Let’s be honest: one of the society’s main AI predictions missed the mark. ❌
We thought it would replace manual workers first, but it's actually knowledge workers facing the most significant impact today.
While some fear job loss and others are eagerly incorporating AI into their workflows, one thing is certain:
Generative AI is not just here to stay; it is booming. 💥
Looks like you too are interested in the topic, so keep reading if you want to delve deeper into:
- The inner workings of generative AI and its advantages
- The influence of generative AI on art and fostering creative expression
- What lies ahead for the future of generative AI
Ready? Let’s go!
What is generative AI?
Generative AI may sound futuristic, but we can actually see many of its applications in our daily lives.
Social media channels are flooded with AI-generated images, and you may well have read an AI-generated text without knowing it wasn't written by a human. Not to mention ChatGPT, which is the fastest growing web platform ever, with over 100 million users in only 6 months after its release. 💬
The thing is, we’re in a unique moment in time, when generative AI is getting more accessible to a wide audience.
This will have significant consequences on how we create and consume media. The paradigm shift we're facing is bound to be a change the size of the printing press.
It’s important to distinguish between the 2 types of artificial intelligence:
1. Analytical AI: Traditional AI that focuses on analyzing existing data that can be used for predictions and automation, and is therefore capable of taking over time-consuming, manual tasks in place of humans.
2. Generative AI: A new type of AI that learns from data and creates new data based on what it learns. It's therefore capable of creating entirely new entities in many different forms, including text, images, audio, and video.
These new, generative AI models have many real-world applications.
We’ll look into them in this article, but first, let’s briefly see how they actually work.
How generative models work?
As mentioned above, generative AI can generate new data in text, images, video, code and audio.
But the technology underlying the creation of all these formats is the same:
Generative AI works by using deep learning to build models from a given set of training data. These models are trained to recognize patterns in the data and then generate new data based on those patterns. Generative AI also has a feedback loop that allows models to be updated as new data is generated and used, meaning they are gradually improved.
1️⃣ GPT-4, the largest language model to date, has been trained with almost all available data from the Internet. The more text we put on the Internet, the better it will get in the future.
2️⃣ Stable Diffusion, a text-to-image model, has been trained with billions of images with English captions, images by more than 1800 artists, and special databases focused on fictional characters. The more images we put on the web, the better the model gets at understanding our prompts.
So now that you know the basics of what’s going on in the background, let’s take a look at some concrete applications of AI in our daily lives.
Btw, here's our list of fun ai tools worth exploring:
Real applications of generative AI models?
Affordable and easy-to-use AI applications are flourishing these days.
So let's examine some real examples of how people are using generative AI:
1. AI for text generation
Anna, a small business owner, just published a new blog post she wrote using this AI writing tool called Jasper. She wrote the prompts for the tool, including the topic for the blog post, the tone in which it should be written, and the main points she wanted to mention. After clicking Generate, she got her blog post in seconds.
📝 This is an example of AI being used for text generation.
It is the process of automatically creating natural language text from different input data based on large language models. It is being used to create multiple forms of written content, such as blog posts, social media copy, emails, and more.
📝 Best AI text generators: ChatGPT, Jasper, Writer
2. AI for image generation
Mark just tested how AI text-to-image works. He decided to try out Stable Diffusion, the latest text-to-image generative model from Stability AI. He visited their demo page, typed in the text prompt, and the AI generated 4 different realistic images for him in 20 seconds.
🖼 This is an example of AI being used to generate images from text.
Image generation can be used in areas like digital art, computer graphics, medical imaging, or just for fun.
🖼 Best AI image generators: Stable Diffusion, DALL·E 2, Midjourney
3. Voice generation:
Nina needed a voiceover narration for her product demo video, but didn’t want to record herself. She used Descript Overdub, a text-to-speech generator that allowed her to create the narration by simply typing in text. She was able to choose from a variety of stock AI Voices that are indistinguishable from human voices, and got her narration in seconds.
🗣 This is an example of AI being used to create realistic voices from text.
AI voice generation can be used to create virtual assistants, improve accessibility for people with speech disabilities, create engaging videos, and more.
🗣 Best AI voice generators: Synthesia, Murf.ai, Listnr
4. Video generation:
Andrew is an HR professional who is responsible for onboarding new employees. He wanted to make the onboarding process more enjoyable, so he decided to create personalized onboarding talking-head videos using Synthesia. All he had to do was select an AI avatar, type in his script, and the talking head video was generated in minutes.
📹 This is an example of AI being used to create videos.
