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Mass Accountability

269  Followers

I am a freelance, independent and investigative journalist, I focus on public officials, civil and our community rights. Anyone that is monetized and wants to share my video contact me before permission, reuse or republishing my video. I also ask that you give me recognition of being the videographer. Any mainstream media, newspaper including local or company that is affiliated with anything mainstream does not have my permission and needs to ask before they try to republish my work. If I find any copyright violations they will be flagged and contacted. Thank you so much for your support, please continue to like share and tell your friends, family and even strangers to subscribe!! We will bring Unity back to community!! I have been asked how people can help with donations for my time. Here is my PayPal and CashApp. Thank you for all the support!! 💚💛❤ To Contact Email: massanetwork44@gmail.com paypal.me/MassAccountability CashApp: https://cash.app/$MassAccountability44

An Archive For The Masses - Daily Uploads!!

56  Followers

This is a home for any information that seems to be suppressed, censored, punished, held back, ridiculed, mocked, or in any way treated as though other people have a right to decide what YOU can and cannot see. You don't have to believe everything you see or read, but you still have a right to see or read it, and that's the point here. Make your own choices, you 've got your own beliefs, and all I want is for you to have access to as much information as possible, as information is power, and power is influence, and we need balance restored.

Mass Awakening

48  Followers

My name is Shoshi Herscu, an investigative journalist and activist from Israel. My book, Mass Awakening, tells the story of my personal awakening, as well as that of all humanity, to the massive deception of the world’s Elite controllers and their devastating agendas. It is an exposé on dark agendas and how people are fighting back offering hope for the future. I could’ve gone into denial, but Mass Awakening is my way of “fighting back” by documenting humanity awakening to these generational abusers.

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.

9  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.

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