Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
Step aside, LLMs. The next big step for AI is learning, reconstructing and simulating the dynamics of the real world.
The pressure to produce faster has overshadowed the need to think deeper. As knowledge workers face mounting expectations to deliver insights, recommendations, and strategic decisions that carry real ...
BioRender provides a rich set of tools for creating highly accurate images from biology. The tools provide a visual language to support AI in the biological domain. Notation and diagrams are essential ...
CLIP is one of the most important multimodal foundational models today. What powers CLIP’s capabilities? The rich supervision signals provided by natural language, the carrier of human knowledge, ...
Abstract: As AI technology evolves, seeing is not believing. The boundary between human and machine creativity is increasingly blurred, presenting challenges for the art industry. This is more ...
Abstract: With the rise of AI-generated content in creative fields like film and animation, assessing its visual perception quality has become a major challenge. Traditional evaluation methods often ...
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