# exploration Published articles for exploration. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Museas & Astronoma On Apple Vision Pro Support Curiosity & Discovery DevFeed: [Museas & Astronoma On Apple Vision Pro Support Curiosity & Discovery]() Original publisher: [Read original article]() Author: Laura Mingail Published: 2026-09-07T23:28:57Z Content type: article Language: en Sources: [UploadVR]() Topics: [3D](), [App]() Tags: [3d](), [apple](), [apps](), [art](), [design](), [discovery](), [education](), [exploration](), [interview](), [learning](), [science](), [technologies](), [vision]() ### AI overview An interview with Miguel Garcia Gonzalez examines how the Apple Vision Pro apps Museas and Astronoma use immersive design, real-world source material, and selective 3D presentation to encourage curiosity and exploration of art and science. ### Source excerpt What makes exploring art and science in spatial apps so compelling? We look at Apple Vision Pro apps Museas and Astronoma to learn how to design for curiosity and discovery. ## Помочь пользователю открыть новое: как мы боролись с замкнутым кругом рекомендаций в Яндекс Лавке DevFeed: [Помочь пользователю открыть новое: как мы боролись с замкнутым кругом рекомендаций в Яндекс Лавке]() Original publisher: [Read original article]() Author: ramilboiarchenkov (Яндекс) Published: 2026-07-07T07:02:47Z Content type: tutorial Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [Machine learning]() Tags: [discovery](), [exploration](), [machine-learning](), [ml](), [tag-4004cf5948d3](), [tag-b0a411324cb6](), [tag-b2cbb9058e3c]() ### AI overview This article explains how the Yandex Lavka team addressed the feedback loop in recommendation systems, which can overemphasize familiar products and limit discovery. It describes personalized exploration of unfamiliar products and discusses calibrating the probability and aggressiveness of that exploration for each user. ### Source excerpt Хорошая рекомендательная система быстро учится угадывать, что вы положите в корзину. И чем точнее она угадывает, тем реже показывает что-то незнакомое: ведь выгоднее предлагать проверенное. Со временем система замыкается на привычках человека и перестаёт показывать ему хоть что-то за их пределами. Беда в том, что интересы меняются, а система просто так этого не замечает. Изменить ситуацию, как правило, удаётся лишь ценой краткосрочных потерь: стоит добавить в выдачу незнакомые товары, и объём ближайших покупок неизбежно начинает снижаться. Меня зовут Рамиль Боярченков, я занимаюсь машинным обучением в команде Яндекс Лавки. Расскажу, как мы собрали механизм, который подмешивает незнакомые товары персонально -- тем, кто к ним расположен, -- и с какой вероятностью это делать для каждого пользователя. По пути разберу, как мы калибровали "агрессивность" exploration и что получилось в итоге. Читать далее ## A redesigned Explorations UI: better data exploration - Tinybird DevFeed: [A redesigned Explorations UI: better data exploration - Tinybird]() Original publisher: [Read original article]() Author: Julia Vallina, Nuria Mediavilla Published: 2025-09-19T12:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [ui](), [Artificial Intelligence](), [SQL]() Tags: [ai](), [data](), [exploration](), [sql](), [tinybird-news](), [ui]() ### AI overview Tinybird announces a redesigned Explorations UI with an AI feature that lets users ask for SQL queries in plain English instead of writing them from scratch. ### Source excerpt Stop writing SQL from scratch. Ask in plain English, get the exact query you need. Explorations just got a serious AI upgrade. ## Add an interface to your Neon database via Outerbase DevFeed: [Add an interface to your Neon database via Outerbase]() Original publisher: [Read original article]() Author: Brandon Strittmatter Published: 2024-06-07T15:02:35Z Content type: release Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [SQL](), [Data visualization](), [AI Models](), [Data Management](), [dashboards]() Tags: [announce](), [community](), [dashboards](), [data-management](), [data-studio](), [data-visualization](), [database](), [exploration](), [filter](), [generate](), [guide](), [how-to](), [integration](), [interface](), [language](), [models](), [postgres](), [sorting](), [sql](), [team](), [visualization]() ### AI overview The article announces the public availability of the Outerbase integration for Neon. It lets teams connect Neon Postgres databases to Outerbase Data Studio to collaboratively view, edit, query, manage, and visualize data. Outerbase AI can generate SQL queries, schemas, data, and visualizations from natural-language requests. ### Source excerpt We are beyond