# points Published articles for points. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## T-Mobile rewards points expiry texts are a phishing scam DevFeed: [T-Mobile rewards points expiry texts are a phishing scam]() Original publisher: [Read original article]() Author: Pieter Arntz Published: 2026-09-17T10:44:01Z Content type: news Language: en Sources: [Malwarebytes]() Topics: [account](), [App]() Tags: [customer](), [links](), [messages](), [phishing](), [points](), [reward-points](), [rewards-points](), [scam](), [scams](), [t-mobile](), [threat-intel]() ### AI overview Malwarebytes reports a phishing campaign that sends fake T-Mobile rewards-point expiry messages. The messages use invented balances, urgent expiry dates, and phishing links to pressure recipients into clicking before verifying the claim. ### Source excerpt A large phishing campaign is using fake T-Mobile rewards points and looming expiry dates to pressure recipients into clicking malicious links. ## Loyalty points fraud is funding hacker holidays (Lock and Code S07E18) DevFeed: [Loyalty points fraud is funding hacker holidays (Lock and Code S07E18)]() Original publisher: [Read original article]() Author: Malwarebytes Labs Published: 2026-09-07T18:23:18Z Content type: article Language: en Sources: [Malwarebytes]() Topics: [Cybercrime](), [passwords]() Tags: [account-takeover](), [airline](), [airline-miles](), [credit-card-points](), [cybercrime](), [fraud](), [hotel-rewards](), [loyalty-account](), [loyalty-points](), [loyalty-points-fraud](), [podcast](), [points](), [rewards-account](), [rewards-points]() ### AI overview A Lock and Code podcast episode examines loyalty-points theft, why criminals target points balances, and ways companies and consumers can protect against fraud. ### Source excerpt This week on the Lock and Code podcast, we speak with Kim Sutherland about loyalty points fraud and how everyday people can stay safe. ## Benchmarking vector indexes DevFeed: [Benchmarking vector indexes]() Original publisher: [Read original article]() Author: Evgeniy Patlan Published: 2026-08-27T13:35:32Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [benchmarking](), [Ground truth / benchmark quality](), [Databases](), [ann](), [datasets](), [Sorting]() Tags: [ai-vector](), [ann](), [benchmark](), [benchmarking](), [benchmarks](), [blog](), [blog-post](), [data](), [database-performance](), [database-trends](), [databases](), [datasets](), [embeddings](), [index](), [measurements](), [model](), [open-source](), [percona](), [points](), [report](), [run](), [search](), [sorting](), [vector-search](), [vectorsearch]() ### AI overview This article explains how Percona's vector-bench measures vector indexes by building database engines from pinned versions, running them in identical containers with the same data and hardware, and comparing consistent measurements. It describes embeddings, exact search, approximate nearest neighbour search, and ground truth as the brute-force reference needed to evaluate index accuracy. ### Source excerpt Nearly every database has vector search now, and every one of them has a blog post with a big number in it. Almost none of those numbers can be checked, because the thing that makes them meaningful is usually missing. We built a vector-bench to stop guessing. You name the engines you want, build them ... Continued The post Benchmarking vector indexes appeared first on Percona. ## How mobility gives language models a deeper understanding of place DevFeed: [How mobility gives language models a deeper understanding of place]() Original publisher: [Read original article]() Published: 2026-08-21T10:54:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Language models](), [AI Models](), [data](), [datasets](), [Google]() Tags: [ai](), [ai-models](), [algorithms-theory](), [artificial-intelligence](), [benchmark](), [benchmarks](), [data](), [datasets](), [earth-ai](), [embedding](), [google](), [language-models](), [machine-intelligence](), [mobility](), [model](), [models](), [points](), [research](), [vector]() ### AI overview Google Research introduces Mobility-Embedded POIs (ME-POIs), a framework that combines language-model-based text representations of places with aggregated, anonymized mobility patterns. The resulting embeddings capture both a place's identity and its changing functional activity, improving predictions such as visit intent, price level, opening hours, and busyness. ### Source excerpt Algorithms & Theory ## Connecting User Generated Content