An order of magnitude is usually a factor of ten. Thus, four orders of magnitude is a factor of 10,000 or 104. This article presents a list of multiples, sorted by orders of magnitude, for units of information measured in bits and bytes. The byte is a common unit of measurement of information (kilobyte, kibibyte, megabyte, mebibyte, gigabyte, gibibyte, terabyte, tebibyte, etc.). For the purpose of this article, a byte is a group of 8 bits (octet), a nibble is a group of four bits. Historically, neither assumption has always been true. The decimal SI prefixes kilo, mega, giga, tera, etc., are powers of 103 = 1000. The binary prefixes kibi, mebi, gibi, tebi, etc. respectively refer to the corresponding power of 210 = 1024. In casual usage, when 1024 is a close enough approximation of 1000, some of the decimal prefixes have been used in relation to computer memories to mean the binary power, but increasingly from 1998, standards bodies have chosen to limit the resultant confusion by disallowing when software displays a binary quantity with a decimal prefix. Microsoft operating systems still report file and free spaces on a storage device in this casual sense. Note: this page mixes between two kinds of entropies: 1. * Entropy (information theory), such as the amount of information that can be stored in DNA 2. * Entropy (thermodynamics), such as entropy increase of 1 mole of water These two definitions are not entirely equivalent, see Entropy in thermodynamics and information theory. For comparison, the Avogadro constant is 6.02214179(3)×1023 entities per mole, based upon the number of atoms in 12 grams of carbon-12 isotope. In 2012, some hard disks used ~984,573 atoms to store each bit. In January 2012, IBM researchers announced they compressed 1 bit in 12 atoms using antiferromagnetism and a scanning tunneling microscope with iron and copper atoms. This could mean a practical jump from a 1 TB disk to a 100 TB disk. (Wikipedia).
Order of Magnitude is a useful tool for estimation, but what are they? In this video I explain what they are and how you can use them. See www.physicshigh.com for all my videos and other resources. If you like this video, please press the LIKE and SHARE with your peers. And please add a CO
From playlist skills and foundations
Astronomy - Ch. 17: The Nature of Stars (3 of 37) Apparent Magnitude: Example
Visit http://ilectureonline.com for more math and science lectures! In this video I will give examples of the apparent magnitude of the Sun, full moon, Venus, Pluto... Next video can be seen at: http://youtu.be/-REARVFFlgE
From playlist ASTRONOMY 17 STARS AND THE H-R DIAGRAM
Ex: Determine the Difference in Order of Magnitude of Two Quantities
This video explains how to determine the difference in order of magnitude of two quantities. http://mathispower4u.com
From playlist Using the Definition of a Logarithm
Determining values of a variable at a particular percentile in a normal distribution
From playlist Unit 2: Normal Distributions
Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set
From playlist Statistics (Full Length Videos)
Ex: Determine the Difference in Order of Magnitude of Two Quantities (Application)
This video explains how to determine the difference in order of magnitude of two quantities. http://mathispower4u.com
From playlist Using the Definition of a Logarithm
Astronomy - Ch. 17: The Nature of Stars (14 of 37) Apparent Magnitude: Another Look
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain what is apparent magnitude. Next video can be seen at: http://youtu.be/-4FYvEx7jyw
From playlist ASTRONOMY 17 STARS AND THE H-R DIAGRAM
More Standard Deviation and Variance
Further explanations and examples of standard deviation and variance
From playlist Unit 1: Descriptive Statistics
This is the fourth video of a series from the Worldwide Center of Mathematics explaining the basics of vectors. This video deals with vector magnitude. For more math videos, visit our channel or go to www.centerofmath.org
From playlist Basics: Vectors
MIT 6.001 Structure and Interpretation of Computer Programs, Spring 2005 Instructor: Harold Abelson, Gerald Jay Sussman, Julie Sussman View the complete course: https://ocw.mit.edu/6-001S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE18841CABEA24090 Generic Operators Despi
From playlist MIT 6.001 Structure and Interpretation, 1986
Timo Prusti - ESA Presentation recorded during the first Gaia data workshop at ESA's European Space Astronomy Centre (ESAC) 2-4 November 2016. The slides to this presentation are available here: http://www.cosmos.esa.int/documents/915837/915858/20161102_Gaia_TPrusti_web.pdf
From playlist Gaia Mission Playlist
Lecture 4B | MIT 6.001 Structure and Interpretation, 1986
Generic Operators Despite the copyright notice on the screen, this course is now offered under a Creative Commons license: BY-NC-SA. Details at http://ocw.mit.edu/terms Subtitles for this course are provided through the generous assistance of Henry Baker, Hoofar Pourzand, Heather Woo
From playlist MIT 6.001 Structure and Interpretation, 1986
Movement Pruning: Adaptive Sparsity by Fine-Tuning (Paper Explained)
Deep neural networks are large models and pruning has become an important part of ML product pipelines, making models small while keeping their performance high. However, the classic pruning method, Magnitude Pruning, is suboptimal in models that are obtained by transfer learning. This pap
From playlist Papers Explained
SQL SELECT Tutorial - Part 2 |¦| SQL Tutorial |¦| SQL for Beginners
In this tutorial, we continue to explore the SQL SELECT statement. In addition to the standard SELECT, FROM, WHERE, ORDER BY, and LIMIT statements, we will also us the SELECT DISTINCT, LIKE, and BETWEEN statements. The data used in this video is available as a CSV from Socratica on Githu
From playlist Introduction to SQL (Computer Science)
Full title: RandAugment: Practical automated data augmentation with a reduced search space Paper link: https://arxiv.org/abs/1909.13719 ❤️ Support the channel ❤️ https://www.youtube.com/channel/UCkzW5JSFwvKRjXABI-UTAkQ/join Paid Courses I recommend for learning (affiliate links, no extra
From playlist Papers Explained
Parameters in indexed homology - Simon Cho
Workshop on Topology: Identifying Order in Complex Systems Topic: Parameters in indexed homology Speaker: Simon Cho Affiliation: University of Michigan Date: October 9, 2020 For more video please visit http://video.ias.edu
From playlist Mathematics
Mapping Disasters from Space (live public talk)
Original air date: Thursday, Oct. 4 at 7 p.m. PT (10 p.m. ET, 0200 UTC) Space-based radar and GPS are helping us understand and map the damage caused by earthquakes, volcanoes, landslides, hurricanes and floods. Being able to see through clouds to detect changes on the ground was valuable
From playlist Earth
Percentiles, Deciles, Quartiles
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From playlist Unit 1: Descriptive Statistics