excited to announce that the Outerbase integration for Neon is now publicly available. This integration enables you to instantly connect your Neon Postgres database to Outerbase's Data Studio and invite your team to view, edit, query, and visualize your data with yo... ## My First 30 days as a Product Manager at the BBC DevFeed: [My First 30 days as a Product Manager at the BBC]() Original publisher: [Read original article]() Author: Louise Ankers Published: 2022-02-15T22:31:11Z Content type: opinion Language: en Sources: [BBC]() Topics: [Product Management](), [Agile](), [Self-organizing Team](), [User experience (UX)](), [Testing]() Tags: [agile](), [apps](), [bbc](), [data](), [distributed](), [experimentation](), [exploration](), [management](), [new-starter](), [product](), [product-management](), [software-development](), [teamwork](), [testing](), [ux]() ### AI overview A Senior Product Manager describes her first 30 days at the BBC, including the organization's product-management culture, roadmap practices, agile teamwork, distributed work, and support from specialists in UX, data, experimentation, and testing. ### Source excerpt Much like Sir David Attenborough I was not successful on my first application to the BBC , however I was not dissuaded and applied again! Fortunately, I was successful last year and have joined the BBC as Senior Product Manager -- Children's Apps. CBeebies Playtime Island app icon On my first day all the team were very welcoming and friendly, and have explained (and continue to explain!) every BBC acronym very patiently. As a new Product person, it's often intimidating to join a new organisation, not to mention within a new domain. As I have joined during the COVID-19 Omicron wave, everyone is working from home. I am keen to meet the team in person as much as possible -- though we are quite geographically distributed so we will have to plan quite carefully. Product On an organisational level -- the first thing that was clear to me was that the BBC Product Culture follows the principles and values from good Product Management practice such as that advocated by product experts such as Roman Pilcher or Melissa Perri. Having read many books and blogs over the years about say -- having a roadmap that indicates what you are working on now, next and later to offer transparency to stakeholders rather than a delivery plan -- has always been something I've desired to do, and here it is being used in practice! Agile Values Another thing I noticed was the enthusiasm for teamwork and team values -- as one of the principles of the Agile Manifesto that I am passionate about "The best architectures, requirements, and designs emerge from self-organizing teams" -- again in many organisations this may start as an ambition but be waylaid by older management practices and a blindness to what is a creative process. My own reaction to this approach is that I feel there is the right focus on thinking about why we are building, and even if we should be building -- this makes me feel that people think the same way that I do, and that experimentation and exploration in the problem and discovery space ## Computers can be understood DevFeed: [Computers can be understood]() Original publisher: [Read original article]() Author: Nelson Elhage Published: 2020-02-16T20:00:00Z Content type: opinion Language: en Sources: [Nelson Elhage]() Topics: [Software](), [systems](), [coding]() Tags: [abstraction](), [architecture](), [browser](), [compilers](), [complexity](), [concepts](), [cpu](), [exploration](), [hardware](), [javascript](), [kernel](), [learning](), [software](), [systems]() ### AI overview The author describes a mindset centered on the belief that computers and software systems can be understood through determined exploration and learning. Although modern systems are highly complex and layered, each layer can be understood at an appropriate level of abstraction, with deeper investigation possible when needed. ### Source excerpt Introduction This post attempts to describe a mindset I've come to realize I bring to essentially all of my work with software. I attempt to articulate this mindset, some of its implications and strengths, and some of the ways in which it's lead me astray. Software can be understood I approach software with a deep-seated belief that computers and software systems can be understood. This belief is, for me, not some abstruse theoretical assertion, but a deeply felt belief that essentially any question I might care to ask (about computers) has a comprehensible answer which is accessible with determined exploration and learning. ## Metaballs DevFeed: [Metaballs]() Original publisher: [Read