# numbers Published articles for numbers. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers DevFeed: [MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers]() Original publisher: [Read original article]() Author: Harold Fritts Published: 2026-09-16T15:00:00Z Content type: news Language: en Sources: [StorageReview.com]() Topics: [Benchmark](), [Inference Performance](), [Retrieval Augmented Generation (RAG)](), [agentic-coding](), [GPU](), [Vera Rubin NVL72](), [Nvidia](), [Vera Rubin]() Tags: [agentic-coding](), [ai](), [benchmark](), [enterprise](), [gpt-oss](), [gpu](), [inference](), [llama-cpp](), [numbers](), [nvidia](), [qwen3](), [rag]() ### AI overview MLCommons published MLPerf Inference v6.1 with record participation, two new inference tests, and peer-reviewed results for several newly covered accelerators. The release reports a 5.7x improvement in the best per-accelerator DeepSeek-R1 server result compared with v5.1. ### Source excerpt MLCommons has published MLPerf Inference v6.1, and the round sets a participation record with 30 submitting organizations and 486 datacenter and edge results. Two new tests join the suite: an End-to-End RAG pipeline for the datacenter and an Edge Agentic Inference benchmark for single-user devices, and the results carry the first peer-reviewed numbers for NVIDIA's The post MLPerf Inference v6.1: 5.7x Per-Accelerator Gains, a 512-GPU Run, and Vera Rubin's First Peer-Reviewed Numbers appeared first on StorageReview.com. ## Subnormal floating-point numbers are expensive... on Intel processors DevFeed: [Subnormal floating-point numbers are expensive... on Intel processors]() Original publisher: [Read original article]() Author: Daniel Lemire Published: 2026-09-15T12:54:32Z Content type: article Language: en Sources: [Daniel Lemire]() Topics: [floating-point](), [Benchmark](), [intel](), [C++](), [Cache]() Tags: [benchmark](), [c-plus-plus](), [floating-point](), [intel](), [linux](), [numbers](), [performance](), [processors]() ### AI overview This article benchmarks the performance cost of IEEE subnormal floating-point values across Intel, AMD, Arm, and Apple processors. It reports that Intel multiplications involving subnormals can be about 45 to 50 times slower than normal multiplications, while additions and subtractions remain at full speed. AMD Zen 5 performs much better in the tested workloads. ### Source excerpt We represent floating-point numbers using the IEEE standard. For very small numbers, the standard uses special subnormal numbers. Unfortunately, they have a reputation of making operations slow. Thus video game programmers and machine learning specialists sometimes avoid computing with subnormal numbers for performance. How slow are they? Let me measure. I wrote a small C++ ... Continue reading Subnormal floating-point numbers are expensive... on Intel processors ## How engineering teams can measure AI coding ROI with cost attribution and outcome metrics DevFeed: [How engineering teams can measure AI coding ROI with cost attribution and outcome metrics]() Original publisher: [Read original article]() Author: Kelsey Rosen Published: 2026-09-08T00:00:00Z Content type: article Language: en Sources: [Harness Blog]() Topics: [ai-coding](), [Ground truth / benchmark quality](), [coding](), [Finance]() Tags: [ai](), [ai-coding](), [analysis](), [blog](), [coding](), [cost](), [datadog](), [engineering](), [governance](), [harness](), [incident](), [lifecycle](), [measurement](), [metrics](), [numbers](), [production](), [team](), [tokens](), [tooling](), [workflow]() ### AI overview A Harness panel discussion outlines ways engineering organizations can measure AI coding ROI. The panel recommends attributing costs to specific work, combining throughput metrics with qualitative evidence, and using governance and process changes to interpret results. ### Source excerpt Harness panelists share practical strategies for measuring AI coding ROI, from granular cost attribution and lifecycle metrics to budgeting, governance. | Blog ## double, BigDecimal, or Fixed-Point? DevFeed: [double, BigDecimal, or Fixed-Point?]