TURN

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is the communication for teams who believe there’s more to work than keeping up with group chat apps and chaotic email threads. Twist tool interviewed , Founder of to know more. Kevin William David Amir Salihefendic Twist Hi Amir, So tell us about Twist? is a team communication app based on asynchronous, real threads. It is bet against real-time messaging apps, and for communication that happens on your schedule. So you can choose when to disconnect to do deep, uninterrupted work and when to connect to catch up. Twist Doist’s It’s our bet against chaotic, one-line-at-a-time chat, and for the organized, thoughtful conversations that really move work forward. Most importantly, it’s our bet against team cultures that require people to be constantly connected, and for cultures that prioritize focused, meaningful . (And then sign out at the end of the day, guilt-free.) productivity Tell me more about why you are building this? In 2014, our team , tried Slack. Our team communication flourished like never before, even though many of us had never met in person. We shared GIFs, we shared laughs, and we shared a level of interaction that we’d never experienced before. But, the Slack honeymoon didn’t last long. which is entirely remote Communication wasn’t happening asynchronously — it was happening in real-time, by the minute, all day long. Issues and solutions discussed by teammates in Europe and Asia were already buried six feet under by the time teammates in the Americas even woke up. Team knowledge wasn’t being preserved. Conversations weren’t inclusive or transparent. Communication was disorganized and chaotic. Worse still, keeping up with the group’s chat was beginning to take up more and more of our team’s time and attention. Using real-time group chat was a completely unsustainable, and unfair, way to run a remote-first company. That’s when we realized we needed a tool that supported our team values — of craftsmanship, focus, impact, balance, and clear communication — instead of undermining them. If we were experiencing these frustrations with real-time, all-the-time communication, other teams like ours were probably experiencing them too. What’s unique about what you are building & why do you think companies should use Twist? Here are a few of the design decisions we’ve made along the way to prioritize asynchronous communication over real-time messaging, doing great work over being constantly connected. Thread-first communication Threaded conversations have been at Twist’s core from the beginning. They let anyone on the team create a conversation about a specific topic and ensure that whole conversations — ideas, issues, answers, and decisions — stay organized around that topic. With Twist, there’s no pressure to respond immediately. In fact, many members snooze all notifications for significant portions of the day, and some don’t have notifications turned on at all. This gives them complete control over their time and attention to do deep, thoughtful work. Here’s an example of a thread from our Doist Branding channel where we discussed, gave feedback, and iterated on the new logo for Twist for over a year — all organized in the same thread! Slack recently introduced the concept of threads inside the app as well. The feature is great at what it’s designed for — to hold small side conversations that branch off the main channel — but it doesn’t solve any of the issues we faced. Threaded communication isn’t something you can bolt on as an afterthought. When everything else is built around group chat, real-time communication will always be the default. Truly transparent conversations From our experience with Slack, we knew that merely making conversations public wasn’t enough to guarantee equal access to information across the company. Transparency was one of the main reasons that we built communication around clear topics. Instead of having to skim through single-stream-of-consciousness chat channels, our team can now browse topics to get an overview of the discussions happening in the company. We can delve deeper into just the conversations we’re interested in, even if we’re not directly involved. We often share links to whole threads as reference so people can look and see how a certain decision was made. Our newest team members have been able to quickly get up to speed on what’s going on and see our team culture in action by reading past discussions about our work. We’ve found that Twist has helped us stay connected in more meaningful ways, not just socializing, but actually sharing in the important conversations that determine the core of who we are as a company. Leaving out the online presence indicator A small, but impactful design choice we made in creating Twist was to leave out the online presence indicator. The presence indicator has become something of an expectation for any team communication tool, a holdover from the days when productivity was measured by hours worked rather than work accomplished. But we felt that it would ruin the asynchronous nature of Twist: If you see that a teammate is online, you expect an immediate response. If you see someone is offline, you’re more likely to postpone sending a message because they probably won’t get back to you right away. Without the presence indicator, our team has adapted to adding comments and sending messages whenever they need to. They have no way of knowing if the person is online, so they don’t expect an immediate response. Conversations may happen more slowly, but more real work gets done since we don’t have to deal with constant distractions and context-switching that come with real-time messaging. Time Off (really off) Another example of how we’ve designed Twist to foster mindful communication is the Time Off feature. Twist lets you set up a Time Off status that mutes all notifications from the app, changes your avatar to a “vacation” avatar, and lets your teammates know when you’ll return. This way people can properly recharge and take a well-deserved vacation, and everyone knows not to expect a response until they get back. Ambition and balance are two of the core values of our company. Yes, we want to work hard and build a strong company, but not at the expense of our health and relationships. If we achieve our goals, but we’ve burnt ourselves out in the process, then we’ve failed. It feels amazing to be able to build features like Time Off that reflect those values. Who uses Twist? Extrapolating data from Twist’s beta testers, approximately: 25% work in tech, software, IT 11% in advertising and marketing 7% in finance and accounting 7% in manufacturing 50% remaining are a mix of many diverse industries! How are your customers using Twist? Could you share a few different use cases? is the a manager at an engineering company. They are using it to manage projects related to the implementation design, R&D, bugs, etc. Peter is a management coach who provides corporate and personal management training in the US and Canada. She works with three employees, four volunteers and several external contractors. Everyone works remotely. They use Twist to make plans and have conversations– when their discussions needs to become actionable, they switch over to Todoist. Ellen owns a social events business. They were using Facebook Messenger, but could never properly track all the details about the different events that they were planning. Twist has helped them become more organized, and has helped them try new ideas because they can propose them and then come back later to fine tune them. Mark is the Senior Director of a large veterinary practice with two locations, many employees and four other directors that lead different aspects of the business standpoint. With Twist, his team “can have a continuous conversation, versus jumping in and out of stand alone emails, and checking a bloated inbox full of spam and inquiries. [We] can go into Twist to take on the core of [our] work.” Lain Have there been unique use cases for Twist that you hadn’t thought of or expected? We’re still surfacing use cases but, for example, is a serial entrepreneur who has many small businesses. His invents prototypes of products and then has them produced in China, and sells them online. He has 7 FTE and 20 contractors working on their core business in Twist. Eric Were there any early ‘growth hacks’ or tactics that have contributed to your current success? We worked hand-in-hand with an active beta testing community comprised of people who were already familiar with Doist’s products and philosophies (they were using Todoist Business). This helped us refine our app and identify bugs and inconveniences in the UI. Our growth tactics has been largely based on content marketing. We’ve published several posts on about how our team works and we decided to create Twist. One of those posts– – got published on Reddit and “went viral.” It was “liked” over 700 times on Medium, was shared heavily on social media and ended up getting syndicated on Fast Company. Medium why Why we’re betting against real-time team messaging What were some of the biggest challenges while building the product early on and how did you solve them? Our main goal was to ensure that Twist was mindfully designed in order to reflect the ethos of the company. We build products that are based on our philosophies and values and not to make an immediate profit or to hijack people’s attention and free time for a quick buck. We’re taking the more difficult path but we believe it’ll be the best one not only for users but for our bottom line (in the long run). We were very cognizant of making sure Twist WOULD NOT: Create the feeling of being at work while actually accomplishing very little. Make people anxious about missing out. About having to contribute right now. Cause constant distractions. What have been some of the most interesting integrations you’ve added? Are there any that have been particularly impactful for you? – turns conversations in Twist into actionable Todoist tasks and allows you to get updates about tasks and comments in a specific Twist thread. Todoist – links Twist to hundreds of other apps & services ( ) Zapier reference Before we finish, what are the top 5–10 products that you depend on to run the company & how do you use them? : 100% of our team communication Twist : team task management Todoist Business : document creation & management Google Drive & Dropbox Paper **:**issue tracking GitHub : customer support Zendesk : marketing emails SendGrid : design Sketch : design mock ups Marvel Originally published at siftery.com .

