Neural Synesthesia: When Art Meets GANs | Lionbridge AI

Neural Synesthesia is an AI art project that aims to create new and unique audiovisual experiences with artificial intelligence. It does this through collaborations between humans and generative networks. The results feel almost like organic art. Swirls of color and images blend together as faces, scenery, objects, and architecture transform to music. There’s a sense of things swinging between feeling unique and at the same time oddly familiar.

Neural Synesthesia creator Xander Steenbrugge says "Most of the datasets I use are image sets I’ve encountered over the years. I saved them because I knew one day I’d have a use for them. I’ve always had an interest in aesthetics so when I discover something that triggers that sixth sense, I save it.

Most GAN papers use datasets of more than 50,000 images, but in practice you can get away with fewer examples. The first step is to start from a pre-trained GAN model that has already been trained on a large dataset. This means the convolutional filters in the model are already well-shaped and contain useful information about the visual world. Secondly, there’s data augmentation, which is basically flipping or rotating an image to effectively increase the amount of training data. Since I don’t really care about sample realism, I can actually afford to do very aggressive image augmentation. This results in many more training images than actual source images. For example, the model I used for a recent performance at Tate Modern had only 3,000 real images, aggressively augmented to a training set of around 70,000."

Via:[https://lionbridge.ai/articles/neural-synesthesia-when-art-meets-gans/]

#ai #art #machinelearning #gans #artificialintelligence

What is GEEK

Buddha Community

ART + AI

The idea that AI can infiltrate the field of art is frightening and rightfully so. While it has been no secret that AI can definitely replace blue-collar jobs and possibly threaten white-collar jobs, the idea that it can impact the livelihood of artists isn’t one that the media has foretold, nor have dystopian movies explored. However, we can see early traces of AI in art. It has slowly seeped into written literature, journalism, paintings and even music.

Having said that, this isn’t a novel (😉) idea. Sometime in the 90s, a music theory professor trained a program to write Bach-styled compositions. Then, to his students, he played both the real and computer-generated versions. To them, both were indistinguishable. Since then, technology has rapidly improved to a state that AI can create music of its own.

#ai #art #artificial-intelligence #art-and-ai #is-ai-art-really-art #is-art-unique-to-humans #creativity #future

Neural Synesthesia: When Art Meets GANs | Lionbridge AI

Neural Synesthesia is an AI art project that aims to create new and unique audiovisual experiences with artificial intelligence. It does this through collaborations between humans and generative networks. The results feel almost like organic art. Swirls of color and images blend together as faces, scenery, objects, and architecture transform to music. There’s a sense of things swinging between feeling unique and at the same time oddly familiar.

Neural Synesthesia creator Xander Steenbrugge says "Most of the datasets I use are image sets I’ve encountered over the years. I saved them because I knew one day I’d have a use for them. I’ve always had an interest in aesthetics so when I discover something that triggers that sixth sense, I save it.

Most GAN papers use datasets of more than 50,000 images, but in practice you can get away with fewer examples. The first step is to start from a pre-trained GAN model that has already been trained on a large dataset. This means the convolutional filters in the model are already well-shaped and contain useful information about the visual world. Secondly, there’s data augmentation, which is basically flipping or rotating an image to effectively increase the amount of training data. Since I don’t really care about sample realism, I can actually afford to do very aggressive image augmentation. This results in many more training images than actual source images. For example, the model I used for a recent performance at Tate Modern had only 3,000 real images, aggressively augmented to a training set of around 70,000."

Via:[https://lionbridge.ai/articles/neural-synesthesia-when-art-meets-gans/]

#ai #art #machinelearning #gans #artificialintelligence

This Week in AI | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

This Week in AI - Issue #22 | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.Have fun!

Research Papers

• Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wild
• Slowing Down the Weight Norm Increase in Momentum-based Optimizers
• The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps
• AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks
• Coherent Reconstruction of Multiple Humans from a Single Image
• Variational Bayesian Monte Carlo with Noisy Likelihoods
• GNN3DMOT: Graph Neural Network for 3D Multi-Object Tracking with Multi-Feature Learning
• Are we done with ImageNet?
• How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds
• Background Modeling via Uncertainty Estimation for Weakly-supervised Action Localization
• The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps
• Image Deconvolution via Noise-Tolerant Self-Supervised Inversion
• Learning a Unified Sample Weighting Network for Object Detection

Articles

• Deepfake Detection Challenge Results: An open initiative to advance AI
• Slightly Unnerving AI Produces Human Faces Out of Totally Pixelated Photos
• NeoML Released as TensorFlow Alternative
• Google Meet takes on Zoom with AI-powered noise cancellation
• Open Compound Domain Adaptation
• Dense pose for animal classes with transfer learning
• 10 Ways Enterprises Are Getting Results From AI Strategies
• An understanding of AI’s limitations is starting to sink in
• Why we switched from Flask to FastAPI for production machine learning
• Simple Transformers
• The key differences between rule-based AI and machine learning
• Deep learning-based surrogate models outperform simulators and could hasten scientific discoveries
• HANDS-ON GUIDE TO OBJECT DETECTION USING YOLO
• Artificial neural networks that mimic the flexibility and computing power of the brain
• MIT researchers train AI to predict how humans paint works of art
• What Do Machine Learning Engineers Do Anyway?
• AI Is Amazing But Complicated, And We Don’t Necessarily Need To Plunge In Headfirst
• Deep learning networks track up to 100 animals simultaneously
• Is artificial intelligence changing art?

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution