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Has AI Now Proven That Human Creativity is a Scam?
A Deep Dive into the AI Art Revolution Part 1

Image made with ideogram.ai Prompt: Lots of robot hands cutting pictures with scissors and pasting them onto paper, make it look like a Hokusai drawing, ukiyo-e
What we have this week:
Hit me with the Latest ππ»
Have new Diffusion Models Taken Human Creativityβs Aura?: An Intro
Prompt Like an Artist not an Amateur!
Infinite Tomorrowβs Apes
The future is in βIllions!β
Latest AI News
Apple have revealed how much they are spending on AI and believe their advanced language model Ajax is better than Chat GPT.
Time Magazine have recently focused on AI with their 100 influential figures.
Also, in an article by Mustafa Suleyman Co-Founder Of Deep Mind and now Co-Founder & CEO of Inflection AI talks about the impact of AI on society in a prelude to his new book βThe New Wave"β.
A group of Artists have signed an open letter to Congress saying generative AI is okay, arguing that AI tools lower barriers to creating art and that artists themselves should be included in the regulatory process.
Researchers have put forward MVDream a new multi-view diffusion model that that can create 3D models from text. Itβs resolution is limited at this stage just like 2D ones were in the beginning, so this latest research from the team at Bytedance offers some great potential.
The Imitation Game Part 1 :π π :
What are we talking about? | Diffusion Models |
What are they? | Generative AI that can recognise a text prompt and render an image using a process called diffusion. They are trained on an image library of millions. |
Examples | MidJourney, Dalle-E, Stable Diffusion |
So what is happening?
The magic of prompting Diffusion Models with a few words and getting back a highly resolved professional looking piece of art has been an astounding revelation.
Question: Are Diffusion Models Artists?
When you put it like that itβs pretty obvious, right? The answer is a resounding no!
Letβs look at the process of art creation to draw some conclusions as to the current state of visual creativity of humans and AI.
What are the key ingredients of creative intelligence you need to produce visual artwork?
Just for fun letβs try giving Diffusion Models a Score card against Humans!
Disclaimer: Itβs basically a dominance factor out of 10 so itβs not 100% accurate, but it gives an illustration of the current gains in the tech.
Diffusion Model v Humans Emoji Score Card!
Idea π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Imagination π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€
Memory π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€
Perspective π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Conceptualisation π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Language π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€π€
Interpretation π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€π€
Invention π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Image Recog π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€π€
Pattern Recog π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€π€
Execution π€π€π€π€π€π€π€π€π€π³
Fingerprint π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Expression π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π€π€π€π€π€
Authenticity π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨π§π½βπ¨
Itβs clear from the score card that visual art creation needs humans. In fact keeping a score card is perhaps not the right way to look at it.
It doesnβt have to be a competition believe it or not!
AI is making in roads into parts of the creative process, but itβs not the whole picture.

The AI Creative Intelligence Bubble is Expanding
Executing at light speed with infinite iterations!
This is where the perceived magic lies.
The skills required to do the physical work of execution is time consuming and requires years of skill acquisition, training, practice and technique.
AI is now providing a shortcut and itβs a huge one!
The speed at which Diffusion Models can execute an image based on text and iterate variations of that form is the real superpower here. Itβs like a lightening rod to realising your ideas.
Itβs also a great opportunity for those without the forming skills to see their ideas realised. A little democratisation of art.
Next week we will continue with some further insights into Human and AI creativity and talk about itβs super powers, itβs limitations, state of IP and give some tips on how to utilise this potentially game changing technology!
Chat GPTβs title contributions
Iβd like to include some of Chat GPTβs contribution to the titling of this story. Iβm always impressed with itβs predicting of the next word and the power this process has to display comprehension of a subject. Albeit a magic trick really, but thatβs another story.
Standard story title:
AI's Mirror or Genuine Imagination?
The AI Mirage: Debunking Creativity's Golden Aura
For Click Bait:
βCreativity Exposed: AI's Copycat Feat Questions Its True Worth! π€π‘π¨ #AIvsCreativityβ
"Creativity or Copy-Paste? AI's Sneaky Secret Shakes the Artistic World! π¨π€― #AIvsCreativityβ
Prompt Strategy for Artists
Here are some approaches to working with Diffusion Models creatively to better realise your artistic vision.
1. Develop your Idea First
Put everything you can into developing an idea. Do the work! Donβt just go with the first thought you have. Think about your inspiration and explore your ideaβs βworldβ further. You can even use a Diffusion Model as your sketchbook.
The stronger your idea to be begin with, the better your work will be!
2. Be Specific
Diffusion models are labellers. They will take each word and in some ways mysteriously reconstruct from the combination of labels you give it. Give each specific thing you want to see and try different synonyms of that word to gain better results.
3. Iterate, Iterate, Iterate
Think of the process of image generation as just that, a process. The more you iterate the better and hopefully more original the result. If you are going off the first prompt you are probably getting an obvious imitation at first.
4. Game the System
Once you have something in mind. Look at doing a staged approach to your prompts and this will steer the model to your ultimate genius vision!
Donβt always start with the things you want to see in the first prompt. You could start with shapes and simple forms to define the composition. With the diffusion modelβs regenerating each time from the previous you will have more control and creative collaboration to get a great result.
Below is an example with possible [sub]prompts. You can have more in each prompt stage, but this gives you an idea of the through-flow process.
Initial Prompt - General shape - An exploding balloon
Next - Add in another shape idea - Atomic explosion
Next - Add in an unexpected element - waterfall of colourful art glass
Next - More Elements - fractal robots
Next - What details would you like - lots of wires
Next - Colours - pale green
Etc Etc
There are infinite ways you can tailor a process like this.
5. Combine and Conquer!
A Diffusion Model will do its best to represent your text and will combine things in all sorts of wondrous ways. This is an element of art that is powerful in conveying ideas.
Try and be as original in your combinations as possible. Think outside the box! Also, try combining a couple vs many.
Banana + Day πβ±
Banana + Nurture + Crane + Day ππ©π»βπΌπβ±π€ͺ
Think of your idea and all itβs complimentary and opposing elements.
6. Collaborate
Try adding your own self made images. This is a way to collaborate and influence the output with some of your own original material and put your fingerprint on it.
7. Use More Than One Diffusion Model
Now that you have found a great new tool, why limit it to one! Each model has been fine tuned in different ways, so be sure to run your ideas through as many as you can and even upload a result from one into another.
8. Experiment
Try poetic, abstract and downright crazy illegible gibberish if you like. See how the model interprets and then do the above. Itβs a great way to free constraints and find unexpected paths to express your ideas.
This will also ultimately help you understand the model and itβs behaviour. The more you do, the more command you will have over your results.
Infinite Tomorrowβs Apes
Been busy creating this series of Tomorrowβs Apeβs with ideogram.ai
With AI youβre able to make endless iterations with each Ape seemingly having their own individual personality!

Prompt: a smiling humanoid ape connected to a neural network with lots of wiring, neurones for fur and tech. Lots of miniature AI robots around him
It looks to me like the future is going to be in βillionsβ!

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