to Loyalty Engines DevFeed: [Connecting User Generated Content to Loyalty Engines]() Original publisher: [Read original article]() Author: Govinda Vyas Published: 2026-06-25T15:50:07Z Content type: article Language: en Sources: [Bazaarvoice]() Topics: [API](), [systems](), [payload](), [data](), [User Experience]() Tags: [apis](), [conversations-api](), [email](), [integration](), [loyalty](), [payload](), [performance](), [points](), [ugc](), [user-generated-content-ugc]() ### AI overview This article explains how to connect Bazaarvoice user-generated content submissions with loyalty platforms through APIs. It describes a source-connector-destination architecture and a workflow that validates review events before awarding points, including different rewards for text-only and photo reviews. ### Source excerpt In the modern e-commerce stack, User-Generated Content (UGC) and Loyalty Programs are often treated as separate silos. One captures the voice of the customer (Ratings, Reviews, Q&A); the other manages the economy of retention. For brands and retailers, the challenge isn't just "collecting reviews"--it's building a high-performance bridge between user action and value generation. How [...] ## Game Builder Tutorial 1: Build a 2D Platformer -- Duke's Coffee Run DevFeed: [Game Builder Tutorial 1: Build a 2D Platformer -- Duke's Coffee Run]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-06-25T00:00:00Z Content type: tutorial Language: en Sources: [CodeName One]() Topics: [Tutorial](), [Code](), [Java](), [arcade]() Tags: [building](), [code](), [guide](), [java](), [play](), [points](), [project](), [tutorial]() ### AI overview A code-included tutorial for building a playable 2D platformer with the Codename One Game Builder. It covers importing an animated Duke sprite sheet, designing a level, using generated level data and companion code, and implementing win and lose behavior. ### Source excerpt A complete, code-included walkthrough that builds a playable 2D platformer with the Codename One Game Builder -- importing an animated Duke sprite sheet, designing the level, and the win/lose code. ## State of Geospatial in ClickHouse in March 2026 DevFeed: [State of Geospatial in ClickHouse in March 2026]() Original publisher: [Read original article]() Author: Mark Needham Published: 2026-03-04T00:00:00Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [Geographic Information System]() Tags: [analytics](), [batch](), [clickhouse](), [history](), [points](), [production](), [speed](), [storage](), [tools]() ### AI overview This article surveys ClickHouse's geospatial capabilities as of March 2026, covering its type system, spatial functions, grid-based indexing systems such as H3 and S2, WKT and WKB support, version history, production readiness, and limitations. ### Source excerpt Everything you need to know about ClickHouse as a geospatial analytics engine: its type system, indexing grids, strengths, and limitations. ## Introducing GIST: The next stage in smart sampling DevFeed: [Introducing GIST: The next stage in smart sampling]() Original publisher: [Read original article]() Published: 2026-01-23T17:46:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Algorithms](), [Algorithms & Theory](), [datasets](), [data](), [Machine Learning & Artificial Intelligence](), [Algorithm](), [Google](), [NeurIPS]() Tags: [algorithms](), [algorithms-theory](), [classification](), [computer-vision](), [data](), [data-mining-modeling](), [datasets](), [diversity](), [embedding](), [google](), [language-models](), [large-language-models-llms](), [machine-intelligence](), [machine-learning](), [neurips](), [points](), [research](), [systems](), [training](), [vision]() ### AI overview Google Research introduces GIST, an algorithm for selecting a high-quality subset of data for model training. It balances diversity, which reduces redundancy, with utility, which favors relevant and informative data, and provides a mathematical guarantee about solution quality. ### Source excerpt Algorithms & Theory ## Mesh Gradients in Jetpack Compose DevFeed: [Mesh Gradients in Jetpack Compose]() Original publisher: [Read original article]() Author: sinasamaki Published: 2025-02-07T19:02:29Z Content type: tutorial Language: en Sources: [sinasamaki]() Topics: [Jetpack Compose](), [Compose](), [Android](), [Code]() Tags: [android](), [article](), [code](), [color](), [compose](), [design](), [experiment](), [how-to](), [implement](), [jetpack](), [jetpack-compose](), [mesh](), [performance](), [points](), [range]() ### AI