Keep calm, the next wave of AI is here.
In 2023, a seismic shift is underway. The foundations underlying the creation of digital art, video, 3D objects, text, code, and data are rupturing. Something new is surfacing.
The epicenter of this wave lies in the rise of applications using generative AI — a technology promising to strap a rocket ship to the engine of content creation.
However, opinions on the technology are sharply divided — between those who believe it will birth a rising tide of innovation, and those who fear it will drown creativity, impoverish artists, and usher in a lifeless dystopia of soulless creative automation!
Over the next few weeks, I’ll give you an inside view into this amazing new technology, explore its pitfalls and promises, and look at the challenges and possibilities ahead.
What is Generative AI?
A simple explanation is that generative AI takes in data, discerns meaning from that data, and produces new ideas and content. It doesn't just observe patterns, but learns to mimic and innovate based on those patterns, creating unique outputs such as text, images, music, or any other form of content.
Well actually, if you think about it, generating newness from knowledge is something we humans take for granted.
This fact is so innate to us that the thought of anyone or anything else producing “new ideas” makes us a little uncomfortable. Imagine if your toaster could suggest new ways of preparing your bread.
As “smart” as your phone is, it can only perform the functions that humans have coded into its design.
Even our furry friends in the animal kingdom can’t generate new ideas in the same way or to the level that we can, relying mainly on habit and instinct.
Humans have enjoyed dominance over the processes of ideation and creation, using it to invent technology, build civilizations, and produce the greatest masterpieces.
Generative AI has joined us in that privileged class. It, too, can create new ideas and content by mimicking the elements of creation — learning, imitation, chaos, iteration, and curation.
The output is curated randomness: content that is novel yet grounded in a prior idea.
History of Generative AI
Let's hit the rewind button for a second and dive into the history of generative AI. We're in the early days of computing. Computers are as big as your living room and pretty straightforward - they crunch numbers and store data, but that's about it. Kind of like really expensive calculators.
Then, in comes machine learning in the mid-20th century, and everything starts to get a lot more interesting. Computers begin 'learning' from data.
Fast-forward to the 2010s, and here's where things get wild. A subset of machine learning, called deep learning, gives computers the ability to learn from enormous amounts of information.
Generative Adversarial Networks, or GANs for short, are a key innovation. Introduced by Ian Goodfellow and his team in 2014, GANs are like two kids in a prank war - one keeps trying to fool the other, and the other keeps getting better at telling when it's being fooled. And as they play this game, they get better and better, leading to more and more realistic creations. These clever structures become the cornerstone of the generative AI revolution.
Generative AI vs AI
So, how does generative AI differ from the 'old' AI? As mentioned earlier, the key difference lies in the ability to generate 'new' content.
Traditional AI is typically programmed to perform specific tasks and lacks the ability to 'create' in the way humans or generative AI can. Think of your GPS system: it can find the fastest route to your destination based on programmed algorithms and current traffic data, but it can't 'invent' a new type of transportation.
Generative AI, on the other hand, learns from vast amounts of data and then uses that knowledge to generate something new. This could be a piece of artwork, a piece of writing, or a completely new idea.
The evolution from old AI to generative AI signifies a monumental shift. We've moved from a world where AI merely performs tasks to one where it can contribute to the creative process.
Generative Art: the First Wave
Let me just show you.
No-one created the images in this article. I typed some random text into a field, hit enter, and the AI “created” the artwork in a matter of seconds.
Whether or not you like the outputs, isn’t the point. They were produced in less time than it would have taken me to get my easel and paint brushes ready.
Factoring in that I have absolutely zero artistic or photographic talent (I struggle to draw stick figures), I can safely say that Generative AI Art has allowed me to do the impossible.
Several artists have already voiced concerns that their work is being used to generate content without attribution, permission, or compensation.
Some artists are worried that, when generative art floods the internet with hundreds of images looking similar to their own, they will lose both income and relevance.
I’ll address these ethical issues in another article, but for now, it is important to pay attention to the debates around generative art as a preview of broader things to come.
It is only a matter of time before we see generative technologies integrated into many different types of applications.
Generative AI Use Cases
Generative AI will revolutionize our cultural and creative landscape, and shift our perceptions of knowledge entirely.
Would you have suspected if I hadn’t told you that the illustrations in this article were entirely computer generated? Does it matter to you? Does it make the output any less valuable to you as the reader?
Now apply that thought to every single idea and knowledge output that we, as humans, generate.
Imagine a world where AI can design award-winning buildings, write bestselling novels, or even write that report that you’ve procrastinated over for weeks.
What does that mean for the already tenuous line between real and fake?
Ok… I’m getting a bit carried away here. The truth is that we don’t yet know exactly how generative AI will work and what its full application will be.
But we know that generative AI is breaking all the rules — blurring the lines between creator and audience, data and output, code and art.
I suspect that we’re in for a wild ride.
Bringing It Home
Right now, the challenge is getting generative AI out of the computer clouds and into the hands of everyday folks like you and me.
This moment is special — the rise of generative AI will force society to define new norms. It has already raised questions about ownership, originality, and even the idea of “self”.
It is important that we, as a society, explore these ideas together.
Right now, most people may not even realize what generative AI is, let alone what we can do with it and why it is so important for us to take notice.
So the starting point is to bring it to the people so that we can begin these important conversations.
Enter the Vanaverse: Vana's Perspective
Vana doesn't see a future where ideation is replaced. Instead, imagine a world where you and I team up with AI, creating a fusion of human and artificial intelligence that opens up untapped reservoirs of knowledge and ideas. Doesn't that sound exciting?
One thing that really stands out about generative AI is how it can enhance our capabilities. Picture this: not only are you more productive, but your creativity is also given a turbo boost. My experience with these cutting-edge tools reminds me of kindergarten – a mishmash of fun, bewilderment, and a sprinkling of chaos.
Vana encourages us to embrace this wild ride of unpredictability, to find joy in the unexpected. But how? By letting us weave our unique characteristics into the fabric of the AI.
You can now fuse your personal data with generative AI to create what we call a Virtual DNA, or "VNA". Think of it as a digital mirror reflecting specific elements of your personality. Take the Face VNA, for instance: it's a map of your physical features. Or the Music VNA – a reflection of your musical preferences.
You'll be amazed at the breadth of personal elements that AI can help digitize. It's like building an interactive, digital twin of yourself – a comprehensive, lively image of you in the virtual world.
Crafting this digital doppelgänger allows you to voyage across the Vanaverse: a frontier of AI-guided experiences designed for dabbling in alternate realities.
First stop: Faces
There's a powerful truth: our faces are the portals to our souls. They aren't merely showcases of emotions; they're the artful narrators of our untold tales. Each twinkle of joy, furrow of worry, or arch of surprise weaves an intricate tapestry of our humanity.
But there's more. Faces are enigmas that we're instinctively wired to unravel. Each glance we cast at another's face, we're decoding subtle cues, reflections of our inherent biases. This fascinating dance opens a riveting conversation about human psychology. Our faces, truly, are the mirrors of our unique inner worlds.
As the inaugural experience in the Vanaverse, you get to create your unique Face Model! With this face model, you can play around with multiple realities. Ever wondered how you'd look as a cyborg? Consider it done. Fancy being a fairy princess for a day? Easy peasy. Ever been curious about appearing as a different gender? Absolutely feasible.
As we further expand the Vanaverse, you'll be able to add more dimensions to your Digital Self: body, voice, writing style, and the possibilities are endless.
So, are you ready for the journey?