The optimism that deep neural networks, particularly those based on the Transformer design, will speed up scientific discovery stems from their contributions to previously...
In the rapidly evolving landscape of generative AI, concerns surrounding intellectual property rights have emerged as a critical issue. Companies like Getty Images, one...
In the realm of computer vision, a persistent challenge has perplexed researchers: altering an object's camera viewpoint with just a single RGB image. This...
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It has been said that information theory and machine learning are "two sides of the same coin" because of...
Researchers have introduced a cutting-edge framework called MUTEX, short for "MUltimodal Task specification for robot EXecution," aimed at significantly advancing the capabilities of robots...
In recent years, large language models (LLMs) have revolutionized the field of natural language processing, enabling unprecedented zero-shot and few-shot learning capabilities. However, their...
Understanding their surroundings in three dimensions (3D vision) is essential for domestic robots to perform tasks like navigation, manipulation, and answering queries. At the...
Unlike narrow or specialized AI systems designed for specific tasks, Artificial General Intelligence (AGI) can perform a wide range of functions that aim to...
Auditing Large Language Models (LLMs) has become a paramount concern as these models are increasingly integrated into various applications. Ensuring their ethical, unbiased, and...
Model merging refers to the process of combining multiple distinct models, each designed to perform separate tasks or solve different problems, into a single...
Transformers could be one of the most important innovations in the artificial intelligence domain. These neural network architectures, introduced in 2017, have revolutionized how...
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