overview A tutorial on using a modifier in Jetpack Compose to create and animate mesh gradients from colored points. It explains point placement, smoothing, axis-specific resolution, and the performance trade-offs of higher resolution. ### Source excerpt Learn how to implement beautiful Mesh Gradients on Android ## Pixtral Large DevFeed: [Pixtral Large]() Original publisher: [Read original article]() Published: 2024-11-18T08:00:00Z Content type: release Language: en Sources: [Mistral AI Blog]() Topics: [AI Chat]() Tags: [ai](), [benchmarks](), [evaluation](), [gemini](), [gpt](), [images](), [leaderboard](), [llms](), [model](), [models](), [multimodal](), [ocr](), [open](), [open-source](), [performance](), [points](), [production](), [reasoning](), [research](), [vision]() ### AI overview Pixtral Large is a 124B open-weights multimodal model built on Mistral Large 2. The article reports benchmark results for image, document, chart, and text understanding, and notes research and commercial licensing options. ### Source excerpt Pixtral Large is deprecated. Discover Mistral AI's latest vision models and capabilities in our updated documentation. ## Text Coordinate Systems DevFeed: [Text Coordinate Systems]() Original publisher: [Read original article]() Author: Thorsten Ball, Nathan Sobo, Antonio Scandurra Published: 2024-06-27T00:00:00Z Content type: tutorial Language: en Sources: [Zed Industries - Blog]() Topics: [systems]() Tags: [display](), [points]() ### AI overview This Zed Decoded article explains the text coordinate systems used in Zed's codebase, including rows and columns, offsets, UTF-16 offsets, display points, and anchors. It discusses how points support navigation and why text-coordinate operations require careful handling. ### Source excerpt In this episode of Zed Decoded, Thorsten talks Nathan and Antonio about the text coordinate systems in Zed's codebase, from rows and columns to offsets to display points to anchors. ## Open Source Hackathon 2024 winners DevFeed: [Open Source Hackathon 2024 winners]() Original publisher: [Read original article]() Author: Tyler Shukert Published: 2024-04-30T07:00:00Z Content type: news Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [For the Love of Code](), [Open Source](), [Artificial Intelligence](), [HTML](), [Tailwind CSS](), [API](), [App](), [migration](), [npm]() Tags: [ai](), [api](), [app](), [components](), [creativity](), [css](), [developers](), [hackathon](), [html](), [images](), [migration](), [npm](), [open-source](), [points](), [speed]() ### AI overview Supabase announces the winners of its 2024 Open Source Hackathon. The winning projects include a tool that converts database diagrams into SQL schemas, an AI-assisted HTML component generator using Supabase and Tailwind CSS, AI-powered virtual wardrobe and interactive storytelling applications, a fast-paced image-based word game, and an app for tracking paused Supabase instances. ### Source excerpt Announcing the winners of the Open Source Hackathon 2024! ## Subpixel GUI DevFeed: [Subpixel GUI]() Original publisher: [Read original article]() Author: Nenad Rakocevic (noreply@blogger.com) Published: 2023-08-09T13:32:00Z Content type: article Language: en Sources: [Red]() Topics: [Red](), [GUI](), [floating-point](), [API](), [test]() Tags: [3d](), [4k](), [components](), [floating-point](), [gui](), [pairs](), [points](), [precision](), [scale](), [subpixel]() ### AI overview The article explains how Red/View addressed a GUI dragging glitch caused by converting integer coordinates to floating-point values on displays using scaling above 100%. It introduces point2D! and point3D! datatypes to represent decimal positions and sizes. ### Source excerpt Maybe you didn't notice, but Red/View, our GUI engine, has subpixel precision from the beginning! Unfortunately, that level of precision was not directly accessible to end users, until now. Actually, it would be more accurate to say that we had subpixel resolution only so far. The guilty part is the pair! datatype being limited to integer components only, while subpixel precison requires decimal numbers. So we have recently introduced new datatypes to cope with that. What urged us to make those changes now was a very peculiar visual glitch caused by that dissonance. That glitch happens during face dragging operations. Here is an example using our View test script: As you can see, on some positions, the face starts shaking while the mouse cursor remains still. This affects any