Focus on productivity by drowning the noise out from team and group chat at work

RAMAT GAN, Israel, November 20th, 2024/Chainwire/--Playnance proudly announces the official listing of its groundbreaking blockchain, PlayBlock, on DappRadar, the premier tracking platform for decentralized applications (dApps). Just weeks after its launch, PlayBlock has achieved the remarkable milestone of being ranked #8 globally in daily transactions and daily turnover, solidifying its position as one of the most dynamic blockchains in the world. From Polygon Powerhouse to Global Contender PlayBlock’s success reflects a seamless transition from operating on the Polygon blockchain—where it contributed an extraordinary 15% of Polygon’s daily transactions—to establishing itself as an independent Layer-3 blockchain. Now, PlayBlock is driving unparalleled growth: Top-Tier Performance: With its listing on DappRadar, PlayBlock is recognized as a global leader, surpassing hundreds of established blockchains in both activity and volume.
Empowering Innovation: At the forefront of PlayBlock’s ecosystem is its flagship dApp, UpVsDown.com, a cutting-edge prediction market platform revolutionizing user engagement in the Web3 space. “The success of PlayBlock and UpVsDown.com demonstrates the power of user-focused innovation,” said Pini, CEO of Playnance. “Becoming the #8 blockchain globally is just the beginning as we continue to redefine how people trade, predict, and interact in Web3.” UPvsDOWN.com: Leading PlayBlock’s Growth UpVsDown.com is Playnance’s premier prediction market platform, allowing users to place real-time predictions on various assets, including cryptocurrencies, commodities, and forex. This engaging and skill-driven dApp is a key driver of PlayBlock’s rise, offering: Zero-Gas Trading: Cost-free transactions make predicting markets accessible to everyone.
Instant Rewards: Smart contracts ensure seamless payouts directly to user wallets.
Global Accessibility: With a simple, intuitive interface, UpVsDown.com attracts players worldwide, bridging Web2 and Web3 audiences. PlayBlock: Shaping the Future of Blockchain PlayBlock is purpose-built to meet the evolving needs of the Web3 community, featuring: Gas-Free Transactions: Eliminating barriers to entry for gamers, traders, and developers.
High-Speed Scalability: Supporting 40,000 transactions per second, PlayBlock powers real-time applications at scale. - Seamless Integration: EVM compatibility ensures developers can easily transition their dApps to PlayBlock, enhancing its growing ecosystem. What’s Next for Playnance? PlayBlock’s DappRadar listing signals a new era of transparency and growth for the ecosystem. With UpVsDown.com leading the charge, Playnance aims to expand its influence through innovative partnerships, cutting-edge dApps, and a user-centric approach that bridges Web2 and Web3. About Playnance Based in Ramat Gan, Israel, with offices in Dubai, UAE Playnance is a comprehensive Web3 ecosystem designed to empower users with blockchain solutions for trading, gaming, and decentralized finance. Powered by its Layer-3 blockchain, PlayBlock, and anchored by its leading dApp, UpVsDown.com, Playnance is driving the mass adoption of Web3 technologies worldwide. For more information on PlayBlock and the Playnance ecosystem, users can visit playnance's official website, explore UpVsDown.com & track playnance's progress on DappRadar. Contact CEO Pini Peter Playnance pini@playnance.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here RAMAT GAN, Israel, November 20th, 2024/Chainwire/--Playnance proudly announces the official listing of its groundbreaking blockchain, PlayBlock , on DappRadar , the premier tracking platform for decentralized applications (dApps). Just weeks after its launch, PlayBlock has achieved the remarkable milestone of being ranked #8 globally in daily transactions and daily turnover, solidifying its position as one of the most dynamic blockchains in the world. PlayBlock PlayBlock DappRadar DappRadar daily transactions daily transactions From Polygon Powerhouse to Global Contender PlayBlock’s success reflects a seamless transition from operating on the Polygon blockchain—where it contributed an extraordinary 15% of Polygon’s daily transactions —to establishing itself as an independent Layer-3 blockchain. Now, PlayBlock is driving unparalleled growth: 15% of Polygon’s daily transactions 15% of Polygon’s daily transactions PlayBlock PlayBlock Top-Tier Performance: With its listing on DappRadar, PlayBlock is recognized as a global leader, surpassing hundreds of established blockchains in both activity and volume. Empowering Innovation: At the forefront of PlayBlock’s ecosystem is its flagship dApp, UpVsDown.com, a cutting-edge prediction market platform revolutionizing user engagement in the Web3 space. Top-Tier Performance: With its listing on DappRadar , PlayBlock is recognized as a global leader, surpassing hundreds of established blockchains in both activity and volume. DappRadar DappRadar Empowering Innovation: At the forefront of PlayBlock’s ecosystem is its flagship dApp, UpVsDown.com , a cutting-edge prediction market platform revolutionizing user engagement in the Web3 space. UpVsDown.com UpVsDown.com “The success of PlayBlock and UpVsDown.com demonstrates the power of user-focused innovation,” said Pini, CEO of Playnance . “Becoming the #8 blockchain globally is just the beginning as we continue to redefine how people trade, predict, and interact in Web3.” Playnance Playnance UPvsDOWN.com: Leading PlayBlock’s Growth UpVsDown.com is Playnance’s premier prediction market platform, allowing users to place real-time predictions on various assets, including cryptocurrencies, commodities, and forex. This engaging and skill-driven dApp is a key driver of PlayBlock’s rise, offering: UpVsDown.com UpVsDown.com PlayBlock’s PlayBlock’s Zero-Gas Trading: Cost-free transactions make predicting markets accessible to everyone. Instant Rewards: Smart contracts ensure seamless payouts directly to user wallets. Global Accessibility: With a simple, intuitive interface, UpVsDown.com attracts players worldwide, bridging Web2 and Web3 audiences. Zero-Gas Trading: Cost-free transactions make predicting markets accessible to everyone. Instant Rewards: Smart contracts ensure seamless payouts directly to user wallets. Global Accessibility: With a simple, intuitive interface, UpVsDown.com attracts players worldwide, bridging Web2 and Web3 audiences. UpVsDown.com UpVsDown.com PlayBlock: Shaping the Future of Blockchain PlayBlock is purpose-built to meet the evolving needs of the Web3 community, featuring: PlayBlock PlayBlock Gas-Free Transactions: Eliminating barriers to entry for gamers, traders, and developers. High-Speed Scalability: Supporting 40,000 transactions per second, PlayBlock powers real-time applications at scale. Gas-Free Transactions: Eliminating barriers to entry for gamers, traders, and developers. High-Speed Scalability: Supporting 40,000 transactions per second, PlayBlock powers real-time applications at scale. - Seamless Integration: EVM compatibility ensures developers can easily transition their dApps to PlayBlock, enhancing its growing ecosystem. What’s Next for Playnance ? Playnance Playnance PlayBlock’s DappRadar listing signals a new era of transparency and growth for the ecosystem. With UpVsDown.com leading the charge, Playnance aims to expand its influence through innovative partnerships, cutting-edge dApps, and a user-centric approach that bridges Web2 and Web3. DappRadar DappRadar UpVsDown.com UpVsDown.com About Playnance Based in Ramat Gan, Israel, with offices in Dubai, UAE Playnance is a comprehensive Web3 ecosystem designed to empower users with blockchain solutions for trading, gaming, and decentralized finance. Powered by its Layer-3 blockchain, PlayBlock, and anchored by its leading dApp, UpVsDown.com, Playnance is driving the mass adoption of Web3 technologies worldwide. For more information on PlayBlock and the Playnance ecosystem, users can visit playnance's official website , explore UpVsDown.com & track playnance's progress on DappRadar . website website UpVsDown.com UpVsDown.com DappRadar DappRadar Contact CEO Pini Peter Playnance pini@playnance.com This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here This story was distributed as a release by Btcwire under HackerNoon’s Business Blogging Program. Learn more about the program here here here

