For the past decade, AI has brought digital transformation from industrial automation, such as in visual inspection and predictive maintenance, to our everyday life. AI powers the search results we... 더 읽어보기 >>

The following blog post is from Jack Ferrari, Edge AI Product Manager, Joe Sanford, Senior Application Engineer, and Reed Axman, Strategic Partner Manager. We recently attended the Edge AI... 더 읽어보기 >>

As hospitals integrate more advanced patient monitoring systems, the ability to process, analyze, and act on real-time medical data has become critical. Traditional monitoring systems generate large... 더 읽어보기 >>

MATLAB makes it easy to integrate Python®-based AI models into your MATLAB and Simulink workflows. You can call PyTorch® and TensorFlow™ models - or any Python code - directly from MATLAB. For... 더 읽어보기 >>

In computer vision, pretrained models are often used and adapted to the task at hand by performing transfer learning. Transfer learning involves modifying and retraining a pretrained network with... 더 읽어보기 >>

Deep neural networks like convolutional neural networks (CNNs) and long-short term memory (LSTM) networks can be applied for image- and sequence-based deep learning tasks. Graph neural networks... 더 읽어보기 >>

Today is the last day of 2024. Most of you are busy with non-AI, non-programming, non-thinking-about-work preparations for the new year. Nevertheless, I wanted to wrap up this year by looking back... 더 읽어보기 >>

As NeurIPS 2024 comes to a close, I am thinking back to all the inspiring presentations and conversations with brilliant AI researchers. It was clear that scientists are committed to bringing the... 더 읽어보기 >>

In this previous blog post, we explored the key aspects and benefits of transformer models, described how you can use pretrained models with MATLAB, and promised a blog post that shows you how to... 더 읽어보기 >>

In the world of deep learning, transformer models have generated a significant amount of buzz. They have dramatically improved performance across many AI applications, from natural language... 더 읽어보기 >>