Fishing Walleye Striper Crappie Trout Catfish Bluegill
9 FollowersFishing for Lake Erie Walleye, Ohio River Hybrid Striper Bass, Catfish Deer Creek, Paint Creek Crappie, Alum Creek Bluegill, Mad River Brown Trout.
Code Blue Cam
1,033 FollowerBlue Cam Series
17 FollowersWelcome to Blue Cam Series! This channel features BWC footage of police officers on duty.
Wealth & Career Blueprint
7 Followers💸 Welcome to Wealth & Career Blueprint 💼 Money. Success. Growth. We all want them—but let’s face it, traditional advice can be dry, confusing, or just plain overwhelming. That’s why we’re here. At Wealth & Career Blueprint, we break down complex topics—from mastering your finances to advancing your career—in a way that’s clear, relatable, and grounded in real experience. No fluff. No jargon. Just solid insights, storytelling, and practical strategies you can actually use. What you’ll find here: ✅ Smart financial tips to grow and manage your money 💰 ✅ Career strategies to help you land the right opportunities 🚀 ✅ Mindset and productivity tools for long-term success 💡 No matter your background, we’re here to make success feel achievable. 👣 If you're ready to take control of your future, follow the channel and explore the content—one step, one story at a time.
CaptBlueBeard
12 FollowersCode blue cam
18 FollowersThis channel delivers unbiased and genuine footage of incident captured by body cameras
The Camel Care Blue Zone Community Program Process Steps
8 FollowersThe Camel Care Blue Zone Community Program Process Steps The Camel Care Blue Zone Community Program Process Steps Step 1. Registration and Sharing: https://www.eventbrite.ca/e/1368919427859?aff=oddtdtcreator Step 2. Subscription And Comment: https://www.youtube.com/@CamelCareBlueZoneLiveTo100 Step 3. Course Material Download Link: https://camelcare.ca/product/master-the-path-of-professional-success/ Step 4. Classroom: https://meetn.com/camelcare101 Sign in MEETN PASSCODE:1350 Let's collaborate! Thanks, Jack Bosma Digitologist 1-862-200-1469 tutorjacknetwork@gmail.com https://www.facebook.com/jack.bosma https://www.linkedin.com/in/jack-b-bosma/ https://rumble.com/user/JackBBosma https://www.skool.com/@jack-bosma https://t.me/jackbosma https://www.udemy.com/course/interviewstexterviews-with-jack-bosma-i/ https://www.udemy.com/courses/search/?src=ukw&q=VETERANSWERS https://wa.link/c9h5bn https://api.whatsapp.com/send?phone=18622001469 https://x.com/JackBosma4 https://www.youtube.com/@jackbbosma2025 "Inspect what you expect."
Call of Duty Black Ops 6 With BlueVoyager
6 FollowersWhere gamers are free!
Project Blue 〘CarlyChannel〙
8 FollowersI'm Carly.H, a freelance artist who sometimes makes content for small creators. Creator of Regain Control | 2000s-2010s Gamer | VA | 💙#PNGTuber
BlueBodyCams
6 FollowersUsers 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 FollowersWe’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.