type of face. The shaking is about ±2 pixels. It is caused by the difference in precision between the /offset facet expressed in integer numbers and the backend API, which only deals with floating point numbers. The accumulated error when converting integer->float->integer gives a 2 pixels difference. Such error happens on displays where the scaling factor is different from 100%. With the rise of 2K, 3K and 4K displays, a scaling factor > 100% has become the norm, making this glitch more frequent. You might think that this is not a big issue until you start building custom scrollbars and see your entire scrolled content shaking massively... New point datatypes In order to provide decimal positions and sizes for View faces, extending the existing pair! datatype was considered, though, the pair syntax can hardly scale up for such needs: 2343.122x54239.44 2343.122x54239.44x6309.332 2343.122x54239.44x6309.332x442.3321 2.33487e9x54239.44 2.33487e9x54239.44x9.83242e17 2.33487e9x54239.44x9.83242e17x5223.112 1.#infx1.#infx1.#inf As you can notice there, it quickly becomes difficult to read and identify the individual components. So we opted for adding a new literal form (hence a new datatype) that matc ## Ideas and Solutions for Advent of Code 2021 in Kotlin -- Part 4/4 DevFeed: [Ideas and Solutions for Advent of Code 2021 in Kotlin -- Part 4/4]() Original publisher: [Read original article]() Author: Yev Kanivets Published: 2021-12-26T14:39:41Z Content type: tutorial Language: en Sources: [xorum.io - Medium]() Topics: [Advent of Code](), [Kotlin](), [3D](), [pixel]() Tags: [3d](), [advent-of-code](), [algorithms](), [array](), [beacon](), [competitive-programming](), [data-structures](), [kotlin](), [pixel](), [points](), [scanner](), [solutions]() ### AI overview A Kotlin walkthrough of Advent of Code 2021 tasks 19 and 20. It explains matching rotated point sets in 3D space using beacon intersections, then enhancing an image represented as a 2D pixel array while accounting for infinite padding and changing background values. ### Source excerpt Ideas and Solutions for Advent of Code 2021 in Kotlin -- Part 4/4 The final week of Advent of Code was, obviously, the most challenging one. To be honest I was close to being happy with just a silver star multiple times. But at the end, tenacity made the difference. 50 stars are mine this year 🌟 Ideas and Solutions for tasks 1 to 6 can be found here, for tasks 7 to 12 -- here, for tasks 13 to 18 -- here. Day 19: Beacon Scanner We are provided with several sets of points in 3D space. Those points are rotated differently in each set, so we don't know how X, Y, and Z coordinates are aligned between sets. Our goal is to merge all those sets into a single group by matching points (sub-task one) and find the most significant distance between coordinate origins after they are matched. Here is the complete task. This is an exciting task! I've initially learned about this idea from The Three-Body Problem book, which introduced the concept of locating any star in the Universe by the distances from a few nearest stars -- in our case, "a few" means 12. Think about it as a star fingerprint ;) So to match the sets of points in 3D space, we need: check all combinations of rotations in three dimensions (in our task, the step is 90 degrees, so there are 48 combinations) for the whole set assume that each pair of points from the first set and the second set is an intersection by adjusting all points to that pair check how many adjusted points intersect between the two sets if there are more than 12 intersections, voilá -- the sets are matched The embedded Kotlin's functions like intersect, map, and mapNotNull make the solution, even for such a complex task, elegant. Day 20: Trench Map This image-enhancing task provides us with the initial photo (2D array of black and white pixels), and enhancing guidance (1D array). Enhancing happens in steps, where for each pixel, we found its enhanced value as a result of a combination of itself + all eight adjacent pixels. Here is the complete task. We ## Rate Limiting GraphQL APIs by Calculating Query Complexity DevFeed: [Rate Limiting GraphQL APIs by Calculating Query Complexity]() Original publisher: [Read original article]() Author: Guilherme Vieira Published: 2021-06-22T18:30:02Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [GraphQL](), [Shopify](), [API](), [REST API](), [servers]() Tags: [analysis](), [api](), [apis](), [complexity](), [graphql](), [loops](), [performance](), [points](), [rest](), [servers](), [shopify]() ### AI