All Videos Channels

"Revving Up with AutoPulse: Car Enthusiast's Paradise"

5 Followers

"Revving Up with AutoPulse: Car Enthusiast's Paradise" is your ultimate destination for all things automotive. Join us on a thrilling journey through the world of cars, where passion meets horsepower, and enthusiasts unite. Our channel is dedicated to catering to the needs and interests of car lovers, whether you're a die-hard gearhead, a weekend wrench-turner, or simply someone who appreciates the beauty and power of automobiles.Revving Up with AutoPulse" is more than just a channel; it's a community where car enthusiasts come together to share their passion, knowledge, and experiences. So, buckle up and subscribe to our channel for a thrilling ride into the heart of the automotive world!

Users can generate videos up to 1080p resolution, up to 20 sec long, and in widescreen, vertical or square aspect ratios. You can bring your own assets to extend, remix, and blend, or generate entirely new content from text.

4 Followers

We’ve discovered neurons in CLIP that respond to the same concept whether presented literally, symbolically, or conceptually. This may explain CLIP’s accuracy in classifying surprising visual renditions of concepts, and is also an important step toward understanding the associations and biases that CLIP and similar models learn. Fifteen years ago, Quiroga et al.1 discovered that the human brain possesses multimodal neurons. These neurons respond to clusters of abstract concepts centered around a common high-level theme, rather than any specific visual feature. The most famous of these was the “Halle Berry” neuron, a neuron featured in both Scientific American⁠(opens in a new window) and The New York Times⁠(opens in a new window), that responds to photographs, sketches, and the text “Halle Berry” (but not other names). Two months ago, OpenAI announced CLIP⁠, a general-purpose vision system that matches the performance of a ResNet-50,2 but outperforms existing vision systems on some of the most challenging datasets. Each of these challenge datasets, ObjectNet, ImageNet Rendition, and ImageNet Sketch, stress tests the model’s robustness to not recognizing not just simple distortions or changes in lighting or pose, but also to complete abstraction and reconstruction—sketches, cartoons, and even statues of the objects. Now, we’re releasing our discovery of the presence of multimodal neurons in CLIP. One such neuron, for example, is a “Spider-Man” neuron (bearing a remarkable resemblance to the “Halle Berry” neuron) that responds to an image of a spider, an image of the text “spider,” and the comic book character “Spider-Man” either in costume or illustrated. Our discovery of multimodal neurons in CLIP gives us a clue as to what may be a common mechanism of both synthetic and natural vision systems—abstraction. We discover that the highest layers of CLIP organize images as a loose semantic collection of ideas, providing a simple explanation for both the model’s versatility and the representation’s compactness.

Rise up and thrive

4 Followers

Welcome to our channel, the ultimate destination for anyone looking to achieve their goals and live their best life! Join us on a journey of personal growth and professional development as we explore the world of success, entrepreneurship, and motivation. With our expert advice, inspiring stories, and positive vibes, you'll learn how to overcome obstacles, unleash your potential, and create the life of your dreams. Whether you're an aspiring entrepreneur, a seasoned business pro, or simply someone who's hungry for success, our chaannel has everything you need to take your life to the next level. So what are you waiting for? Hit that subscribe button and let's get started! #motivation #business #successmindset #selfimprovement #inspiration #personalgrowth #financialfreedom