() Original publisher: [Read original article]() Author: Stefano Fago Published: 2026-06-14T00:00:00Z Content type: article Language: en Sources: [Nicolas Frรคnkel]() Topics: [Java]() Tags: [bigdecimal](), [engineering](), [floating-point](), [java](), [numbers](), [performance](), [pitfalls](), [precision]() ### AI overview A Java-focused article explains how to choose among double, BigDecimal, and fixed-point arithmetic based on required precision, rounding rules, and performance constraints. It covers IEEE 754 binary representation, floating-point equality pitfalls, tolerance-based comparisons, and production concerns such as serialization, testing, and concurrency. ### Source excerpt There is an evergreen debate in the Java world: should you always use BigDecimal for money? The short answer is no. The real answer is: it depends on your computational context: the precision you need, the rounding rules you must follow, and the performance budget you have. The problem is that this conversation is often driven by dogma rather than engineering. ## Only 17% of all 64-bit Integers are products of two 32-bit integers DevFeed: [Only 17% of all 64-bit Integers are products of two 32-bit integers]() Original publisher: [Read original article]() Author: Daniel Lemire Published: 2026-05-22T01:16:35Z Content type: article Language: en Sources: [Daniel Lemire]() Topics: [Programming](), [hash]() Tags: [cryptographic](), [hash](), [numbers](), [precision](), [programming]() ### AI overview The article examines what fraction of 64-bit integers can be represented as the full product of two 32-bit integers. It presents the result that only 17% can be produced this way and relates the question to hash-function design and multiplication behavior. ### Source excerpt In software programming, the product between two integers is often computed to a fixed number of bits with overflow. Consider 8-bit integers. If you multiply 127 by 127, you get back the number 1 as an 8-bit unsigned integer, with an overflow. The actual full product is 16129. To represent 16129, you typically use 16 ... Continue reading Only 17% of all 64-bit Integers are products of two 32-bit integers ## PayPal Business Fees in 2026: Effective Costs for International and Low-Value Transactions DevFeed: [PayPal Business Fees in 2026: Effective Costs for International and Low-Value Transactions]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-03-15T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Transactions](), [Software as a service]() Tags: [2026](), [chargebacks](), [cost](), [cross-border](), [examples](), [fees](), [global-payments](), [numbers](), [paypal](), [pricing](), [review]() ### AI overview This guide examines PayPal business fees in 2026, emphasizing that effective costs depend on payment type, geography, currency conversion, disputes, payout behavior, and average order value. It uses scenario math and compares total costs with Dodo Payments. ### Source excerpt PayPal advertises 2.99% + $0.49--but FX spreads, $20 chargebacks, and cross-border surcharges quietly push your real cost past 8%. See line-by-line examples for 2026. ## \[Math\] Intervals: Apache Maven version numbers DevFeed: [\[Math\] Intervals: Apache Maven version numbers]() Original publisher: [Read original article]() Published: 2025-12-18T23:00:00Z Content type: article Language: en Sources: [Dennis Yurichev]() Topics: [Maven](), [math]() Tags: [apache](), [math](), [numbers]() ### AI overview This article explains how Apache Maven version ranges use mathematical interval notation, including fixed versions, half-open intervals, half-closed intervals, and omitted infinity signs. ### Source excerpt [Math] Intervals: Apache Maven version numbers ## 5 to 18: Why Your Count Might Be Off by One DevFeed: [5 to 18: Why Your Count Might Be Off by One]() Original publisher: [Read original article]() Author: Ruslan Spivak Published: 2025-08-19T15:37:00Z Content type: tutorial Language: en Sources: [Ruslan Spivak]() Topics: [Code](), [coding](), [bug]() Tags: [blog](), [bug](), [code](), [numbers](), [range]() ### AI overview A tutorial explains how to count integers in an inclusive range using b - a + 1. It uses the range from 5 to 18 to show why subtracting the endpoints alone produces an off-by-one error, then connects the mistake to dates, strings, workout plans, floors, and loop boundaries in code. ### Source excerpt Quick question: How many numbers are there from 5 to 18, including both ends? Your first instinct might be to subtract: 18 - 5 = 13 Feels right. But it's wrong. It's a small thing, and kind of basic, but this mistake got me more times than I'd like ... ## Implementing Unsure Calculator in 100 lines of Haskell DevFeed: [Implementing Unsure Calculator in 100 lines of Haskell]() Original publisher: [Read original article]() Published: 2025-04-25T00:00:00Z Content type: tutorial Language: en Sources: [Romes' Musings]() Topics: [Haskell](), [Development](), [math]() Tags: [article](), [expression](), [haskell](), [list](), [monad](), [numbers](), [operations](), [range]() ### AI overview This tutorial implements an Unsure Calculator in Haskell. It introduces a range operator for uncertain values, models calculations with a probability monad and normal distributions, samples results using pseudo-randomness, and builds an embedded calculator expression language. ### Source excerpt Contents 1 Unsure Calculator 1.1 Sampling it up 1.2 Calculator Expressions 1.3 Showing up 1.4 Conclusion 1 Unsure Calculator The recently trendy Unsure Calculator makes reasoning about numbers with some uncertainty just as easy as calculating with specific numbers. The key idea is to add a new "range" operator (written ~) to the vocabulary of a standard calculator. The range x~y denotes that a real value is uncertain, but we are 95% sure that it falls between x and y1. Reading the notation is easy: when you see 10~15, you say: "ten to fifteen". Arithmetic operations and friends (e.g. sin, or log) transparently operate on ranges and literal numbers alike. Calculation results in a plot with a range of values that the input expression can take, and with what frequency. The motivation behind the original article is neat, so I'll just recommend you read it there to learn how and why you'd use such a calculator. Here's a real life example they used: 1400~1700 * 0.55~0.65 - 600~700 - 100~200 - 30 - 20 Now, let's implement it. 1.1 Sampling it up Summon a probability monad from the void2. data Dist a where Return :: a -> Dist a Bind :: Dist b -> (b -> Dist a) -> Dist a Normal :: Double -> Double -> Dist Double instance Monad Dist where (>>=) = Bind instance Applicative Dist where pure = Return; (<*>) = ap instance Functor Dist where fmap = liftM The monad instance is free: pure = Return and (>>=) = Bind. The Normal constructor denotes a normal distribution given the standard deviation and mean. With do-notation we can easily construct a complex tree mixing Returns, Binds, and Normals. For instance: d = do s <- Normal 0 1 return (5 + s) desugars to d = Bind (Normal 0 1) (\s -> Return (5 + s)) Then, embue meaning onto a Dist a by allowing an a to be sampled according to the distribution the Dist represents. We use StdGen from random as a source of uniform pseudo-randomness: sample :: StdGen -> Dist a -> a sample g d = case d of Return x -> x Normal mean std_dev -> n1 * std_dev ## 2024 CVE Data Review DevFeed: [2024 CVE Data Review]() Original publisher: [Read original article]() Author: jgamblin Published: 2025-01-05T00:04:57Z Content type: article Language: en Sources: [Jerry Gamblin]() Topics: [Statistics](), [data](), [Vulnerabilities](), [vulnerability](), [Protocol (disambiguation)](), [Cisco](), [iOS](), [GitHub](), [Kernel](), [WordPress](), [WordPress Plugins]() Tags: [cisco](), [cve](), [cve-data](), [github](), [kernel](), [numbers](), [open-source](), [packages](), [statistics](), [uncategorized](), [vulnerabilities](), [vulnerability](), [wordpress](), [wordpress-plugins]() ### AI overview This review examines 2024 CVE statistics, reporting 40,009 published CVEs, a 38.83% increase from 2023. It covers publication patterns, CVSS severity scores, CPE records, and CVE Numbering Authorities. ### Source excerpt 2024 brought unprecedented growth in CVE data, so I figured it would be appropriate to start the new year by exploring these statistics and highlighting some of the more intriguing data points. CVEs By The Numbers We ended 2024 with 40,009 published CVEs, up over 38% from the 28,818 CVEs published in 2023. CVEs By Month Month ... Read more ## How and when to use btree\_gist DevFeed: [How and when to use btree\_gist]() Original publisher: [Read original article]() Author: George MacKerron Published: 2024-07-08T13:29:31Z Content type: tutorial Language: en Sources: [Blog -- Neon Docs]() Topics: [SQL](), [Databases](), [CSV](), [data](), [DateTime]() Tags: [data](), [extension](), [files](), [format](), [index](), [monitor](), [numbers](), [postgres](), [schema](), [sql](), [time]() ### AI overview This tutorial explains how to use PostgreSQL indexes for queries combining one-dimensional and multidimensional data. It focuses on the btree_gist extension and demonstrates its use with UK crime data containing locations and reporting dates, including loading selected CSV data into PostgreSQL. ### Source excerpt The right indexes make big SQL queries fast. If you've been using Postgres for more than 5 minutes, you're almost certainly familiar with the everyday B-Tree index. This can deal with data that has a one-dimensional ordering: numbers, timestamps, text, and so on. And if you've ha... ## Optimizing Digit Counting for Kotlin Long Values DevFeed: [Optimizing Digit Counting for Kotlin Long Values]() Original publisher: [Read original article]() Author: Romain Guy Published: 2024-05-27T00:00:00Z Content type: article Language: en Sources: [Posts on Romain Guy]() Topics: [Code](), [Optimization](), [Kotlin]() Tags: [android](), [assembly](), [code](), [developer](), [floating-point](), [graphics](), [kotlin](), [numbers](), [operator](), [optimization](), [performance]() ### AI overview This article explores ways to count the decimal digits in positive Kotlin Long values without relying on floating-point log10, which cannot represent every Long value exactly. It compares a straightforward branching approach with a binary-search solution and reports faster execution for the latter on a Pixel 6. ### Source excerpt Jake Wharton recently caused me to go down yet another silly optimization rabbit hole when he nonchalantly linked to a piece of code used to count the number of digits in a Long during a Slack conversation about Kotlin's lack of ternary operator. This of course triggered folks like Madis Pink and me to want to optimize it... Counting digits Link to heading The simplest way to count the number of digits would be to compute log10(n).toInt() + 1, where n is our input number. Unfortunately logarithmic functions like Kotlin's log10 are only defined for floating point numbers. If our input is an Int or a Long, we could first convert to Double and then call log10, but not all Long values can be stored in a Double (any value above 2^53), and we would have to special case 0. We must therefore find a different solution1. ## Extract a Number from a String with JavaScript DevFeed: [Extract a Number from a String with JavaScript]() Original publisher: [Read original article]() Author: David Walsh Published: 2024-01-16T11:48:41Z Content type: tutorial Language: en Sources: [David Walsh]() Topics: [JavaScript](), [Regular expression](), [Web Development](), [HTML]() Tags: [html](), [input](), [javascript](), [javascript-quick-tips](), [numbers](), [quick-tips](), [regular-expressions](), [string]() ### AI overview This tutorial explains how to extract numbers from strings in JavaScript, particularly user input from HTML form fields, using regular expressions. ### Source excerpt User input from HTML form fields is generally provided to JavaScript as a string. We've lived with that fact for decades but sometimes developers need to extract numbers from that string. There are multiple ways to get those numbers but let's rely on regular expressions to extract those numbers! To employ a regular expression to [...] The post Extract a Number from a String with JavaScript appeared first on David Walsh Blog. ## Computing Percentages Easier DevFeed: [Computing Percentages Easier]() Original publisher: [Read original article]() Published: 2023-09-05T21:47:37Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [math](), [Computing]() Tags: [approach](), [arithmetic](), [math](), [mathematics](), [numbers](), [puzzle](), [scaling]() ### AI overview A math tutorial explains mental percentage calculations using the fact that x% of y equals y% of x. It presents several approaches, including choosing the easier percentage, multiplying first and dividing by 100, scaling from 1%, and splitting the denominator. ### Source excerpt Problem: Compute 16% of 25 in your head. Solution: 16% of 25 is equivalent to 25% of 16, which is clearly 4. This is true for all numbers: $x\%$ of $y$ is always equal to $y\%$ of $x$. The first one is $\frac{x}{100} y$ and the second is $\frac{y}{100}x$, and because multiplication is commutative and associative, both are equal to $(x \cdot y) / 100$. You can pick the version that is easiest. ## Operator overloading in Kotlin DevFeed: [Operator overloading in Kotlin]() Original publisher: [Read original article]() Published: 2023-01-23T00:01:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [Kotlin](), [Code](), [class](), [function](), [Compiler](), [Math and Logic]() Tags: [arithmetic](), [class](), [code](), [compiler](), [complex-numbers](), [engineering](), [extension-function](), [function](), [kotlin](), [number](), [numbers](), [operations](), [operator-overloading](), [physics](), [type](), [types](), [workshop-learning-programming]() ### AI overview A tutorial on Kotlin operator overloading. It explains Kotlin's predefined operators, how operator methods are declared for custom classes, and how arithmetic and range operators are handled, using complex numbers as an example. ### Source excerpt How are operators defined for types in Kotlin, and how can we define our own operators. ## Presenting data efficiently in emails DevFeed: [Presenting data efficiently in emails]() Original publisher: [Read original article]() Author: Chao Zhang Published: 2021-01-29T01:25:52Z Content type: tutorial Language: en Sources: [Stories by Chao Zhang on Medium]() Topics: [data](), [Android Gradle Plugin](), [email](), [ci](), [APK](), [dashboards]() Tags: [android](), [android-gradle-plugin](), [apk](), [ci](), [data](), [data-visualization](), [email](), [numbers]() ### AI overview The article presents a simple technique for making email reports more engaging by displaying key metrics with less text and larger numbers. It illustrates the approach with an Android Gradle Plugin upgrade report covering CI build-time reductions and APK size changes, and connects the idea to public COVID-19 dashboards. ### Source excerpt A simple trick to write an email report for your readers Image by Hermann Traub from Pixabay Recently my team wrote an email report to the leadership team on the executive summary of Android Gradle Plugin upgrades. Below is the initial version of the reports in the exec summary section: - We have migrated to Android Gradle Plugin from 4.0 to 4.1. -We have observed a reduction in CI build by 50% at 50th percentile and 32% at 90th percentile. - Our APK size is also reduced by -17% The above looks pretty ordinary. But let's compare it to the following: Less text, larger numbers, much easier for readers to get interested in reading them ๐ŸŽ‰ Testimony: I have received more than 5 "wow"s from readers across the company hierarchy for the bottom version. The inspiration is actually from the COVID-19 dashboard of where I live. I came to realize how often it is used in public versus how rare it is used in company emails. ## Commas in big numbers everywhere: An OpenType adventure DevFeed: [Commas in big numbers everywhere: An OpenType adventure]() Original publisher: [Read original article]() Author: Tristan Hume Published: 2019-10-14T00:00:00Z Content type: article Language: en Sources: [Jane Street]() Topics: [Font](), [data](), [jupyter](), [Terminal](), [browser]() Tags: [browser](), [documentation](), [efficiency](), [feature](), [fonts](), [jupyter](), [jupyter-notebooks](), [numbers](), [terminal]() ### AI