Exploring AI, what is artificial intelligence good for and how can we apply it?
There are many practical applications for AI. Of the many, I will only mention a few entry-level AI applications that interest me and our team at Mn8XR and MonkeyAI. My goal is to start exploring each practical area of Applied AI, and build a library of experience, knowledge, and successes and iterate on what works well. Here are a few applications that we are initially focusing on as well as a little history on how I have been gradually using AI in content creation.
Multimodal AI to create images (text to image)
This is one of the easiest applications of AI and many digital content creators who use AI are mostly using this technology. Just see the image I made above as the blog image header as an example. It’s an easy way to engage viewer interest. AI is currently trending due to new developments in Multimodal AI (text to image is an example of multimodal) and image diffusion advancements, led in part by Google, OpenAI, Midjourney and other creative AI services. Most of these applications are cloud-based computing that access large databases of images and AI training models (libraries), and provide basic root-level access to their AI to developers like MonkeyAI.
This technology isn’t new, I remember using Google Deep Dream AI over seven years ago to add all sorts of organic imagery to my existing images. I was impressed by the potential of the technology then and have dabbled in it over the years. There have been several other noteworthy apps and open source tools over the years, but this year Midjourney, Dall-E, and Disco Diffusion have really upped the game for believability and photoreal appearance to the human eye, which can be analyzed and confirmed using the MS COCO dataset for image “realness”. Some of the notable newer updates in this technology is the ability to use the style of virtually any known artist to get a result. For instance, you can enter a prompt of “/imagine a beautiful woman in the style of Pablo Picasso, and you will get an image of an AI-generated image that looks like it was painted by Pablo Picasso. The image database has so many of his images, that it’s easy for AI to recognize details of his style and replicate that in new original artwork. And honestly, many AI human characters tend to have a Pablo Picasso type jumble and juxtaposition in the facial features, that this is a perfect example. ;)Multimodal AI Speech (text to speech)
The spoken word is one of the most effective ways to communicate. Nowadays you don’t need a recording studio or to hire talent to record a voice-over for your content or app. You can create your voiceovers, narration for ebooks, products, instructional videos or anything, using AI for text to speech. Text to speech has been around forever, but now it uses AI to customize the sound and feel of each human AI voice, with control of speed, inflection, and more on each word or syllable. We can add emotions to the text prompts, such as happy, scared, serious, playful, sad, excited and more now. The results are astonishing. We used Google Voice API in 2 of my Unreal Engine projects in 2020 and 2021, to read educational trivia questions aloud in a WW2 Historical Educational app I designed, and to provide a synthesized voice for several Unreal Engine Meta-Human characters I made.Multimodal AI Music (text to music)
This is fascinating. You can use text prompts, referencing other songs, and music genres and styles to create new hybrid stylized music using Artificial Intelligence. My videos feature not only AI imagery and AI Voices, but the music is also created by Artificial Intelligence.
Multimodal AI Video (text to video) Well, this is just crazy. You can enter text prompts, to create animated videos. For instance, you can type the lyrics of a song, and the AI will use its best effort to create a video of what you want. The results are something that human artists are not able to replicate without thousands of times more time and effort. Deep Fakes are another new application for AI, and the best way to show both of these is to show what our AI Developer Mike Peterson has created in this video showing Deep Fakes and AI Diffusion Video. (play video below)
Machine Learning (ML)
Here is the definition: What is Machine Learning? | IBM
The most obvious useful function to me is using video cameras to collect data, and analyze it in multiple non-standard ways to collect unseen predictive data. For example multiple sensors at a production line can record temperature variations, vibration, and even noise levels to accurately predict system failure in advance. Other ideas are sensors that can understand human feelings based on data gathered from video and datasets of people’s faces and biofeedback metrics, to more accurately predict what they want, mean, or how they are responding to a learning module, or interactive experience to better gauge reactions, interest, and retention.Interactive experiences, VR, MR, AR, XR using AI
Extended Reality (XR) is the one of the most useful places to use AI. In Unreal Engine, we use behavior trees, and custom animations, and sound effects, to create user experiences that are different each time, and not based on traditional animation timelines or clips. In 2020 and 2021, I created PlayaVR, a Virtual Reality Burning Man art camp and art exhibition. We were blessed to collaborate with one of the best DJ’s and scratch masters in the world, DJ Qbert of The Invisible Skratch Piklz, and created an 3d AI version of him for our application. Our AI DJ Qbert rides a motorized monocycle, complete with a built in turntable and record cart, and he scratches different samples based on various inputs. We are excited to continue developing the DJ Qbert AI as the first AI Turntablist that guest DJs can feature in their shows, live streams, or VR/XR media. PlayaVR also features the AI work of Amin Ahktar, who is an official Pixologic Zbrush Livestreamer, Epic Fellowship graduate, and creator of Augmented Reality (AR) Toys Fungisaurs, who created some of our AI with his 3D models and animations.
AI apps, APIs, and cloud and website integrations
I really see this as the future of AI. The tech giants OpenAI, Google, and Amazon AWS have all provided the general public with access to their AI, and APIs to integrate new services. It’s worth noting, that almost anyone can learn to utilize cloud based AI to create applications, APIs, and website integrations using Artificial Intelligence. I have already created accounts on both OpenAI and Google, and watched some of the tutorials on writing apps that use their cloud based AI, and it actually looks pretty easy, compared to character animation and Unreal Engine development. I anticipate having my first few test AI apps within several weeks, then being able to integrate that into a website with an API is futher down the road, so that the AI apps can use the website better.
Conclusion: I think the future of this technology will one day manifest in one direction, as AI-managed websites. The AI will use more data than keyboard input, to analyze what the user means, needs, and wants, to create content that is more engaging or can lead to a sell. For instance, an AI could create website sales funnel pages, based on data it can turn into AI images, written content, spoken word, video content, high end transitions, and a call to action, and analyze and adjust based on web traffic metrics. I am sure someone else is thinking about all of this already, for a while… For now, it’s a fascinating, emerging new field that combines art and technology offering immense potential that can be applied immediately on many creative projects. Follow us as we show how to apply artificial technology and art to create content and media.
I am looking for creative ways to use this technology to help clients manifest their visions. If I can help you with design, imagery, web, or interactive experiences please contact me via email.
Click the Full Screen button on the middle right, and mouse wheel to pull the camera back and look around in 3d at AI Equilateral images.