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AI trends in 2023: Graph Neural Networks

AssemblyAI

What is the current role of GNNs in the broader AI research landscape? Let’s take a look at some numbers revealing how GNNs have seen a spectacular rise within the research community. We find that the term Graph Neural Network consistently ranked in the top 3 keywords year over year.

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Researchers from the University of Oxford Developed a Deep Learning-Based Software for Precision Tracking of Fish Movement in Complex Environments

Marktechpost

Addressing these challenges, a UK-based research team introduced a hybrid method, merging deep learning and traditional computer vision techniques to enhance tracking accuracy for fish in complex experiments. The deep learning part involves the use of object detection and tracking.

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UCLA Researchers Propose PhyCV: A Physics-Inspired Computer Vision Python Library

Marktechpost

Artificial intelligence is making noteworthy strides in the field of computer vision. One key area of development is deep learning, where neural networks are trained on huge datasets of images to recognize and classify objects, scenes, and events. All Credit For This Research Goes To the Researchers on This Project.

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How to Visualize Deep Learning Models

The MLOps Blog

Deep learning models are typically highly complex. While many traditional machine learning models make do with just a couple of hundreds of parameters, deep learning models have millions or billions of parameters. The reasons for this range from wrongly connected model components to misconfigured optimizers.

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Microsoft Releases GRIN MoE: A Gradient-Informed Mixture of Experts MoE Model for Efficient and Scalable Deep Learning

Marktechpost

Artificial intelligence (AI) research has increasingly focused on enhancing the efficiency & scalability of deep learning models. These models have revolutionized natural language processing, computer vision, and data analytics but have significant computational challenges.

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Amazon Researchers Present a Deep Learning Compiler for Training Consisting of Three Main Features- a Syncfree Optimizer, Compiler Caching, and Multi-Threaded Execution

Marktechpost

The idea of compilation is a potentially effective remedy that can balance the needs for computing efficiency and model size. In recent research, a team of researchers has introduced a deep learning compiler specifically made for neural network training.

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This AI Paper Presents a Study on AIS (Androgen Insensitivity Syndrome) Testing Using Deep Learning Models

Marktechpost

The researchers improved the program’s ability to measure how bad the problem was. Researchers also categorized the type of spine curve just by looking at one picture. This problem statement fell under the class of Computer Vision and was a classification approach. If you like our work, you will love our newsletter.