overview This article describes Numderline, a font that uses OpenType shaping features to insert commas into numbers and emphasize digit grouping. It explains the basics of font shaping, including glyph substitutions and positioning, and discusses how reverse substitution enables grouping digits from the end of a number. ### Source excerpt My job involves a lot of staring at large numbers, mostly latencies in nanoseconds, and picking out magnitudes like microseconds. I noticed myself constantly counting digits in my text editor, in my terminal, and in Jupyter notebooks in my browser. ## Leave Those Numbers for April 1st DevFeed: [Leave Those Numbers for April 1st]() Original publisher: [Read original article]() Author: Adam Published: 2019-04-02T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Cybersecurity](), [Security Attacks]() Tags: [attacks](), [cyber-attacks](), [marketing](), [numbers](), [phishing](), [sales](), [verify]() ### AI overview This opinion argues that vendors should stop using exaggerated, unsupported cybersecurity statistics in sales and marketing materials. It recommends that buyers challenge unverifiable claims and penalize misleading numbers through purchasing decisions. ### Source excerpt Over-inflated numbers won't scare me into buying your 'solution'. ## Serverless by the numbers: 2018 report DevFeed: [Serverless by the numbers: 2018 report]() Original publisher: [Read original article]() Author: Andrea Passwater Published: 2018-03-09T00:00:00Z Content type: article Language: en Sources: [Serverless Blog]() Topics: [Serverless]() Tags: [aws](), [aws-lambda](), [cloud-computing](), [faas](), [function-as-a-service](), [infrastructure-as-code](), [insights](), [numbers](), [report](), [serverless](), [serverless-architecture](), [serverless-framework]() ### AI overview A 2018 report presents serverless usage statistics covering event sources, service structures, runtimes, and related areas. ### Source excerpt Serverless usage stats: event sources, service structures, runtimes, and more. ## A Concrete Introduction to Probability Using Python DevFeed: [A Concrete Introduction to Probability Using Python]() Original publisher: [Read original article]() Published: 2016-04-27T00:00:00Z Content type: tutorial Language: en Sources: [Peter Norvig]() Topics: [math](), [Python]() Tags: [concepts](), [example](), [numbers](), [python]() ### AI overview A tutorial notebook introduces probability theory through Python 3 implementations. It defines experiments, outcomes, sample spaces, events, and probability, then applies these concepts to a fair-die example and notes a second part on probability paradoxes. ### Source excerpt Update to my probability notebook, adding the Central Limit Theorem, also known as the Strength in Numbers Theorem. ## 3 steps to fix encoding problems in Ruby DevFeed: [3 steps to fix encoding problems in Ruby]() Original publisher: [Read original article]() Author: Justin Weiss Published: 2015-09-16T06:59:11Z Content type: tutorial Language: en Sources: [Justin Weiss]() Topics: [Ruby](), [Exception]() Tags: [array](), [exception](), [numbers](), [ruby]() ### AI overview A Ruby tutorial explains how string encodings relate bytes to characters, why changing an encoding can alter printed text without changing the underlying bytes, and how conversion errors occur. It introduces Ruby methods for converting strings, inspecting bytes, and interpreting bytes under another encoding, then presents a three-step process for fixing encoding bugs. ### Source excerpt You only really think about a string's encoding when it breaks. When you check your exception tracker and see Encoding::InvalidByteSequenceError: "\xFE" on UTF-8 staring you in the face. Or maybe "they're" starts showing up as "theyรขEUR โ„ขre". So, when you have a bad encoding, how do you figure out what broke? And how can you fix it? What is an encoding? If you can imagine what encoding does to a string, these bugs are easier to fix. You can think of a string as an array of bytes, or small numbers: irb(main):001:0> "hello!".bytes => [104, 101, 108, 