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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.

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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.

Second Rate Saints

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This podcast is produced by a small team of passionate, God fearing Christians who have no greater passion than to worship the Lord. However, we've never been to good at singing. Thankfully, the Lord has blessed us with a passion for learning, exploring the word of God, and asking the tough questions that so many never even think to ask. So if diving into the word of the Lord in a thoughtful, intellectual, and edifying way sounds interesting to you, come and tune in to our weekly discussion and hopefully you can learn something from these Second Rate Saints!

Cockatiel Singing

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Welcome to our cockatiel singing channel, here you will find cockatiel songs to train your cockatiel to sing. See below the subjects that we are going to talk about here on our channel cockatiels singing: Cockatiels singing Cockatiel songs to train cockatiels, Cockatiel songs to cheer up, Cockatiel Whistling, original cockatiel song, cockatiel, cockatiels, cockatiel singing, cockatiel singing, cockatiel whistle ,cockatiel singing, cockatiel whistling,cockatiel singing,whistling for cockatiel,cockatiel hissing,cockatiel calling,cockatiel original singing,cockatiel singing,cockatiel male singing,cockatiel singing own,cockatiel singing a lot,cockatielmale,singing,whistling,teaching cockatiel sing, sing, whistle