PlayBlock Rockets To 8 Globally In Blockchain Transactions And Turnover Following DappRadar Listing

PlayBlock Cohetes Uka 8 Uraqpachan Blockchain Transacciones Ukat Facturación Arktasa DappRadar Listing

PlayBlock se dispara al 8º puesto a nivel mundial en transacciones y facturación de blockchain tras su inclusión en DappRadar

PlayBlock רקטות ל-8 ברחבי העולם בעסקאות ומחזור בלוקצ'יין בעקבות רישום DappRadar

PlayBlock se penje na 8 globalno u Blockchain transakcijama i prometu nakon uvrštavanja na DappRadar

PlayBlock、DappRadar上場後、ブロックチェーン取引と売上高で世界第8位に急上昇

PlayBlock Rockets გლობალურად 8-მდე ბლოკჩეინ ტრანზაქციებში და ბრუნვაში DappRadar-ის ჩამონათვალის შემდეგ

PlayBlock нь DappRadar жагсаалтын дагуу блокчэйн гүйлгээ, эргэлтээрээ дэлхий даяар 8-д хүрдэг.

PlayBlock Cohetes 8 kaqman Globalmente Blockchain Transacciones kaqpi chaymanta Turnover kaqpi DappRadar Listado kaqpi qatispa

PlayBlock Roketi Kwa 8 Ulimwenguni Katika Shughuli za Blockchain na Mauzo Kufuatia Orodha ya DappRadar

PlayBlock tăng vọt lên vị trí thứ 8 trên toàn cầu về giao dịch Blockchain và doanh thu sau khi niêm yết trên DappRadar

DappRadar 上市后，PlayBlock 区块链交易量和营业额飙升至全球第八

I-PlayBlock Rockets Iya ku-8 Emhlabeni Wonke Ku-Blockchain Transactions kanye Nenzuzo Elandela Uhlu lwe-DappRadar

Have you ever felt overwhelmed trying to make sense of dense notes or wished you could listen to them like a podcast while on the go? In this article, I’ll share the tool that could help you turn text into engaging audio podcasts; I believe it could help you learn new things faster and more effectively. Why Turning Notes into Podcasts Is a Game-Changer Did you know that over 50% of people prefer podcasts as their primary way of learning? Podcasts are portable, easy to consume, and perfect for multitasking. But creating a podcast used to feel like a daunting task — until now. Whether you’re a student trying to review lecture notes or a professional preparing for a big presentation, converting written material into something engaging takes time and effort. For me, the challenge was turning long, complex notes into something I could review effortlessly. I wanted to take these notes and transform them into a format I could absorb while driving, exercising, or just relaxing. That’s where NotebookLM came in. What Is NotebookLM and How Does It Work? NotebookLM is an AI-powered tool designed to help users simplify, organize, and transform their notes. Think of it as a smart assistant for your learning process. One of its standout features is the ability to convert text into audio — essentially creating podcasts from your notes. Here’s how I used it: 1. Upload your content: I started by uploading my notes, articles, or YouTube video links into NotebookLM. 2. AI Analysis: The AI analyzed the material, breaking it into clear, logical sections. This was great because it identified the key points I needed to focus on. 3. Text-to-Audio Conversion: The tool converted the notes into an audio format. But here’s the cool part: it wasn’t just a robotic reading. The AI added natural pacing, emphasis, and tone, making the audio feel like a professionally narrated podcast. 4. Download and Listen: Within minutes, I had a polished audio file that I could download and listen to anywhere — on my phone, in the car, or even during a walk. You also can get a shareable link that you can open on any device with the internet connection. The process was so intuitive that I barely had to do any editing, which saved me hours of work. Another cool feature is that you can Customize Audio Overview. You can specify the focus and add instructions for your podcast. This means you can focus on a specific aspect of the subject. This is the example of the podcast: https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio Why NotebookLM Is Perfect for Learners and Creators Before NotebookLM, I often felt stuck. My notes would pile up, and the thought of reviewing them felt overwhelming. But now, I can turn my notes into audio, plug in my headphones, and listen to it on the go or before bedtime. This tool has made learning not just easier but enjoyable. I’ve retained more information because I can revisit the audio anytime. This tool isn’t just for people like me who want to review notes on the go. It’s also great for: Students: Simplify your study material into audio for easier revision.
Professionals: Prepare presentations or training sessions while multitasking.
