Jack Bosma: Skillshare User
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SUBSCRIBE FOR A COOKIE! Accomplishments: - Raised $20,000,000 To Plant 20,000,000 Trees - Removed 30,000,000 pounds of trash from the ocean - Built wells in Africa - helped 1,000 blind people see - helped 1,000 deaf people hear - Given millions to charity - Started my own snack company Feastables - Donated over 100 cars lol - Gave away a private island (twice) - Gave away 1 million dollars in one video - Counted to 100k - Read the Dictionary - Read Bee Movie Script - Read Longest English Word - Watched Paint Dry - Ubering Across America - Watched It's Every Day Bro For 10 Hours - Ran a marathon in the world's largest shoes - Adopted every dog in a shelter - Bought $1,000,000 in lottery tickets - Sold houses for $1 - I got buried alive - Recreated Squid Game in real life - Gave away a chocolate factory - Gave away private jet - Survived 50 hours in Antarctica You get the point haha
Află metode moderne de tratament și îmbunătățire a sănătății prin metode naturistebazate pe cercetări medicale relevante. Ne propunem să oferim informații generale și să stimulăm creșterea personală. Abonează-te pentru conținut actualizat și valoros, și pornim împreună în această călătorie de descoperire și creștere personală. Canalul nostru YouTube furnizează informații educative și informative. Cu toate acestea, nu înlocuiește sfaturile, diagnosticul sau tratamentul medical profesionist. Consultă specialiștii pentru sfaturi medicale. Autodiagnosticarea și auto-tratamentul pot fi periculoase. Nu utilizați informațiile de aici pentru a evita sau amâna consultarea unui profesionist medical. Sunteți responsabil pentru acțiunile dvs. și nu îmi asum răspunderea pentru eventualele riscuri sau consecințe asociate utilizării informațiilor prezentate."
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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.
Udacity User: Jack Bosma https://community.udacity.com/u/4bd7ad10 Let's collaborate! Thanks, Jack Bosma https://meetn.com/jackbosma tutorjacknetwork@gmail.com "Inspect what you expect."
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