To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.
To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.
New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.
This article explores TPU vs GPU differences in architecture, performance, energy efficiency, cost, and practical implementation, helping engineers and designers choose the right accelerator for AI workloads today!
Training AI models is costly, forcing a trade-off between compressing large models or accepting weaker performance from smaller ones trained from scratch.
A team that included Chongzie Zhang from McKelvey Engineering developed a method that allows robots to teach other robots with different features to perform the same task.
To advance modern medicine, EPFL researchers are developing AI-based diagnostic tools. Their goal is to predict the best treatment a patient should receive.
New research uses AI to improve training of sensorimotor skills in human subjects, with potential applications ranging from performing surgery to perfecting tennis serves.
Shadow Robot’s partnership with Google DeepMind exemplifies how collaboration drives innovation in robotics and AI. This article explores how their expertise in dexterous robotic hands, particularly the DEX-EE, is advancing machine learning research.
Building on the success of conventional wearables, smart rings have been enthusiastically embraced by early adopters with a finger on the pulse of cutting-edge yet fashionable health and fitness wireless products.
NPUs are integrated units that excel in real-time AI tasks on edge devices like smartphones and IoT systems with low power consumption. TPUs are standalone processors designed for large-scale AI workloads in data centers, delivering exceptional performance in deep learning tasks.
Learn how agnostic systems like Awentia's No-Data Vision Foundation Model addresses key barriers to AI adoption such as data dependency, cost, and complexity across industries like agriculture, robotics and manufacturing.
For this article we interviewed Niwa and Omura, who are responsible for the design, development, and operation of the system, as well as Toda, who requested its development and is also a user.
Generative AI has evolved to become an advanced, general-purpose technology that has reached the level of practical use, and the usage scenarios have become more familiar applications. Nowadays, the application of AI including generative AI has even expanded into the field of sports.
EPFL researchers have developed 4M, a next-generation, open-sourced framework for training versatile and scalable multimodal foundation models that go beyond language.