Content Creators: Turn your ideas into podcasts effortlessly, saving time and boosting productivity. NotebookLM bridges the gap between written and spoken content, making it accessible to everyone. Video DEMO: How to Use NotebookLM Podcast https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true The most beautiful part is that NotebookLM is entirely free. So give it a shot and share with me your experience. Cheers! Have you ever felt overwhelmed trying to make sense of dense notes or wished you could listen to them like a podcast while on the go? In this article, I’ll share the tool that could help you turn text into engaging audio podcasts; I believe it could help you learn new things faster and more effectively. Why Turning Notes into Podcasts Is a Game-Changer Did you know that over 50% of people prefer podcasts as their primary way of learning? Podcasts are portable, easy to consume, and perfect for multitasking. But creating a podcast used to feel like a daunting task — until now. 50% of people prefer podcasts Whether you’re a student trying to review lecture notes or a professional preparing for a big presentation, converting written material into something engaging takes time and effort. For me, the challenge was turning long, complex notes into something I could review effortlessly. I wanted to take these notes and transform them into a format I could absorb while driving, exercising, or just relaxing. That’s where NotebookLM came in. What Is NotebookLM and How Does It Work? NotebookLM is an AI-powered tool designed to help users simplify, organize, and transform their notes. Think of it as a smart assistant for your learning process. One of its standout features is the ability to convert text into audio — essentially creating podcasts from your notes. NotebookLM NotebookLM Here’s how I used it: Here’s how I used it: 1. Upload your content : I started by uploading my notes, articles, or YouTube video links into NotebookLM. Upload your content 2. AI Analysis: The AI analyzed the material, breaking it into clear, logical sections. This was great because it identified the key points I needed to focus on. AI Analysis: 3. Text-to-Audio Conversion: The tool converted the notes into an audio format. But here’s the cool part: it wasn’t just a robotic reading. The AI added natural pacing, emphasis, and tone, making the audio feel like a professionally narrated podcast. Text-to-Audio Conversion: 4. Download and Listen : Within minutes, I had a polished audio file that I could download and listen to anywhere — on my phone, in the car, or even during a walk. You also can get a shareable link that you can open on any device with the internet connection. Download and Listen The process was so intuitive that I barely had to do any editing, which saved me hours of work. Another cool feature is that you can Customize Audio Overview. You can specify the focus and add instructions for your podcast. This means you can focus on a specific aspect of the subject. This is the example of the podcast: https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio https://notebooklm.google.com/notebook/1076c05e-4438-41db-b44c-2335d5859c24/audio Why NotebookLM Is Perfect for Learners and Creators Before NotebookLM, I often felt stuck. My notes would pile up, and the thought of reviewing them felt overwhelming. But now, I can turn my notes into audio, plug in my headphones, and listen to it on the go or before bedtime. This tool has made learning not just easier but enjoyable. I’ve retained more information because I can revisit the audio anytime. This tool isn’t just for people like me who want to review notes on the go. It’s also great for: Students: Simplify your study material into audio for easier revision. Professionals: Prepare presentations or training sessions while multitasking. Content Creators: Turn your ideas into podcasts effortlessly, saving time and boosting productivity. Students: Simplify your study material into audio for easier revision. Students: Professionals: Prepare presentations or training sessions while multitasking. Professionals: Content Creators : Turn your ideas into podcasts effortlessly, saving time and boosting productivity. Content Creators NotebookLM bridges the gap between written and spoken content, making it accessible to everyone. Video DEMO: How to Use NotebookLM Podcast https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true https://youtu.be/fPsugPu9lqI?si=CzreDmclFqbwBSVP&embedable=true The most beautiful part is that NotebookLM is entirely free . So give it a shot and share with me your experience. NotebookLM is entirely free Cheers!