108, 111, 33] In this encoding, 104 means h, 33 means !, and so on. It gets trickier when you use characters that are less common in English: irb(main):002:0> "hellแน!".bytes => [104, 101, 108, 108, 225, 185, 143, 33] Now it's harder to tell which number represents which character. Instead of one byte, แน is represented by the group of bytes [225, 185, 143]. But there's still a relationship between bytes and characters. And a string's encoding defines that relationship. Take a look at what a single set of bytes looks like when you try different encodings: # Try an ISO-8859-1 string with a special character! irb(main):003:0> str = "hellร”!".encode("ISO-8859-1"); str.encode("UTF-8") => "hellร”!" irb(main):004:0> str.bytes => [104, 101, 108, 108, 212, 33] # What would that string look like interpreted as ISO-8859-5 instead? irb(main):005:0> str.force_encoding("ISO-8859-5"); str.encode("UTF-8") => "hellะด!" irb(main):006:0> str.bytes => [104, 101, 108, 108, 212, 33] The bytes didn't change. But that doesn't look right at all. Changing the encoding changed how the string printed, without changing the bytes. And not all strings can be represented in all encodings: irb(main):006:0> "hiโˆ‘".encode("Windows-1252") Encoding::UndefinedConversionError: U+2211 to WINDOWS-1252 in conversion from UTF-8 to WINDOWS-1252 from (irb):61:in `encode' from (irb):61 from /usr/local/bin/irb:11:in `
' Most encodings are small, and can't handle every pos ## Prime numbers and universe factories DevFeed: [Prime numbers and universe factories]() Original publisher: [Read original article]() Author: andreacorbellini Published: 2015-02-15T16:54:00Z Content type: opinion Language: en Sources: [Andrea Corbellini]() Topics: [ASCII]() Tags: [ascii](), [encoding](), [fun](), [math](), [numbers](), [xkcd]() ### AI overview The article explores how prime numbers can encode ASCII text, inspired by an XKCD comic. The author searches prime numbers for English messages and discusses the possibility of finding longer texts or software encoded this way, while noting uncertainty about some primality results. ### Source excerpt I'm a XKCD fan, and I look it up regularly. There's a comic that I particularly enjoyed: Pi Equals. The comic Pi Equals, from XKCD.com (CC-BY-NC 2.5). Well, it appears that Randall was right in that there's a help message hidden somewhere. And I just found it in a prime number: 245178888024581899558766786108789912235672909204719666025638877624752119760547413887830514281649480308707369249 That number corresponds to the ASCII encoding ... ## Visualizing hex dumps with Unicode emoji DevFeed: [Visualizing hex dumps with Unicode emoji]() Original publisher: [Read original article]() Author: Oona Rรคisรคnen (noreply@blogger.com) Published: 2014-10-29T23:52:00Z Content type: tutorial Language: en Sources: [Oona Rรคisรคnen]() Topics: [Emoji](), [Perl](), [OpenSSH](), [Script](), [ssh](), [Terminal]() Tags: [art](), [hex-value](), [numbers](), [openssh](), [perl](), [script](), [silly](), [ssh](), [terminal]() ### AI overview A Perl script visualizes SSH public key fingerprints and other colon-separated hexadecimal byte sequences by mapping each byte to a selected Unicode emoji. The article explains the byte-to-emoji mapping and notes that the script could be extended to other hex-formatted sources such as xxd. ### Source excerpt Memorizing SSH public key fingerprints can be difficult; they're just long random numbers displayed in base 16. There are some terminal-friendly solutions, like OpenSSH's randomart. But because I use a Unicode terminal, I like to map the individual bytes into characters in the Miscellaneous Symbols and Pictographs block. This Perl script does just that: @emoji = qw( ๐ŸŒ€ ๐ŸŒ‚ ๐ŸŒ… ๐ŸŒˆ ๐ŸŒ™ ๐ŸŒž ๐ŸŒŸ ๐ŸŒ  ๐ŸŒฐ ๐ŸŒฑ ๐ŸŒฒ ๐ŸŒณ ๐ŸŒด ๐ŸŒต ๐ŸŒท ๐ŸŒธ ๐ŸŒน ๐ŸŒบ ๐ŸŒป ๐ŸŒผ ๐ŸŒฝ ๐ŸŒพ ๐ŸŒฟ ๐Ÿ€ ๐Ÿ ๐Ÿ‚ ๐Ÿƒ ๐Ÿ„ ๐Ÿ… ๐Ÿ† ๐Ÿ‡ ๐Ÿˆ ๐Ÿ‰ ๐ŸŠ ๐Ÿ‹ ๐ŸŒ ๐Ÿ ๐ŸŽ ๐Ÿ ๐Ÿ ๐Ÿ‘ ๐Ÿ’ ๐Ÿ“ ๐Ÿ” ๐Ÿ• ๐Ÿ– ๐Ÿ— ๐Ÿ˜ ๐Ÿœ ๐Ÿ ๐Ÿž ๐ŸŸ ๐Ÿ  ๐Ÿก ๐Ÿข ๐Ÿฃ ๐Ÿค ๐Ÿฅ ๐Ÿฆ ๐Ÿง ๐Ÿจ ๐Ÿฉ ๐Ÿช ๐Ÿซ ๐Ÿฌ ๐Ÿญ ๐Ÿฎ ๐Ÿฏ ๐Ÿฐ ๐Ÿฑ ๐Ÿฒ ๐Ÿณ ๐Ÿด ๐Ÿต ๐Ÿถ ๐Ÿท ๐Ÿธ ๐Ÿน ๐Ÿบ ๐Ÿป ๐Ÿผ ๐ŸŽ€ ๐ŸŽ ๐ŸŽ‚ ๐ŸŽƒ ๐ŸŽ„ ๐ŸŽ… ๐ŸŽˆ ๐ŸŽ‰ ๐ŸŽŠ ๐ŸŽ‹ ๐ŸŽŒ ๐ŸŽ ๐ŸŽŽ ๐ŸŽ ๐ŸŽ’ ๐ŸŽ“ ๐ŸŽ  ๐ŸŽก ๐ŸŽข ๐ŸŽฃ ๐ŸŽค ๐ŸŽฅ ๐ŸŽฆ ๐ŸŽง ๐ŸŽจ ๐ŸŽฉ ๐ŸŽช ๐ŸŽซ ๐ŸŽฌ ๐ŸŽญ ๐ŸŽฎ ๐ŸŽฏ ๐ŸŽฐ ๐ŸŽฑ ๐ŸŽฒ ๐ŸŽณ ๐ŸŽด ๐ŸŽต ๐ŸŽท ๐ŸŽธ ๐ŸŽน ๐ŸŽบ ๐ŸŽป ๐ŸŽฝ ๐ŸŽพ ๐ŸŽฟ ๐Ÿ€ ๐Ÿ ๐Ÿ‚ ๐Ÿƒ ๐Ÿ„ ๐Ÿ† ๐Ÿ‡ ๐Ÿˆ ๐Ÿ‰ ๐ŸŠ ๐Ÿ€ ๐Ÿ ๐Ÿ‚ ๐Ÿƒ ๐Ÿ„ ๐Ÿ… ๐Ÿ† ๐Ÿ‡ ๐Ÿˆ ๐Ÿ‰ ๐ŸŠ ๐Ÿ‹ ๐ŸŒ ๐Ÿ ๐ŸŽ ๐Ÿ ๐Ÿ ๐Ÿ‘ ๐Ÿ’ ๐Ÿ“ ๐Ÿ” ๐Ÿ• ๐Ÿ– ๐Ÿ— ๐Ÿ˜ ๐Ÿ™ ๐Ÿš ๐Ÿ› ๐Ÿœ ๐Ÿ ๐Ÿž ๐ŸŸ ๐Ÿ  ๐Ÿก ๐Ÿข ๐Ÿฃ ๐Ÿค ๐Ÿฅ ๐Ÿฆ ๐Ÿง ๐Ÿจ ๐Ÿฉ ๐Ÿช ๐Ÿซ ๐Ÿฌ ๐Ÿญ ๐Ÿฎ ๐Ÿฏ ๐Ÿฐ ๐Ÿฑ ๐Ÿฒ ๐Ÿณ ๐Ÿด ๐Ÿต ๐Ÿถ ๐Ÿท ๐Ÿธ ๐Ÿน ๐Ÿบ ๐Ÿป ๐Ÿผ ๐Ÿฝ ๐Ÿพ ๐Ÿ‘€ ๐Ÿ‘‚ ๐Ÿ‘ƒ ๐Ÿ‘„ ๐Ÿ‘… ๐Ÿ‘† ๐Ÿ‘‡ ๐Ÿ‘ˆ ๐Ÿ‘‰ ๐Ÿ‘Š ๐Ÿ‘‹ ๐Ÿ‘Œ ๐Ÿ‘ ๐Ÿ‘Ž ๐Ÿ‘ ๐Ÿ‘ ๐Ÿ‘‘ ๐Ÿ‘’ ๐Ÿ‘“ ๐Ÿ‘” ๐Ÿ‘• ๐Ÿ‘– ๐Ÿ‘— ๐Ÿ‘˜ ๐Ÿ‘™ ๐Ÿ‘š ๐Ÿ‘› ๐Ÿ‘œ ๐Ÿ‘ ๐Ÿ‘ž ๐Ÿ‘Ÿ ๐Ÿ‘  ๐Ÿ‘ก ๐Ÿ‘ข ๐Ÿ‘ฃ ๐Ÿ‘ค ๐Ÿ‘ฅ ๐Ÿ‘ฆ ๐Ÿ‘ง ๐Ÿ‘จ ๐Ÿ‘ฉ ๐Ÿ‘ช ๐Ÿ‘ฎ ๐Ÿ‘ฏ ๐Ÿ‘บ ๐Ÿ‘ป ๐Ÿ‘ผ ๐Ÿ‘ฝ ๐Ÿ‘พ ๐Ÿ‘ฟ ๐Ÿ’€ ๐Ÿ’ ๐Ÿ’‚ ๐Ÿ’ƒ ๐Ÿ’„ ๐Ÿ’… ); while (<>) { if (/[a-f0-9:]+:[a-f0-9:]+/) { ($b, $m, $a) = ($`, $&, $'); print $b.join(" ", map { $emoji[$_] } map hex, split /:/, $m)." ".$a; } } What's happening here? First we create a 256-element array containing a hand-picked collection of emoji. Naturally, they're all assigned an index from 0x00 to 0xff. Then we'll loop through standard input and look for lines containing colon-separated hex bytes. Each hex value is replaced with an emoji from the array. Here's the output: The script could easily be extended to support output from other hex-formatted sources as well, such as xxd: Some additional methods for visualizing hex dumps and key fingerprints, from the comments section: PGP Strong Set Top 50 Fingerprint Art VizHash GD - a visual hash ## Gustavo's IEEE-754 Brain Teaser DevFeed: [Gustavo's IEEE-754 Brain Teaser]() Original publisher: [Read original article]() Published: 2013-08-05T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [coding](), [Math and Logic]() Tags: [ardan-labs](), [blog](), [coding](), [examples](), [floating-point](), [go](), [go-programming](), [golang](), [numbers](), [programming](), [standard]() ### AI overview The article breaks down a question about determining whether an IEEE-754 binary floating-point representation corresponds to an integer. It explains binary scientific notation and simplifies the discussion by working with a 32-bit number. ### Source excerpt Back in June, Gustavo Niemeyer posted the following question on his Labix.org blog: Assume uf is an unsigned integer with 64 bits that holds the IEEE-754 representation for a binary floating point number of that size. How can you tell if uf represents an integer number? I can't talk for you, but I write business applications. I just don't have the background to quickly knock out an answer for a question like this. Fortunately Gustavo posted the logic for the answer. I thought it would be fun to better understand the question and break down his answer. I am going to work with a 32 bit number just to make everything easier. How does the IEEE-754 standard store a floating point number in a binary format? To start I found these two pages: External resource on steve.hollasch.net: http://steve.hollasch.net/cgindex/coding/ieeefloat.html External resource on class.ece.iastate.edu: http://class.ece.iastate.edu/arun/CprE281_F05/ieee754/ie5.html The IEEE-754 specification represents a floating point number in base 2 scientific notation using a special binary format. If you don't know what I mean by base 2 then look at my post on Understanding Type In Go (External resource on ardanlabs.com: https://www.ardanlabs.com/blog/2013/07/understanding-type-in-go.html). Scientific notation is an efficient way of writing very large or small numbers. It works by using a decimal format with a multiplier. Here are some examples: Base 10 Number Scientific Notation Calculation Coefficient Base Exponent Mantissa 700 7e+2 7 * 102 710 2 0 4,900,000,000 4.9e+9 4.9 * 109 4.9 10 9 .9 5362.63 5.36263e+3 5.36263 * 103 5.36263 10 3 .36263 -0.00345 3.45e-3 3.45 * 10-3 3.45 10 -3 .45 0.085 1.36e-4 1.36 * 2-4 1.36 2 -4 .36 In normal scientific notation form there is always just one digit on the left side of the decimal point. For base 10 numbers that digit must be between 1 through 9 and for base 2 numbers that digit can only be 1. The entire number in scientific notation is called the Coefficient. The Ma [Next page]()