The Power of Graph Neural Networks: Understan...

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

VortexNet uses actual whirlpools to build neural networks. Seriously. By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies. Today we explain how vortex shedding, the Str ...  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 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 ...

هذا الجزء الثاني من سلسلتنا عن الذكاء الاصطناعي  ، أذا ماسمعت الجزء الاول انصحك تبدا فيه ، بنتكلم في هالحلقة عن استخدامات و تطبيقات تعلم الالة والذكاء الاصطناعي ، من السيارات ذاتية القيادة ، أنظمة فبركة الصوت والفيديو ، نظام ساهر لرصد المخالفات المرورية ، أنظمة توقع واستباق الاعط ...  Show more

In this episode of the SuperDataScience Podcast, I chat with Vice President of Research at Sentient AI, Risto Miikkulainen. You will hear about the applications of AI across multiple fields, learn about the 2 types of AI - the Evolutionary Algorithms and Reinforcement Learning Al ...  Show more