I Turned Notes Into A Podcast: How to Use NotebookLM Podcast DEMO

In the world of software development, every developer is familiar with the trusty TODO comment. It's often used as a quick reminder to revisit code, refactor, or complete a task at a later stage. But over time, these TODO comments can pile up, becoming silent accumulations of technical debt — a hidden burden that can impact a project's health and maintainability. If left unchecked, these scattered reminders can weigh down the codebase, making it harder for developers to navigate, debug, and extend. In my own work, I encountered this issue firsthand and eventually decided to address it with a tool that makes technical debt visible and actionable: Todoctor. https://github.com/azat-io/todoctor?embedable=true The Hidden Problem of TODO Comments At first, a TODO comment may seem harmless or even helpful. It's a signal for developers to revisit something — perhaps optimize an algorithm, refactor a tricky section, replace an outdated dependency, or complete a feature that’s still in progress. However, with busy schedules, changing priorities, and tight deadlines, these TODOs are often postponed indefinitely. Instead of being addressed, they become artifacts of things left unresolved. Over time, TODO comments can create several issues: Invisible Technical Debt: An accumulation of TODO comments gives the illusion that the code is well-maintained, while, in reality, it hides incomplete tasks and unresolved issues.
Decreased Code Quality: Left unaddressed, these comments can contribute to bugs, hard-to-maintain code, and unexpected behaviors.
Loss of Context: As time passes, developers may forget the purpose of each TODO, especially when team members come and go. This leads to a growing disconnect between the code and the team’s understanding of it. In larger projects or those with multiple contributors, the problem only grows. Without regular attention, TODOs can be scattered throughout the codebase, making it challenging to manage and track technical debt. The Solution: Making Technical Debt Visible with Todoctor As I grappled with this problem, I realized the need for a tool to bring TODO comments out of hiding and into an actionable space where teams can easily assess and address them. This led to the creation of Todoctor, a CLI utility designed to analyze and track TODO comments in JavaScript and TypeScript codebases. With Todoctor, developers and teams can visualize and manage their technical debt over time, helping them make informed decisions about prioritizing cleanup and refactoring. Here’s how it works: Identify TODO Hotspots: Todoctor scans the codebase to locate every TODO comment, collecting information on each comment's age, author, and content.
Visualize Technical Debt: It then generates a report with a graph that illustrates how the number of TODOs has evolved over time, giving teams a clear picture of their technical debt.
Encourage Accountability: With Todoctor, you can track the age of each TODO, see who created it, and view a sortable list of all pending tasks in the codebase. Through these metrics, Todoctor turns technical debt into a visible, manageable element of the project. This transparency can motivate teams to take action on outstanding tasks, and it helps foster a culture of code ownership and quality. A Glimpse into Todoctor’s Technical Implementation Todoctor was developed with simplicity and usability in mind, allowing it to seamlessly integrate into any development workflow. The tool is written in JavaScript and operates as a CLI utility, which makes it easy to set up and run with a single command. For each TODO comment, Todoctor collects metadata such as: Age of the Comment: How long the TODO has been in the codebase.


