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KENYA NEWS ALERT TV

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Welcome to our channel dedicated to the dynamic world of Kenyan politics! Here, we dive deep into the issues shaping the nation, from grassroots movements and youth activism to the latest political developments and government policies. Join us for insightful discussions, expert analyses, and engaging interviews with political analysts, activists, and thought leaders. We cover everything from recent protests and their implications for East African regional politics to the promises made by current leaders and the realities on the ground.Don't forget to subscribe and hit the notification bell to stay updated on our latest videos! Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for fair use for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.

Providing Motivation and Sales Lessons that can Create Financial Abundance via Merchant Sales

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In this channel, you will find detailed merchant service sales tips & motivation from real-life journeys/adventures meant to encourage you to OWN YOUR LIFE To OWN YOUR LIFE means to have freedom of time, money, & health. This business creates 2 of those, and I am here to help you achieve it quicker than figuring it out by yourself. Visit the links below for additional resources Become a PRO!!! Just copy what works in EZ Pay's 28 Day Merchant Sales Mastery Course - http://coaching.ezdirectsales.com Join Joe Wagner & the EZ Team for training, support, and systems to operate your business at http://ezdirectsales.com View our Sales Partner's testimonials about their success and what to expect when working with EZ Pay at https://training.ezdirectsales.com/partners-testimonials Download the free eBook "If I Lost It All Today" at https://promo.ezdirectsales.com/free-book For an overview of all Joe Wagner's coaching, gear, and announcements visit http://joewagnercoaching.com

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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.