All Videos Channels

AspectBMGA

4 Followers

Great Football Edits being uploaded every week! Muslim | 🇧🇩 | 14yo | Single 🙄😂 Idol/Favorite Player-Lionel Andrés Messi 🐐 Best Friends on YT till now ❤ -NOTGOAT7/GoatEditz 😍 -Gally 🥰 Achievements: 🥉Semi Finals in the Voting cup of GoatEditz 😀 🥇Winner in GoatEdit10190's Voting cup🏆 🥇Winner in Zaeditor's voting cup 💪 🥈 Runners up in GoatEdit10190's Euro voting cup 200 Subs-2/3/24 300 Subs-15/5/24 500 Subs-25/7/24 1K Subs-In January 2025 Inshallah💀

It encompasses the exploration and journeying aspect while hinting at the grandeur and mystery of the universe.

1 Follower

Welcome to Cosmic Quests, your portal to the wonders of the universe! Join us as we embark on a journey through the cosmos, exploring celestial phenomena, unraveling the mysteries of space, and delving into the latest discoveries in astronomy and astrophysics. From captivating nebulae to distant galaxies, let's embark on an epic voyage together to uncover the secrets of the cosmos. Get ready to expand your horizons and ignite your curiosity about the vast expanse beyond our world!"

"Hilarious Rumbles: The Best of Physical Comedy". This title highlights the physicality aspect of the comedy and promises a collection of the funniest moments.

1 Follower

Get ready to laugh until you fall off your seat! In this compilation video, we've gathered the most side-splitting and rib-tickling moments from the world of physical comedy. From classic pratfalls and slip-ups to epic fails and unexpected stunts, this video has it all. You'll see some of your favorite comedians and viral stars showcasing their mastery of physical humor, and you'll discover some new talents too. Whether you're a fan of slapstick, acrobatics, or just good old-fashioned silliness, you won't be able to stop chuckling as you watch these hilarious rumbles. So get comfortable, grab some popcorn, and let the laughter begin!

Welcome to Aspect Motivation channel

1 Follower

Welcome to Aspect Motivation, the place where you can find daily inspiration and motivation to help you reach your goals and live your best life. We believe that everyone has the potential to achieve greatness, and our mission is to help you unlock that potential. Whether you're looking to improve your health and fitness, advance your career, or simply become a better version of yourself, we've got you covered. Our videos are designed to provide you with practical tips, strategies, and insights to help you overcome obstacles, stay focused, and stay motivated on your journey. From inspiring stories of people who have overcome incredible challenges, to expert advice on goal-setting and productivity, our content is here to help you succeed.❤❤ So if you're ready to take your life to the next level, hit that subscribe button and join our community of motivated and driven individuals. Let's achieve greatness together! subscribe Please

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.

0 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.