Total Number of TODOs: A straightforward count to track debt size.


Average Age of TODOs: A snapshot of how long tasks have been pending.


Top Contributors: A list showing which team members authored the most TODOs, allowing teams to follow up on specific tasks. Using this data, Todoctor generates a comprehensive HTML report that can be added to a codebase or shared with the team. To start using Todoctor, simply install it and run the following command in the root of your project: npx todoctor Within seconds, Todoctor will analyze your codebase and generate a report, giving you a full view of your technical debt and actionable insights. Why Visualizing Technical Debt Matters Technical debt may seem like a small issue until it begins to slow down development and affect code quality. TODO comments, while useful in the short term, can easily become forgotten liabilities that ultimately need to be addressed. By making these reminders visible and measurable, Todoctor empowers teams to reclaim control over their codebase, ensuring it remains maintainable and ready for future growth. Try Todoctor: https://github.com/azat-io/todoctor?embedable=true In the world of software development, every developer is familiar with the trusty TODO comment. It's often used as a quick reminder to revisit code, refactor, or complete a task at a later stage. But over time, these TODO comments can pile up, becoming silent accumulations of technical debt — a hidden burden that can impact a project's health and maintainability. TODO TODO If left unchecked, these scattered reminders can weigh down the codebase, making it harder for developers to navigate, debug, and extend. In my own work, I encountered this issue firsthand and eventually decided to address it with a tool that makes technical debt visible and actionable: Todoctor . Todoctor https://github.com/azat-io/todoctor?embedable=true https://github.com/azat-io/todoctor?embedable=true The Hidden Problem of TODO Comments TODO At first, a TODO comment may seem harmless or even helpful. It's a signal for developers to revisit something — perhaps optimize an algorithm, refactor a tricky section, replace an outdated dependency, or complete a feature that’s still in progress. However, with busy schedules, changing priorities, and tight deadlines, these TODO s are often postponed indefinitely. Instead of being addressed, they become artifacts of things left unresolved. TODO TODO Over time, TODO comments can create several issues: TODO Invisible Technical Debt: An accumulation of TODO comments gives the illusion that the code is well-maintained, while, in reality, it hides incomplete tasks and unresolved issues. Decreased Code Quality: Left unaddressed, these comments can contribute to bugs, hard-to-maintain code, and unexpected behaviors. Loss of Context: As time passes, developers may forget the purpose of each TODO, especially when team members come and go. This leads to a growing disconnect between the code and the team’s understanding of it. Invisible Technical Debt : An accumulation of TODO comments gives the illusion that the code is well-maintained, while, in reality, it hides incomplete tasks and unresolved issues. Invisible Technical Debt TODO Decreased Code Quality : Left unaddressed, these comments can contribute to bugs, hard-to-maintain code, and unexpected behaviors. Decreased Code Quality Loss of Context : As time passes, developers may forget the purpose of each TODO , especially when team members come and go. This leads to a growing disconnect between the code and the team’s understanding of it. Loss of Context TODO In larger projects or those with multiple contributors, the problem only grows. Without regular attention, TODO s can be scattered throughout the codebase, making it challenging to manage and track technical debt. TODO The Solution: Making Technical Debt Visible with Todoctor As I grappled with this problem, I realized the need for a tool to bring TODO comments out of hiding and into an actionable space where teams can easily assess and address them. This led to the creation of Todoctor , a CLI utility designed to analyze and track TODO comments in JavaScript and TypeScript codebases. TODO Todoctor TODO With Todoctor, developers and teams can visualize and manage their technical debt over time, helping them make informed decisions about prioritizing cleanup and refactoring. Here’s how it works: Identify TODO Hotspots: Todoctor scans the codebase to locate every TODO comment, collecting information on each comment's age, author, and content. Visualize Technical Debt: It then generates a report with a graph that illustrates how the number of TODOs has evolved over time, giving teams a clear picture of their technical debt. Encourage Accountability: With Todoctor, you can track the age of each TODO, see who created it, and view a sortable list of all pending tasks in the codebase. Identify TODO Hotspots: Todoctor scans the codebase to locate every TODO comment, collecting information on each comment's age, author, and content. Identify TODO TODO Visualize Technical Debt : It then generates a report with a graph that illustrates how the number of TODO s has evolved over time, giving teams a clear picture of their technical debt. Visualize Technical Debt TODO Encourage Accountability : With Todoctor, you can track the age of each TODO , see who created it, and view a sortable list of all pending tasks in the codebase. Encourage Accountability TODO Through these metrics, Todoctor turns technical debt into a visible, manageable element of the project. This transparency can motivate teams to take action on outstanding tasks, and it helps foster a culture of code ownership and quality. A Glimpse into Todoctor’s Technical Implementation Todoctor was developed with simplicity and usability in mind, allowing it to seamlessly integrate into any development workflow. The tool is written in JavaScript and operates as a CLI utility, which makes it easy to set up and run with a single command. For each TODO comment, Todoctor collects metadata such as: TODO Age of the Comment: How long the TODO has been in the codebase. Total Number of TODOs: A straightforward count to track debt size. Average Age of TODOs: A snapshot of how long tasks have been pending. Top Contributors: A list showing which team members authored the most TODOs, allowing teams to follow up on specific tasks. Age of the Comment: How long the TODO has been in the codebase. Age of the Comment : How long the TODO has been in the codebase. Age of the Comment TODO Total Number of TODOs: A straightforward count to track debt size. Total Number of TODO s: A straightforward count to track debt size. Total Number of TODO Average Age of TODOs: A snapshot of how long tasks have been pending. Average Age of TODO s: A snapshot of how long tasks have been pending. Average Age of TODO Top Contributors: A list showing which team members authored the most TODOs, allowing teams to follow up on specific tasks. Top Contributors : A list showing which team members authored the most TODO s, allowing teams to follow up on specific tasks. Top Contributors TODO Using this data, Todoctor generates a comprehensive HTML report that can be added to a codebase or shared with the team. To start using Todoctor, simply install it and run the following command in the root of your project: npx todoctor npx todoctor Within seconds, Todoctor will analyze your codebase and generate a report, giving you a full view of your technical debt and actionable insights. Why Visualizing Technical Debt Matters Technical debt may seem like a small issue until it begins to slow down development and affect code quality. TODO comments, while useful in the short term, can easily become forgotten liabilities that ultimately need to be addressed. By making these reminders visible and measurable, Todoctor empowers teams to reclaim control over their codebase, ensuring it remains maintainable and ready for future growth. TODO Try Todoctor : Try Todoctor https://github.com/azat-io/todoctor?embedable=true https://github.com/azat-io/todoctor?embedable=true

