As we enter a new dawn of creativity with the advent of diffusion models, machine learning is becoming prevalent in the creative industry through creative augmentation or project development.
We are excited to be launching the Digital Arts Research Lab thanks to the efforts of Exploring Intellect Enterprises.
The main goal of D.A.R.L will be to showcase and track the various changes and impacts of Creative Machine Learning on the Creative industry through various self initiated projects or partnerships.
Our creative projects explore the possibilities of the tools being created and how they can be effective in everyday self initiated or client creative projects.
We believe that the theoretical work on the nature and proper definition of creativity is to be performed in parallel with the practical work on the implementation of systems that exhibit creativity, with one strand of work informing the other. This way we creative enterprise CML-Ops solutions for companies that want to be at the forefront in delivering amazing solutions for their clients.
Artificial intelligence has always been an amazing field. In the early days, people thought that solving certain tasks (like chess) would lead to the discovery of human intelligence algorithms. However, the solution for each task turned out to be much less general than expected (e.g. a search over a large number of moves).
The last few years have been surprising again.
An AI technique studied for decades, deep learning, began to excel in a variety of problem areas. Rather than hand-coding a new algorithm for each problem, deep learning designs architectures that can be transformed into a wide range of algorithms based on the data given to them.
This approach has yielded excellent results in pattern recognition problems such as image object recognition, machine translation and speech recognition.
But we’ve also started to see what it would be like for computers to create, dream and experience the world.
Current AI systems have impressive , but limited skills.
It seems that we will continue to push their limits and, in extreme cases, they will reach human proficiency in virtually all intellectual tasks. It’s hard to imagine how much AI could benefit society on a human scale, and it’s just as hard to imagine how much it could harm society if built or used incorrectly.