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.
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EPFL researchers have developed 4M, a next-generation, open-sourced framework for training versatile and scalable multimodal foundation models that go beyond language.
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Using this model, researchers may be able to identify antibody drugs that can target a variety of infectious diseases.
GPUs excel in parallel processing for graphics and AI training with scalability, while NPUs focus on low-latency AI inference on edge devices, enhancing privacy by processing data locally. Together, they complement each other in addressing different stages of AI workloads efficiently.
A new technique identifies and removes the training examples that contribute most to a machine-learning model’s failures.
The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.
Researchers at Stanford Engineering have developed an AI-trained model to accurately recreate the hand movements of elite-level pianists and the physical stresses they endure while playing.
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According to , the global AI robotics market will reach $17 billion in 2024 and will keep growing by 24% annually. Today, robots deliver packages, conduct geological surveys, and entertain visitors of parks and exhibitions – however, that’s not the limit of their abilities.
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Brain–machine interfaces (BMIs) have enabled a handful of test participants who are unable to move or speak to communicate simply by thinking.
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A team of Caltech researchers has developed an analogous algorithm for autonomous robots—a planning and decision-making control system that helps freely moving robots determine the best movements to make as they navigate the real world.
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AI in the IoT also needs to be performed as close to the sensors as possible, all the way to the edge, on increasingly capable devices in terms of compute power.
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Creating realistic 3D models for applications like virtual reality, filmmaking, and engineering design can be a cumbersome process requiring lots of manual trial and error.
This new device uses light to perform the key operations of a deep neural network on a chip, opening the door to high-speed processors that can learn in real-time.
EPFL research investigating the potential impact on education of AI assistants has found that systems like GPT-4 can answer up to 85% of university assessment questions correctly.
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The method could help communities visualize and prepare for approaching storms.