How Accumulating TODOs Turns Into Technical Debt (and My Open Source Tool to Manage It)

Как натрупването на TODO се превръща в технически дълг (и моят инструмент с отворен код за управлението му)

Cómo la acumulación de tareas pendientes se convierte en deuda técnica (y mi herramienta de código abierto para gestionarla)

Kuinka kertyvät TODOt muuttuvat tekniseksi velaksi (ja avoimen lähdekoodin työkaluni sen hallintaan)

Ki jan akimile TODO yo vin tounen dèt teknik (ak zouti sous louvri mwen an pou jere li)

TODO の蓄積が技術的負債に変わる仕組み (およびそれを管理するためのオープンソース ツール)

របៀបដែលការប្រមូល TODOs ប្រែទៅជាបំណុលបច្ចេកទេស (និងឧបករណ៍ប្រភពបើកចំហរបស់ខ្ញុំដើម្បីគ្រប់គ្រងវា)

Kaip kaupiami TODO virsta technine skola (ir mano atvirojo kodo įrankiu jai valdyti)

Kā TODO uzkrāšana pārvēršas par tehnisko parādu (un mans atvērtā pirmkoda rīks tā pārvaldībai)

څنګه د TODOs راټولول په تخنیکي پور بدلیږي (او زما د خلاصې سرچینې وسیله د دې اداره کولو لپاره)

Jinsi Ukusanyaji wa TODO unabadilika kuwa Deni la Kiufundi (na Zana Yangu Huria ya Kuisimamia)

TODO-lary nädip toplamak tehniki bergä öwrülýär (we ony dolandyrmak üçin açyk çeşme guralym)

Як накопичення TODO перетворюється на технічний борг (і мій інструмент із відкритим вихідним кодом для керування ним)

The One Word That Turns Bad Luck Into Gold

Die Een Woord Wat Ongeluk In Goud Verander

একটি শব্দ যা খারাপ ভাগ্যকে সোনায় পরিণত করে

La palabra que convierte la mala suerte en oro

Zorte txarra urre bihurtzen duen hitz bakarra

Le seul mot qui transforme la malchance en or

המילה האחת שהופכת מזל רע לזהב

एक शब्द जो दुर्भाग्य को सोने में बदल देता है

Yon sèl pawòl ki fè move chans an lò

不運を金に変える一言

Het ene woord dat ongeluk in goud verandert

Izwi Rimwechete Rinoshandura Rombo Rakaipa kuva Goridhe

Kötü Şansı Altına Çeviren Tek Kelime

Small Businesses Are Turning to AI for Content Marketing, New Semrush Report Shows

ትናንሽ ንግዶች ለይዘት ግብይት፣ አዲስ የሴምሩሽ ሪፖርት ትርኢቶች ወደ AI እየተቀየሩ ነው።

Малыя прадпрыемствы звяртаюцца да AI для маркетынгу кантэнту, паказвае новая справаздача Semrush

Mala preduzeća se okreću veštačkoj inteligenciji za marketing sadržaja, pokazuje novi Semrush izveštaj

Malé firmy se obracejí na AI pro obsahový marketing, ukazuje nová zpráva Semrush

Las pequeñas empresas recurren a la IA para el marketing de contenidos, según un nuevo informe de Semrush