original article]() Author: Stanko Published: 2020-02-06T00:00:00Z Content type: article Language: en Sources: [Stanko Tadić]() Topics: [generative art](), [creative coding](), [Graphics](), [coding](), [Algorithm](), [implementation](), [render]() Tags: [algorithm](), [art](), [coding](), [computer-graphics](), [creative-coding](), [exploration](), [generative](), [generative-art](), [graphics](), [implementation](), [projects](), [render]() ### AI overview A project write-up about creating Metaballs, a generative art project that combines spheres into organic shapes, slices them, and renders their outlines as vector files. The author describes exploring metaballs, learning about marching cubes and marching squares, using an existing solution, and building tooling for immediate visual feedback. ### Source excerpt I'm all about generative art these days. Today, I present you Metaballs, my latest creation. It is one of those projects that I visualized in my head and managed to pull it off exactly how I imagined it. Somehow I came up with an idea to generate spheres, smoothly merge them to get organic looking shapes, which then I would slice up and render the outlines.I ordered a pen plotter and that is the reason I'm focused on producing vector files. One of the final images looks like this (click on it to see more): Exploration # Not sure how I started thinking about slicing these blobby objects, but I had a clear vision of what I wanted to achieve. At this point I had no idea they are called metaballs. I asked on our company's #tech-creative-coding channel, if anyone is familiar with making something like this, and my colleagues pointed out the term metaballs and marching cubes algorithm. Definition # Wikipedia defines metaballs as: In computer graphics, metaballs are organic-looking n-dimensional isosurfaces, characterised by their ability to meld together when in close proximity to create single, contiguous objects. Which makes them perfect for what I had in mind - generating organic looking blobs. Implementation # The first try # Initially I wanted to implement it myself, but I didn't really know where to start. I had an idea to hack it by overlapping two spheres and calculate a curve between them. By rotating this curve, I would create a tube and merge everything together. It looks ok-ish for two spheres, but I wasn't completely satisfied. And it was impossible do it for more than two spheres. So I gave up early on this idea. Marching on # So I went back to the marching cubes algorithm. After some research I found a wonderful post, which very thoroughly explains implementation of marching squares.Marching squares are the same algorithm as marching cubes, but in 2D. Now I understood how algorithm works, but I gave up on implementing it myself. I was more interested in bei ## Tinybird Changelog: New User Experience for Data Exploration DevFeed: [Tinybird Changelog: New User Experience for Data Exploration]() Original publisher: [Read original article]() Author: Sergio Álvarez Published: 2019-11-18T00:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [changelog](), [User Experience](), [data]() Tags: [changelog](), [data](), [experience](), [exploration](), [product-updates](), [user-experience]() ### AI overview Tinybird describes a new user experience for data exploration in Tinybird Analytics and discusses studying how to build and organize large applications. ### Source excerpt During the last few weeks we've been studying the best way of building and organizing large applications using Tinybird Analytics, and, in addition to a few ... ## Course announcement: Tampering in Depth! DevFeed: [Course announcement: Tampering in Depth!]() Original publisher: [Read original article]() Author: Adam Published: 2019-09-10T00:00:00Z Content type: release Language: en Sources: [Shostack & Friends Blog]() Topics: [Learning]() Tags: [announcement](), [course](), [exploration]() ### AI overview The author announces that LinkedIn has released the second course in an in-depth exploration of STRIDE, focused on Tampering. The course is presented as a way to organize and remember knowledge about the topic. ### Source excerpt I'm excited to announce that I'm hitting my STRIDE and Linkedin has released the second course in my in-depth exploration of STRIDE: Tampering. ## A Go/C Polyglot DevFeed: [A Go/C Polyglot]() Original publisher: [Read original article]() Author: Nelson Elhage Published: 2019-09-05T23:42:28Z Content type: article Language: en Sources: [Nelson Elhage]() Topics: [Go Language](), [C](), [Parsing]() Tags: [c](), [discovery](), [exploration](), [go](), [language](), [syntax]() ### AI overview The article documents the