overview The article explains Shopify's rate-limiting system for the GraphQL Admin API. It contrasts request-based REST API limits with a calculated query cost model that assigns costs according to the data requested and the resulting server load. ### Source excerpt GraphQL opens new possibilities for rate limiting. I'll show you Shopify's rate limiting system for the GraphQL Admin API and how it addresses some limitations of common methods commonly used in REST APIs. ## Implementing PhotoShop font sizes and tracking in CSS, points to pixels conversion DevFeed: [Implementing PhotoShop font sizes and tracking in CSS, points to pixels conversion]() Original publisher: [Read original article]() Author: Stanko Published: 2016-09-08T00:00:00Z Content type: tutorial Language: en Sources: [Stanko Tadić]() Topics: [CSS](), [Sass](), [modern web development]() Tags: [conversion](), [css](), [function](), [mixins](), [photoshop](), [pixels](), [points](), [sass](), [scss](), [tracking]() ### AI overview A tutorial on converting Photoshop font sizes from points to CSS pixels and translating Photoshop tracking into CSS letter spacing using Sass functions and mixins. It explains when to use each construct and provides example Sass and generated CSS. ### Source excerpt We've all been there - trying to get right font sizes from PhotoShop to CSS. Designers usually work with points, which are used in the print, but not common on the web. They also use term tracking a lot, which is actually only a letter spacing with different units. You can recalculate everything by hand and try to keep track of it. But we can use the goodies of SCSS to make that process a bit easier. Point to pixel ratio is 1pt = 1.333333px. We'll create SASS function to do conversion for us. And PhotoShop tracking works relative to the font size. One point of tracking is 1/1000 of the font size. For this one we'll create a mixin. // Converts pt to px @function pt-to-px($size-in-points){ @return #{ round($size-in-points * 1.333333) }px; } // Adds letter spacing to match photoshop tracking @mixin tracking($ps-tracking){ letter-spacing: #{ $ps-tracking / 1000 }em; } // Usage .Component { @include tracking(-5); font-size: pt-to-px(20); line-height: pt-to-px(30); } This will generate following CSS: .Component { letter-spacing: -.005em; font-size: 15px; line-height: 23px; } Note that function and mixin can do pretty much the same job. But it makes more sense to use mixins when including complete styles, and functions to return values. So conversion makes sense to be a function, as we can use it for font size, line height or anything else. Conversion of tracking to letter spacing is including a specific style, so keep it in a mixin. ## The Čech Complex and the Vietoris-Rips Complex DevFeed: [The Čech Complex and the Vietoris-Rips Complex]() Original publisher: [Read original article]() Published: 2015-08-06T09:00:00Z Content type: article Language: en Sources: [Jeremy Kun]() Topics: [data](), [datasets](), [Point cloud](), [Computing]() Tags: [approximation](), [cech-complex](), [complex](), [computational-topology](), [data-mining](), [data-science](), [dataset](), [homology](), [linear-algebra](), [mathematics](), [persistent-homology](), [point](), [points](), [simplicial-complex](), [vietoris-rips-complex]() ### AI overview This article introduces computational topology for analyzing the shape of data. It explains how point clouds can be converted into simplicial complexes so homology and persistent homology can identify qualitative features such as connected components and holes, with some resistance to noise. ### Source excerpt It's about time we got back to computational topology. Previously in this series we endured a lightning tour of the fundamental group and homology, then we saw how to compute the homology of a simplicial complex using linear algebra. What we really want to do is talk about the inherent shape of data. Homology allows us to compute some qualitative features of a given shape, i.e., find and count the number of connected components or a given shape, or the number of "2-dimensional holes" it has. ## Elliptic Curve Cryptography: ECDH and ECDSA DevFeed: [Elliptic Curve Cryptography: ECDH and ECDSA]() Original publisher: [Read original article]() Author: andreacorbellini Published: 2015-05-30T19:23:00Z Content type: tutorial Language: en Sources: [Andrea Corbellini]() Topics: [Cryptography](), [ECDSA](), [math](), [Security, Privacy and Abuse Prevention]() Tags: [algorithms](), [attacks](), [cryptography](), [dh](), [dsa](), [ecc](), [ecdh](), [ecdhe](), [ecdsa](), [hash](), [math](), [parameter](), [points](), [random](), [security](), [smart](), [tls]() ### AI overview This tutorial applies elliptic-curve mathematics over finite fields to cryptography, introducing domain parameters and explaining how random seeds can generate curve parameters or base points. It also discusses weak curves and Smart's attack on the discrete logarithm problem. ### Source excerpt This post is the third in the series ECC: a gentle introduction. In the previous posts, we have seen what an elliptic curve is and we have defined a group law in order to do some math with the points of elliptic curves. Then we have restricted elliptic curves to finite fields of integers modulo a prime. With this restriction, we have seen that ... ## Geo Proximity Search: The Haversine Equation DevFeed: [Geo Proximity Search: The Haversine Equation]() Original publisher: [Read original article]() Author: Federico Published: 2014-12-08T11:48:00Z Content type: tutorial Language: en Sources: [Federico Cargnelutti]() Topics: [SQL](), [PHP](), [Python]() Tags: [databases](), [implementation](), [map](), [navigation](), [open-source](), [php](), [plotting](), [points](), [programming](), [python](), [sql](), [web-development]() ### AI overview This tutorial explains how to perform geo-proximity searches by plotting a radius around a map point using latitude and longitude. It introduces the Haversine equation for calculating great-circle distances and provides implementations in SQL, Python, and PHP. ### Source excerpt I'm working on a project that requires Geo proximity search. Basically, what I'm doing is plotting a radius around a point on a map, which is defined by the distance between two points on the map given their latitudes and longitudes. To achieve this I'm using the Haversine formula (spherical trigonometry). This equation is important [...] ## Elliptic Curves as Algebraic Structures DevFeed: [Elliptic Curves as Algebraic Structures]() Original publisher: [Read original article]() Published: 2014-02-16T10:00:39Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Mathematics](), [structure](), [Cryptography]() Tags: [algorithm](), [cryptography](), [elliptic-curves](), [mathematics](), [points](), [structure]() ### AI overview This mathematical tutorial explains elliptic curves as algebraic structures. It develops the geometric algorithm for adding points by drawing a line through two points, finding the third intersection with the curve, and reflecting that point across the x-axis. ### Source excerpt Last time we looked at the elementary formulation of an elliptic curve as the solutions to the equation $$y^2 = x^3 + ax + b$$ where $ a,b$ are such that the discriminant is nonzero: $$-16(4a^3 + 27b^2) \neq 0$$ We have yet to explain why we want our equation in this form, and we will get to that, but first we want to take our idea of intersecting lines as far as possible. ## Letter Frequencies for Scrabble DevFeed: [Letter Frequencies for Scrabble]() Original publisher: [Read original article]() Published: 2013-01-27T00:00:00Z Content type: article Language: en Sources: [Peter Norvig]() Topics: [data](), [Google](), [datasets]() Tags: [analysis](), [change](), [data](), [game](), [google](), [points](), [scrabble](), [table](), [values]() ### AI overview An analysis of English letter frequencies across historical periods and their relationship to Scrabble point values, using Google Books Ngram data. ### Source excerpt An analysis of frequency counts for letters in English, with applications to the game of Scrabble. Also presents a distillation of the Google Books Ngram data, broken out by time periods. ## Smoother Signatures DevFeed: [Smoother Signatures]() Original publisher: [Read original article]() Author: Square Engineering Published: 2012-07-20T16:01:00Z Content type: article Language: en Sources: [Square Corner Blog RSS Feed]() Topics: [Algorithms](), [Android]() Tags: [algorithm](), [algorithms](), [android](), [caching](), [engineering](), [image](), [linear](), [points](), [touchscreen]() ### AI overview Square's Android signature rendering was improved with a better spline interpolation algorithm, variable stroke-width rendering, and bitmap caching. The article explains replacing straight-line interpolation with cubic Bezier curves to produce smoother signatures from sampled touchscreen points. ### Source excerpt Capturing even more beautiful signatures on Android.