider with DALL-E 2?

DALL-E 2 has the capacity to generate 4x better resolution images than DALL-E and has been preferred by human judges over 70% of the time. This AI technology can be used to create anything from pornography to political deepfakes, so it’s important that users are aware of the potential risks associated with its use.

OpenAI is taking steps to mitigate these risks, such as limiting access and providing a variety of mitigations aimed at preventing and mitigating related risks. Additionally, commercial users may have to consider other factors such as ethical or legal considerations before using the product. Furthermore, they are now allowing users to upload faces for the first time, which could potentially lead to privacy breaches if not handled properly.

Overall, while DALL-E 2 has amazing potential for creating high quality images quickly and efficiently, it is important that users understand all of the potential risks associated with its use in order to ensure their safety and security.

How Can Companies Implement it in Their Business Processes?

DALL-E 2 takes a simple text prompt and generates images based on the AI’s understanding of it. Companies can use its capabilities to create mood boards, design marketing campaigns, generate product designs, create logos and much more. By automating some of the creative processes, businesses can save time while still producing high quality results. Additionally, DALL-E 2 provides an outlook of how generative deep learning models might finally unlock new creative applications for everyone to use. With the help of this AI technology, businesses can have access to innovative ways to showcase their products and services in an exciting way that will capture the attention of potential customers.

What Are Some Examples of Companies Using It Successfully Today?

DALL-E 2 is an advanced artificial intelligence (AI) system developed by OpenAI that utilizes text-to-image generative deep learning. It can generate realistic images from a user-provided description, giving it the potential to revolutionize the way content is created. For example, Adobe Photoshop now offers AI-powered algorithms to aid graphic designers with image processing, and Stitch Fix has experimented with DALL-E 2 to create personalized apparel. Similarly, users are creating over two million images per day with DALL E and its blooming potential in SEO and content creation has made it one of the most sophisticated AI text-to-image generators available today. Not only that, but impressive examples shared on Twitter show that DALL-E 2 can create distinct original images from a given image embedding as well. As such, companies across many industries have begun to utilize DALL E 2 for their content needs in order to take advantage of its powerful capabilities and make their products stand out from competitors.

How Does it Compare to Other AI Technologies on the Market Today?

DALL-E 2 is an advanced artificial intelligence technology developed by Stability AI, which is capable of generating realistic images from natural-language text descriptions. The technology is a major step-up from its predecessor, DALL-E 1, as it offers superior caption matching and photo-realism when compared to the hundreds of image generations produced.

At its core, DALL-E 2 takes text as input and produces images as output. This isn t done in one step; rather, the system uses several algorithms to create its visuals. On top of this core function, Dall-E 2 also has two other methods for producing images diffusion modeling and parameter sharing. The diffusion model achieves performance on par with DALL-E despite using only a third of the parameters (3.5 billion compared to 11 billion).

Since April 2021, DALL-E has sparked an explosion in AI generated images across the world. It’s clear that this technology has immense potential for disruption leading to many exciting possibilities for developers and users alike.

Who Are the Developers Behind DALL E 2 and Why Is It So Popular Right Now?

DALL-E 2, OpenAI’s AI system that can generate images given a prompt or edit and refine existing images, is quickly becoming one of the most talked about technologies. It was launched in beta in April and has quickly gained attention for its ability to revolutionize image-based AI. Developed by OpenAI, the company behind GPT-3 fame, DALL-E 2 requires an invitation to access but is expected to become widely available soon.

The team behind DALL-E 2 includes Aditya Ramesh from Google’s Imagen software as well as OpenAI developers. It uses Google s Imagen software and Microsoft s power to create images from natural language prompts with remarkable accuracy. This makes it possible for developers to create apps that can generate or refine images using natural language instructions without any manual input.

DALL-E 2 is gaining popularity due to its incredible potential applications across many industries such as healthcare, education, media production and marketing industries. Its ability to quickly create unique art and imagery based on natural language instructions could make it the go-to tool for creating visuals for projects ranging from advertisements to medical imaging analysis. The possibilities are endless with this innovative technology!

Will We See More Advanced Versions of This Technology in The Future?

This new technology is powered by contrastive and diffusion text-to-image models called CLIP and unCLIP, which make DALL-E more creative than its predecessor. The AI system can also be used to edit and create faces, making it useful for many applications.

It is likely that we will see more advanced versions of this technology in the future as research continues to improve AI systems. Researchers from MIT have already developed a model that uses multiple models to create more complex images, showing the potential for further improvements to DALL-E 2. As AI research progresses and these systems become more advanced, DALL-E 2 will undoubtedly become an even more powerful tool with many real world applications.

  Conclusion

DALL-E 2 uses a technique called diffusion to understand written text, connect it with existing concepts and produce original visuals. The system consists of two main components: a discrete autoencoder that learns to accurately represent images in a compressed latent space, and prior model that encodes the main features of the image into a mental representation. This allows DALL-E 2 to generate high quality and vibrant output images from text with remarkable accuracy. DALL-E 2 is an important breakthrough in Deep Learning, demonstrating the power of Diffusion Models for image generation.

<p>The post What is DALL-E 2? first appeared on Prompt Muse.</p>