author's exploration of how to create a source file that is valid in both Go and C. It examines the languages' specifications and focuses on differences in comment syntax as a possible way to construct the polyglot. ### Source excerpt Writing a Go/C polyglot Someone on a Slack I'm on recently raised the question of how you might write a source file that's both valid C and Go, commenting that it wasn't immediately obvious if this was even possible. I got nerdsniped, and succeeded in producing one, which you can find here. I've been asked how I found that construction, so I thought it might be interesting to document the thought / discovery / exploration process that got me there. ## Headless Preview in Craft CMS DevFeed: [Headless Preview in Craft CMS]() Original publisher: [Read original article]() Author: andrew@nystudio107.com (Andrew Welch) Published: 2019-08-13T02:40:00Z Content type: tutorial Language: en Sources: [nystudio107 | Articles on modern web development.]() Topics: [Content Management System](), [Single-page application (SPA)](), [API](), [Front end](), [Database]() Tags: [api](), [cms](), [content](), [craft](), [database](), [draft](), [editor](), [exploration](), [frontend](), [headless](), [here-s](), [implement](), [insights](), [introduced](), [preview](), [react](), [svelte](), [vue](), [works]() ### AI overview This article explains how Craft CMS 3.2 introduced headless content preview for pages rendered by a separate single-page application frontend. It describes the tokenized preview workflow, using auto-saved drafts, database records, tokenized URLs, and API requests to connect the editor with the frontend renderer. ### Source excerpt Craft CMS 3.2 introduced headless content preview. Here's an exploration of how it works, and how you can implement it ## Introducing Exploranda, a set of tools for exploring complex systems. DevFeed: [Introducing Exploranda, a set of tools for exploring complex systems.]() Original publisher: [Read original article]() Author: Raphael Luckom Published: 2018-01-25T18:02:35Z Content type: article Language: en Sources: [Localytics]() Topics: [Complex Systems](), [data](), [Tool](), [Monitoring](), [Graphs]() Tags: [ci](), [complex-systems](), [data](), [exploration](), [graphs](), [monitoring](), [systems](), [tools]() ### AI overview The article introduces Exploranda, a tool for exploring complex systems and supporting the early stages of data-driven decision-making. It describes how open-ended investigation differs from established tools such as monitoring, CI, and CD, especially when problems or causes are not obvious. ### Source excerpt At Localytics, data is central to our mission. One of our core principles is to "lead with data." When I envision that, I often think of an analyst using graphs to make a case for a business decision, or a principal engineer using benchmarks to advocate for a ## Security Research and the Elusive Goal of Scientific Rigor DevFeed: [Security Research and the Elusive Goal of Scientific Rigor]() Original publisher: [Read original article]() Author: Adam Published: 2017-04-25T00:00:00Z Content type: opinion Language: en Sources: [Shostack & Friends Blog]() Topics: [Security](), [Security & Privacy](), [Cybersecurity]() Tags: [exploration](), [insights](), [philosophy](), [research](), [review](), [science](), [security](), [security-research]() ### AI overview The article discusses a forthcoming paper on the meaning and practice of making computer security research more scientific. It reports limited clarity and consensus about a Science of Security, and identifies underused scientific practices and recurring methodological errors in security research. ### Source excerpt [no description provided] ## The Elm Developer Retreat DevFeed: [The Elm Developer Retreat]() Original publisher: [Read original article]() Author: Bruce Eckel Published: 2016-09-12T00:00:00Z Content type: article Language: en Sources: [Bruce Eckel - Computing Thoughts]() Topics: [Elm](), [Programming language](), [ui](), [Programming]() Tags: [building](), [developer](), [elm](), [events](), [exploration](), [language](), [programming-language](), [ui]() ### AI overview This announcement describes a developer retreat scheduled for October 6-9 in Crested Butte, Colorado. Participants will study the Elm programming language and begin building the Open-Spaces Board UI. The event has no fee yet, but attendees must arrange travel and lodging and pay for meals. ### Source excerpt Developer Retreats are the most relaxed and low-ceremony events you can imagine, and I've been very satisfied with the first two. October 6-9 in Crested Butte CO, we are going to tackle the Elm programming