4 Algorithms We Borrowed from Nature
We use algorithms every day for things like image searches, predictive text, and securing sensitive data. Algorithms show up all over nature, too, in places like your immune system and schools of fish, and computer scientists have learned a lot from studying them. Here are four ways our technology has improved thanks to algorithms we swiped from nature!
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Sources:
https://www.merriam-webster.com/dictionary/algorithm
https://www.pnas.org/content/108/46/18726
https://link.springer.com/chapter/10.1007/978-3-642-00267-0_9
Fly hashing:
https://www.slaney.org/malcolm/yahoo/Slaney2008-LSHTutorial.pdf
https://science.sciencemag.org/content/358/6364/793
https://science.sciencemag.org/content/suppl/2017/11/09/358.6364.793.DC1
https://medium.com/@jaiyamsharma/efficient-nearest-neighbors-inspired-by-the-fruit-fly-brain-6ef8fed416ee
Object recognition:
https://www.sciencedirect.com/science/article/abs/pii/S1361841517301135 (open copy at https://arxiv.org/pdf/1702.05747.pdf)
https://dev.to/clarifai/what-convolutional-neural-networks-look-at-when-they-see-nudity
http://www.cse.iitm.ac.in/~vplab/courses/CV_DIP/PDF/Feature_Detectors_and_Descriptors.pdf
http://www.cs.cmu.edu/~10701/slides/Perceptron_Reading_Material.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2718241/
https://knowingneurons.com/2014/10/29/hubel-and-wiesel-the-neural-basis-of-visual-perception/
http://www.scholarpedia.org/article/Neocognitron
https://www.frontiersin.org/articles/10.3389/frobt.2015.00036/full
https://www.rctn.org/bruno/public/papers/Fukushima1980.pdf
Anomaly detection:
https://blogs.oracle.com/datascience/introduction-to-anomaly-detection
ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf
https://dl.acm.org/doi/10.1145/283699.283742
https://link.springer.com/content/pdf/10.1007/s11047-006-9026-4.pdf
https://www.cs.unm.edu/~immsec/publications/virus.pdf
https://www.sciencedirect.com/science/article/abs/pii/S221421261630240X
https://link.springer.com/content/pdf/10.1007%2F978-3-642-59901-9.pdf
Swarm algorithms and TERMES:
https://www.sciencedirect.com/science/article/pii/B9780124051638000016
https://dash.harvard.edu/bitstream/handle/1/13068244/Petersen_gsas.harvard.inactive_0084L_11836.pdf
https://www.youtube.com/watch?v=t2e4GIZ3W1o
https://science.sciencemag.org/content/343/6172/754
Simulated annealing:
https://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/methods-for-determining-structure
https://www.annualreviews.org/doi/pdf/10.1146/annurev.pc.42.100191.001213
https://pubs.acs.org/doi/full/10.1021/acs.cgd.9b00517#
https://www.sciencedirect.com/book/9780124167438/nature-inspired-optimization-algorithms
https://www.sciencedirect.com/topics/materials-science/annealing
https://science.sciencemag.org/sites/all/libraries/pdfjs/web/viewer.html?file=/content/sci/220/4598/671.full.pdf
https://www.sciencedirect.com/topics/materials-science/simulated-annealing
https://link.springer.com/article/10.1007/s12559-015-9370-8
https://onlinelibrary.wiley.com/doi/abs/10.1111/itor.12001
Image Sources:
https://commons.wikimedia.org/wiki/File:Hubel%2Bwiesel.jpg
https://www.flickr.com/photos/niaid/29122039942
https://commons.wikimedia.org/wiki/File:Diagram_showing_the_position_of_the_thymus_gland_CRUK_362.svg
Видео 4 Algorithms We Borrowed from Nature канала SciShow
Hosted by: Hank Green
SciShow has a spinoff podcast! It's called SciShow Tangents. Check it out at http://www.scishowtangents.org
----------
Support SciShow by becoming a patron on Patreon: https://www.patreon.com/scishow
----------
Huge thanks go to the following Patreon supporters for helping us keep SciShow free for everyone forever:
Kevin Bealer, Jacob, Katie Marie Magnone, D.A. Noe, Charles Southerland, Eric Jensen, Christopher R Boucher, Alex Hackman, Matt Curls, Adam Brainard, Jeffrey McKishen, Scott Satovsky Jr, Sam Buck, Ron Kakar, Chris Peters, Kevin Carpentier, Patrick D. Ashmore, Piya Shedden, Sam Lutfi, Charles George, Christoph Schwanke, Greg
----------
Looking for SciShow elsewhere on the internet?
