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Synthesis of new visions has witnessed significant advances recently, with Neural Radiance Fields (NeRF) pioneering 3D representation techniques through neural rendering. While NeRF introduced innovative methods to reconstruct scenes by accumulating RGB values ​​along sampling rays using multilayer perceptrons (MLPs), it encountered significant computational challenges. The extensive ray point sampling and large neural network volumes … Read more

Progress in multimodal intelligence depend on processing and understanding images and videos. Images can reveal static scenes by providing information about details such as objects, text, and spatial relationships. However, this comes at the cost of being extremely challenging. Video understanding involves tracking changes over time, among other operations, while ensuring consistency across frames, which … Read more

Artificial intelligence models have advanced significantly in recent years, especially in tasks that require reasoning, such as mathematics, programming, and scientific problem solving. But these advances come with challenges: computational inefficiency and a tendency to overthink. Overthinking in artificial intelligence occurs when models engage in overly lengthy reasoning, leading to increased inference costs and slower … Read more

Advances in artificial intelligence (AI) and machine learning (ML) have enabled transformative advances across various fields. However, the “systems domain” that focuses on optimizing and managing basic AI infrastructure remains relatively underexplored. This domain involves critical tasks such as diagnosing hardware problems, optimizing configurations, managing workloads, and evaluating system performance. These tasks often pose significant … Read more