TV Delivery (Caught on Blink Doorbell)

ATLANTA, GA - A neighbor shared this video after noticing that a neighbor from the apartment complex took their recently delivered television. 

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Why Hollywood Elites Don’t Want You To Watch Sound Of Freedom

In this short clip PBD, Lauren Chen, Adam, and Vinny discuss why Hollywood Elites Don’t Want You To Watch Sound of Freedom.

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How To Handle A Fake Cop! #law #education

3 Ways To Deal With A Fake Cop! Subscribe to@LawByMike for more!  Watch part 1 "3 Signs You're Talking to a Fake Cop!" here: https://youtube.com/shorts/xNCkLacEbD0

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Hey, you might think that this info makes me your lawyer, but it doesn’t and I’m not. Sorry, but I AM NOT YOUR LAWYER unless we have an engagement agreement. I am just providing public information here, like a library does, and am not providing you with legal advice about your situation. So, it would be totally unreasonable for you to conclude we have an attorney-client relationship just because you're viewing this information.

Mike’s Cube Code – Computerphile

Coping with code to constantly count configurations of cubes can cause considerable consternation. Can Computerphile contributor Mike’s concoction continue calculating complete cube configurations or culminate in catastrophe?

Mike's Github link:
https://github.com/mikepound/cubes/ 

Repository that did this first a few years ago 😊
https://github.com/noelle-crawfish/Enumerating-Polycubes 

 
Wikipedia article:
https://en.wikipedia.org/wiki/Polycube 

The page that enumerated up to n=16

Polyominoes Enumeration (kevingong.com) 
http://kevingong.com/Polyominoes/Enumeration.html 

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This video was filmed and edited by Sean Riley.

Computer Science at the University of Nottingham: https://bit.ly/nottscomputer

Computerphile is a sister project to Brady Haran's Numberphile. More at http://www.bradyharan.com

How one kid caused the apocalypse for MrBeast in Chile

MrBeast tells about his trip to Chile when they exposed his location.

Being widely known can indeed bring about significant changes to a person's social life, both positive and negative. Here are a few considerations:

Increased attention and scrutiny: When someone becomes widely known, they often attract increased attention from the public and media. This attention can lead to heightened scrutiny of their actions, words, and personal life. Privacy may become more challenging to maintain, and interactions with others may be subject to intense public scrutiny.

Limited anonymity: Widespread recognition can make it difficult to have a sense of anonymity in public spaces. People may approach or recognize the individual regularly, which can impact their ability to move freely and have spontaneous interactions without being recognized or interrupted.

Changes in social circles: Being widely known can alter social dynamics and relationships. Existing friendships may be affected as the person's public image or responsibilities change. Some individuals may pursue relationships with the person due to their fame or seek to be associated with them for personal gain, making it harder to discern genuine connections.

Trust and authenticity: It can be challenging to determine the true intentions of others when one becomes widely known. People may approach them with ulterior motives or act differently around them, making it important to navigate relationships with caution. Establishing genuine connections and trusting others may become more difficult due to concerns about motives or expectations.

Emotional toll: Dealing with public attention, criticism, and constant scrutiny can be emotionally demanding. Coping with the pressures and expectations that come with being widely known may require additional emotional support or self-care strategies to maintain well-being.

It's important to note that the specific challenges and experiences of being widely known can vary greatly depending on factors such as the person's individual temperament, the level of fame, and the industry or context in which they gained recognition. Some individuals may find ways to manage these challenges effectively and continue to maintain a fulfilling social life, while others may find it more burdensome.

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Compliant Mechanisms that LEARN! – Mechanical Neural Network Architected Materials

This video introduces the world’s first mechanical neural network that can learn its behavior. It consists of a lattice of compliant mechanisms that constitute an artificial intelligent (AI) architected material that gets better and better at acquiring desired behaviors and properties with increased exposure to unanticipated ambient loading conditions. It is a physical version of an artificial neural network used in current machine learning technologies.

To learn more about the content of this video, I encourage you to read the following publications, which can be accessed at the provided links:

[1] Lee, R.H., Mulder, E.A.B., Hopkins, J.B., 2022, “Mechanical Neural Networks: Architected Materials that Learn Behaviors,” Science Robotics, 7(71): pp. 1-9
https://www.science.org/stoken/author-tokens/ST-809/full

[2] Lee, R.H., Sainaghi, P., Hopkins, J.B., 2023, “Comparing Mechanical Neural-network Learning Algorithms,” Journal of Mechanical Design, 145(7): 071704 (7 pages)
https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/145/7/071704/1160625/Comparing-Mechanical-Neural-Network-Learning?redirectedFrom=fulltext

Part files to fabricate the mechanical neural network can be downloaded on Thingiverse using this link:
https://www.thingiverse.com/thefactsofmechanicaldesign/designs

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Acknowledgements:
Special thanks to Ryan Lee, Erwin Mulder, and Pietro Sainaghi who helped fabricate, test, and simulate the mechanical neural network in the video. I am also grateful to my AFOSR program officer, “Les” Lee, who funded the research that this video features. 

Brain Scan Attribution: 
Christian R. Linder, CC BY-SA 3.0 http://creativecommons.org/licenses/by-sa/3.0/, via Wikimedia Commons
https://commons.wikimedia.org/wiki/File:Brain_chrischan_600.gif
https://upload.wikimedia.org/wikipedia/commons/0/0d/Brain_chrischan_600.gif
Microstructure Image Attribution:
Edward Pleshakov, CC BY 3.0 https://creativecommons.org/licenses/by/3.0, via Wikimedia Commons
https://commons.wikimedia.org/wiki/File:CrystalGrain.jpg 
https://upload.wikimedia.org/wikipedia/commons/c/cd/CrystalGrain.jpg 
Body Armor Attribution: 
https://commons.wikimedia.org/wiki/File:MultiCam_IOTV.jpg 
https://upload.wikimedia.org/wikipedia/commons/8/8e/MultiCam_IOTV.jpg 

Disclaimer: 
Responsibility for the content of this video is my own. The University of California, Los Angeles is not involved with this channel nor does it endorse its content.