Facebook: http://www.facebook.com/scishow
Twitter: http://www.twitter.com/scishow
Tumblr: http://scishow.tumblr.com
Instagram: http://instagram.com/thescishow
----------
Sources:
https://www.merriam-webster.com/dictionary/algorithm
https://www.pnas.org/content/108/46/18726
https://link.springer.com/chapter/10.1007/978-3-642-00267-0_9
Fly hashing:
https://www.slaney.org/malcolm/yahoo/Slaney2008-LSHTutorial.pdf
https://science.sciencemag.org/content/358/6364/793
https://science.sciencemag.org/content/suppl/2017/11/09/358.6364.793.DC1
https://medium.com/@jaiyamsharma/efficient-nearest-neighbors-inspired-by-the-fruit-fly-brain-6ef8fed416ee
Object recognition:
https://www.sciencedirect.com/science/article/abs/pii/S1361841517301135 (open copy at https://arxiv.org/pdf/1702.05747.pdf)
https://dev.to/clarifai/what-convolutional-neural-networks-look-at-when-they-see-nudity
http://www.cse.iitm.ac.in/~vplab/courses/CV_DIP/PDF/Feature_Detectors_and_Descriptors.pdf
http://www.cs.cmu.edu/~10701/slides/Perceptron_Reading_Material.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2718241/
https://knowingneurons.com/2014/10/29/hubel-and-wiesel-the-neural-basis-of-visual-perception/
http://www.scholarpedia.org/article/Neocognitron
https://www.frontiersin.org/articles/10.3389/frobt.2015.00036/full
https://www.rctn.org/bruno/public/papers/Fukushima1980.pdf
Anomaly detection:
https://blogs.oracle.com/datascience/introduction-to-anomaly-detection
ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/ieee_tec01.pdf
https://dl.acm.org/doi/10.1145/283699.283742
https://link.springer.com/content/pdf/10.1007/s11047-006-9026-4.pdf
https://www.cs.unm.edu/~immsec/publications/virus.pdf
https://www.sciencedirect.com/science/article/abs/pii/S221421261630240X
https://link.springer.com/content/pdf/10.1007%2F978-3-642-59901-9.pdf
Swarm algorithms and TERMES:
https://www.sciencedirect.com/science/article/pii/B9780124051638000016
https://dash.harvard.edu/bitstream/handle/1/13068244/Petersen_gsas.harvard.inactive_0084L_11836.pdf
https://www.youtube.com/watch?v=t2e4GIZ3W1o
https://science.sciencemag.org/content/343/6172/754
Simulated annealing:
https://pdb101.rcsb.org/learn/guide-to-understanding-pdb-data/methods-for-determining-structure
https://www.annualreviews.org/doi/pdf/10.1146/annurev.pc.42.100191.001213
https://pubs.acs.org/doi/full/10.1021/acs.cgd.9b00517#
https://www.sciencedirect.com/book/9780124167438/nature-inspired-optimization-algorithms
https://www.sciencedirect.com/topics/materials-science/annealing
https://science.sciencemag.org/sites/all/libraries/pdfjs/web/viewer.html?file=/content/sci/220/4598/671.full.pdf
https://www.sciencedirect.com/topics/materials-science/simulated-annealing
https://link.springer.com/article/10.1007/s12559-015-9370-8
https://onlinelibrary.wiley.com/doi/abs/10.1111/itor.12001
Image Sources:
https://commons.wikimedia.org/wiki/File:Hubel%2Bwiesel.jpg
https://www.flickr.com/photos/niaid/29122039942
https://commons.wikimedia.org/wiki/File:Diagram_showing_the_position_of_the_thymus_gland_CRUK_362.svg
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