The Power of Graph Neural Networks: Understan...

Right now, millions of people are simultaneously chatting with a system that remembers nothing, knows nothing, and resets after every message. The engineering keeping that illusion alive is actually the impressive part. ✨ Connect with us! Personal newsletter: https://defragzone.s ...  Show more

The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone. We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely understand their own technology. From blockcha ...  Show more

Today we’re joined by Sophia Sanborn, a postdoctoral scholar at the University of California, Santa Barbara. In our conversation with Sophia, we explore the concept of universality between neural representations and deep neural networks, and how these principles of efficiency pro ...  Show more

<span style= "color: #224422; font-family: 'Lucida Bright', Georgia, serif; font-size: medium;"> My guest this week is Anh Nguyen, a PhD student at the University of Wyoming working in the </span>

💻 Full tutorial: • Physics-Informed Neural Networks (PIN... Physics-Informed Neural Networks (PINNs) integrate known physical laws into neural network learning, particularly for solving differential equations. They embed these laws into the network's loss function, guiding the l ...  Show more

<span class="s1">RNNs are a class of deep learning models designed to capture sequential behavior.<span class= "Apple-converted-space"> </span> An RNN trains a set of weights which depend not just on new input but also on the previous state of the neural network.<sp ...