It can be used to create talking head videos from text for marketing, training, corporate communications, and more.
See how it works in this short video:
📹 Best AI video generators: Synthesia, Pictory, Runway.ml
I’m sure these thoughts have occurred to you while reading this article:
- Is AI stealing people’s jobs?
- Will AI completely replace humans?
- Should we be afraid?
Indeed, the truth is that Generative AI brings forth numerous benefits that are already changing the way we work, so let’s delve a bit deeper.
Benefits of generative AI
A recent report by Bloomberg predicts that generative AI is to become a $1.3 trillion market by 2032. In other words - it’s poised to explode.
And while this prediction may feel a bit distant, here’s the thing: AI will impact each and every business we know. It will change the way we work, communicate, and approach different problems.
Why? Simple – because it has many advantages we can benefit from.
#1 Creative output
Generative AI can produce original and captivating content.
#2 Efficiency and automation
Generative AI can automate complex tasks and save time.
Generative AI can tailor experiences and recommendations to individuals.
#4 Problem solving and simulation
Generative AI can simulate and model complex scenarios.
#5 Data augmentation and synthesis
Generative AI can synthesize data for improved model performance.
Thanks to these advantages, we are witnessing a proliferation of new AI applications across diverse industries. Here are some concrete examples:
However, when it comes to creativity, things get a bit more complicated..
Is generative AI actually creative?
Ok, AI can outperform humans in producing new content, but does that mean it’s actually being creative?
When we talk about generative AI and creativity, we bump into the question of human involvement in the process.
Yes, AI can come up with different ideas for blog titles.
Yes, it can create a new soundtrack for a video game.
Yes, it can write a unique script for a TV show
But — it can only do this based on prompts.
And behind those prompts, there’s a real person, their ideas, and perhaps most importantly, their intention about what to do with the AI-generated piece content.
Therefore it’s important to note that AI does not replace the creative process of humans. It’s rather used to supplement it by providing new ideas, helping to spark more creativity, and making the execution super easy.
Another question that comes to mind:
When generative AI creates content based on large sets of already created data.. Can the outputs really be that unique? 🤔
This definitely is food for thought and worth further discussion.
But then again, think about the content people create without the help of AI: the blog posts we write, the videos we produce, the social media posts we create.. Can we really say those are unique? I don’t think so.
What makes the content unique is actually contextualization, and that’s something that machines can’t do yet.
Empathy? Irony? Emotion?
It’s up to creators to come up with ideas, and AI is here to assist us with execution.
And now that we’ve delved into almost-philosophical questions — are you ready to go even deeper?
Let’s talk generative AI and art.
Can generative AI create art?
Generative AI is fundamentally reshaping the way we think about creativity, communication, and identity. Whether it’s synthetic voice in Hollywood films or virtual influencers modelling high end fashion, long gone are the days where the synthetic can automatically be contrasted to the authentic.
Henry Ajder, leading expert on synthetic media and virtuality
Some claim that these new AI tools, coupled with new ways of distributing content, such as social media, taste communities and NFTs, are actually democratizing art.
And it’s true.
What once required very specific technical knowledge and skills has become accessible to anyone. The tools for creating content with generative AI are open to the public, extremely easy to use, and some of them can even be used for free. 🤖
That means that AI actually shortens the time between idea and execution in the so-called artistic process. It opens up numerous possibilities for creators and replaces the need for manual craftsmanship, which is great.
But opponents have their arguments, too.
Some believe that the damage to the art world has already been done, as generative AI tools have already been trained on artists’ work.
So where’s the line between the original idea and the copy?
When a person prompts the AI to generate art “in the style of Picasso,” whose art is it?
And what actually makes art art? Is it the manual human skill that’s being replaced by AI, or is it the whole context around it?
Do we admire Guernica because of how it looks, or because of the idea it represents?
The future of generative AI
One thing is for sure: generative AI is here to stay and more and more people will start to see its benefits.
We believe that the cultural understanding of media will change radically in the coming years. The cost and skill barriers to content creation are evaporating, and new, altered forms of communication are on the rise. These will change the way we communicate with each other, both on a personal level and in a broad media context.
Victor Riparbelli, Synthesia CEO
As with any new technology, there will be bad actors, but let’s not forget that the technology’s gist has always been how we, as humans and societies, employ it.
It’s clear that generative AI is opening up new possibilities not only for work, but also for creative expression. This will definitely challenge our perception of where the digital realm begins and ends — and maybe that’s the real beauty of it.
And now that you know A LOT about the current state of generative AI, here's some future predictions: