Even if you’re not very familiar with deep learning, you’ve probably heard about it and how it can, among
other things, help automate the driving experience, increase manufacturing efficiency and change the consumer
shopping experience.
Neural network controllers provide complex robots with stability guarantees, paving the way for the safer deployment of autonomous vehicles and industrial machines.
Researchers at EPFL have made a breakthrough in understanding how neural network-based generative models perform against traditional data sampling techniques in complex systems, unveiling both challenges and opportunities for AI's future in data generation.
In this podcast, Sean Hehir, CEO of BrainChip, chats with Dr. Jason K. Eshraghian about neuromorphic computing benefits over traditional AI and its potential to revolutionize the future of computing. Listen in to learn how this emerging technology is shaping the world of AI.
In this episode, we discuss research coming out of the Karlsruhe Institute of Technology to detect the emotions of tennis players better than humans can!
NVIDIA TAO and Edge Impulse integrate to streamline the development and deployment of edge AI models, empowering developers to quickly build and optimize AI applications for diverse hardware environments.
Researchers at EPFL have developed a new, uniquely modular machine learning model for flexible decision-making. It is able to input any mode of text, video, image, sound, and time-series and then output any number, or combination, of predictions.
In this episode, we talk about MIT researchers making a smart tool (like a robot scientist) that uses AI to understand and explain how other AI brains (neural networks) work.
Imagine a task that used to take 11 minutes now taking less time than the blink of an eye. Couple that speed increase with 97% accuracy, and these are the results researchers achieved when combining ML, neural networks and novel compression in a new project advancing reservoir production forecasts.
Learn more about a groundbreaking solution called Temporal Event-based Neural Networks (TENNs) developed by BrainChip, which efficiently combines spatial and temporal convolutions to process sequential data like never before.