language and make a start on building the Open-Spaces Board UI. You can find full details here. Some of us have been studying Elm a bit already but this will be a group exploration so if you haven't had any experience with the language yet you're in good company (although any pre-retreat studying you do will help). ## Project Phoebe - starting the discussion on Mutative Design - Tanya Karsou DevFeed: [Project Phoebe - starting the discussion on Mutative Design - Tanya Karsou]() Original publisher: [Read original article]() Published: 2015-12-08T18:51:34Z Content type: opinion Language: en Sources: [Touchlab | Enterprise Mobile Innovation & Development]() Topics: [Simulation and Design](), [interfaces](), [Users]() Tags: [android](), [design](), [designer](), [discussion](), [exploration](), [interfaces](), [project](), [thoughts]() ### AI overview This article introduces Project Phoebe, an exploration of Liam Spradlin's Mutative Design methodology. The approach aims to create interfaces that adapt to users' differing realities rather than designing for averages, while acknowledging that the concept may not yet be feasible to build. ### Source excerpt Our designer Liam Spradlin has just released Project Phoebe, an exploration of design methodology that seeks to solve the problem, designing for averages. ## Exploring Variations on the Cheryl's Birthday Logic Puzzle DevFeed: [Exploring Variations on the Cheryl's Birthday Logic Puzzle]() Original publisher: [Read original article]() Published: 2015-05-13T00:00:00Z Content type: article Language: en Sources: [Peter Norvig]() Topics: [Math and Logic](), [Code](), [function]() Tags: [code](), [exploration](), [function](), [logic](), [puzzle]() ### AI overview This notebook explores variations of the Cheryl's Birthday logic puzzle by using code to verify generated date lists, randomly construct new puzzles, measure solution outcomes, and introduce a new character named Eve. ### Source excerpt An extended exploration beyond the popular "Cheryl's Birthday" logic puzzle. ## Adversarial Bandits and the Exp3 Algorithm DevFeed: [Adversarial Bandits and the Exp3 Algorithm]() Original publisher: [Read original article]() Published: 2013-11-08T09:00:40Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Machine Learning & Artificial Intelligence](), [Algorithm](), [Learning]() Tags: [algorithm](), [bandit-learning](), [bandits](), [exp3](), [exploitation](), [exploration](), [machine-learning](), [mathematics](), [multiplicative-weights-update-algorithm](), [programming](), [python]() ### AI overview This article introduces adversarial bandit learning and explains how the Exp3 algorithm addresses decisions with uncertain outcomes. It contrasts adversarial payoffs with the simpler stochastic setting and frames success relative to the best single action over repeated trials. ### Source excerpt In the last twenty years there has been a lot of research in a subfield of machine learning called Bandit Learning. The name comes from the problem of being faced with a large sequence of slot machines (once called one-armed bandits) each with a potentially different payout scheme. The problems in this field all focus on one central question: If I have many available actions with uncertain outcomes, how should I act to maximize the quality of my results over many trials? ## Optimism in the Face of Uncertainty: the UCB1 Algorithm DevFeed: [Optimism in the Face of Uncertainty: the UCB1 Algorithm]() Original publisher: [Read original article]() Published: 2013-10-28T11:42:55Z Content type: tutorial Language: en Sources: [Jeremy Kun]() Topics: [Algorithm](), [Mathematics](), [Data Science]() Tags: [algorithm](), [bandit-learning](), [bandits](), [big-o-notation](), [calculus](), [confidence-bounds](), [exploitation](), [exploration](), [machine-learning](), [mathematics](), [programming](), [python](), [random-variables](), [randomized-algorithm](), [science]() ### AI overview This tutorial introduces the multi-armed bandit problem as a model of the exploration-exploitation tradeoff and presents the UCB1 algorithm, which the article describes as performing close to optimally. ### Source excerpt startups The software world is always atwitter with predictions on the next big piece of technology. And a lot of chatter focuses on what venture capitalists express interest in. As an investor, how do you pick a good company to invest in? Do you notice quirky names like "Kaggle" and "Meebo," require deep technical abilities, or value a charismatic sales pitch? When it comes to innovation in software engineering and computer science, and that as a society we should value big pushes forward much more than we do.