neural networks

Alex Shipps | MIT News In the current AI zeitgeist, sequence models have skyrocketed in popularity for their ability to analyze data and predict what to do next. For instance, you’ve likely used next-token prediction models like ChatGPT,…

Microchip just purchased Neuronix AI Labs to expand its ability to deliver power-efficient, AI-enabled edge solutions on FPGAs. Neuronix AI Labs provides neural network sparsity optimization technology that reduces power, size, and…

Neural networks are responsible for many AI breakthroughs, including large language models used in a wide range of applications. However, engineers and scientists struggle to understand their inner workings. Data and computer scientists at…

There’s a novel deep-learning approach to simplify the creation of holograms. With it, 3D images can be generated directly from 2D photos from a standard camera. The method streamlines hologram generation using a sequence of three deep…

Sorry, Shakespeare, I just had to use this headline as Neuralink, Elon Musk's brain-computer interface (BCI) start-up, is recruiting people for its first human trial—the goal is connecting human brains to computers. Initially, the company…

As long as things stay the same, warehouse robots accurately pick and place for shipment without problems. However, change the process, and you must reprogram the robot and retrain the system. MIT researchers developed a training…

Artificial neural networks solve complex tasks better than we can. They’re used in social media, streaming, online gaming, and other areas that target users with posts, movies, fun games, or other content that matches their individual…

Neuroscientists at MIT trained artificial neural network to take on a simple odor classification and the results were surprisingly accurate. Guangyu Robert Yang at MIT’s McGovern Institute for Brain Research led the work as a postdoc at…

Skoltech researchers have demonstrated certain patterns that can cause neural networks to make mistakes in recognizing images are similar to Turing patterns which are ubiquitous in the natural world. The discovery can be used to design…

What exactly goes on in the minds of machines that learn to see? Duke University’s computer science professor, Cynthia Rudin, set out to define exactly what happens in between input and output in deep learning models. The complexity…