Artificial Intelligence
We are Leading research and development across the entire spectrum of AI.
Rayvector Research and development brings AI to its core capabilities pushing the boundaries of what’s possible, and shaping the future of AI. We at Rayvector are working on the core fundamental technology the world loves to witness. Our AI Research includes both Fundamental and Applied research with foundation of mathematics and physics.
Do you have an unresolved problem? We would love to talk over and solve it. Our group of core research engineers are ready to take on . Talk to us to see what is possible for your industry and business.
Synthetic Data Generation
We are the leading research and development across the entire spectrum of AI.
AI is data hungry. The smartness in Artificial Intelligence (AI) is a factor of how much data we allow our AI systems to absorb and learn and how well the datasets provide a full and comprehensive view of the subject we are attempting to digitise.
What is synthetic data?
Synthetic data is any type of data generated using a computer that takes the place of real data. Rayvector specialises in the computer generated,photo realistic annotated images of 3D environments containing objects, things, people.
How does our synthetic data generation help industries?
Synthetic data is any type of data generated using a computer that takes the place of real data. Rayvector specialises in the computer generated,photo realistic annotated images of 3D environments containing objects, things, people.
How does our synthetic data generation help industries?
“Rayvector’s technology creates synthetic data that gives companies the ability to create photo-realistic 3D worlds and extract unlimited synthetic data to train their visual AI models. Instead of spending months just finding 100,000 real-world images to train a visual AI system, Rayvector’s synthetic data software creation platform can be used for AI training to generate the same number of high-quality images over the course of a couple of days and up to 80% reduction in real-world images needed for accurate training.
Synthetic data in AR/VR
Synthetic data to train AR and VR models ranging from hand pose estimation to people segmentation, gesture recognition to natural scene understanding.
Areas of Expertise
Computer Vision
Building efficient architectures and algorithms for understanding, segmenting and classifying images and videos.
Machine learning
Deep learning through ML for generative models, graph learning,, including quantum, geometric, and Bayesian deep learning.
Neural Networks
Improve decision predictions in areas such as Computer Vision,NLP,Medical and disease prediction.
Reinforcement Learning
Learning to optimise through supervision, reinforcement learning, and Bayesian optimization.
Generative Adversarial Networks (GANs)
Exciting and rapidly changing field, delivering on the promise of generative models in their ability to generate realistic examples across a range of problem domains.
Natural Language Processing (NLP)
Talk it, Type it, Sound it. We process it, we recognise it.