Semrush の新しいレポートによると、中小企業はコンテンツ マーケティングに AI を活用し始めている

کوچني سوداګرۍ د مینځپانګې بازارموندنې لپاره AI ته مخه کوي ، د نوي سیمرش راپور ښیې

Bizneset e vogla po i drejtohen AI për marketing të përmbajtjes, tregon raporti i ri i Semrush

Kiçi kärhanalar Mazmun marketingi üçin täze AI-e ýüz tutýarlar, Täze Semrush hasabat görkezişleri

Küçük İşletmeler İçerik Pazarlaması İçin Yapay Zeka'ya Yöneliyor, Yeni Semrush Raporu Gösteriyor

Các doanh nghiệp nhỏ đang chuyển sang AI cho tiếp thị nội dung, báo cáo mới của Semrush cho thấy

Semrush 新报告显示，小型企业正在利用人工智能进行内容营销

Recently came an interesting task, changing custom SVG, to a Webflow project for the animation. I thought it was no big deal, opened a Figma, took the source code of the SVG, threw it in and .... didn't work 😔 Researching the problem, it turned out that the library that animates SVG works directly with rect elements inside the same SVG. Well again no problem I thought :), let's just rename all layers to Rect and we'll be happy. Renamed, I looked at the SVG source code and I don't see rect :( Then, I sat down much more comfortably in my chair and started researching more efficiently. It turned out that for SVG to understand the elements we want to animate as recr we need to draw them.... drum roll - through Frames. Started testing, and everything works. But now there is another problem: How to automate this process? We already have a lot of drawn illustrations, and we don't want to redo them. Well, since we are working in Frames, we have found a way out, need to create the plugin that will wrap all elements in frames. The source code of the Plugin: const selectedNodes = figma.currentPage.selection;

if (selectedNodes.length === 0) {
  figma.notify("Please select at least one layer.");
} else {
  selectedNodes.forEach(node => {
    const frame = figma.createFrame();
    frame.resize(node.width, node.height);
    frame.x = node.x;
    frame.y = node.y;
    frame.appendChild(node);
    node.x = 0;
    node.y = 0;
  });

  figma.notify("All selected layers are wrapped in frames!");
}

figma.closePlugin(); or download the project on GitHub :-) Result: 30 minutes of code and all animations work, work for the future is done. Conclusion: if you can't find interesting tasks, they will find you themselves. Automate everything :) Recently came an interesting task, changing custom SVG, to a Webflow project for the animation. I thought it was no big deal, opened a Figma, took the source code of the SVG, threw it in and .... didn't work 😔 didn't work didn't work Researching the problem, it turned out that the library that animates SVG works directly with rect elements inside the same SVG. Well again no problem I thought :), let's just rename all layers to Rect and we'll be happy. rect Renamed, I looked at the SVG source code and I don't see rect :( rect Then, I sat down much more comfortably in my chair and started researching more efficiently. It turned out that for SVG to understand the elements we want to animate as recr we need to draw them.... drum roll - through Frames. recr Started testing, and everything works. But now there is another problem: How to automate this process? How to automate this process? We already have a lot of drawn illustrations, and we don't want to redo them. Well, since we are working in Frames, we have found a way out, need to create the plugin that will wrap all elements in frames. plugin The source code of the Plugin: const selectedNodes = figma.currentPage.selection;

if (selectedNodes.length === 0) {
  figma.notify("Please select at least one layer.");
} else {
  selectedNodes.forEach(node => {
    const frame = figma.createFrame();
    frame.resize(node.width, node.height);
    frame.x = node.x;
    frame.y = node.y;
    frame.appendChild(node);
    node.x = 0;
    node.y = 0;
  });

  figma.notify("All selected layers are wrapped in frames!");
}

figma.closePlugin(); const selectedNodes = figma.currentPage.selection;

if (selectedNodes.length === 0) {
  figma.notify("Please select at least one layer.");
} else {
  selectedNodes.forEach(node => {
    const frame = figma.createFrame();
    frame.resize(node.width, node.height);
    frame.x = node.x;
    frame.y = node.y;
    frame.appendChild(node);
    node.x = 0;
    node.y = 0;
  });

  figma.notify("All selected layers are wrapped in frames!");
}

figma.closePlugin(); or download the project on GitHub :-) GitHub Result: 30 minutes of code and all animations work, work for the future is done. Conclusion: if you can't find interesting tasks, they will find you themselves. Automate everything :)

Tutorial: How to Turn Figma Files to SVG with Rect Elements

Падручнік: як ператварыць файлы Figma у SVG з элементамі Rect

Урок: Как да превърнете Figma файлове в SVG с Rect елементи

Tutorial: Cómo convertir archivos Figma a SVG con elementos Rect

آموزش: نحوه تبدیل فایل های Figma به SVG با عناصر Rect

Tutorial: Ki jan yo vire fichye Figma nan SVG ak eleman Rect

Tutorial: come trasformare i file Figma in SVG con elementi Rect

מדריך: כיצד להפוך קבצי Figma ל-SVG עם רכיבי Rect

チュートリアル: Figma ファイルを Rect 要素付きの SVG に変換する方法

Упатство: Како да ги претворите Figma-датотеките во SVG со Rect Elements

Samouczek: Jak przekształcić pliki Figma do formatu SVG za pomocą elementów Rect

Tutorial: Si t'i ktheni skedarët Figma në SVG me Elemente Rect

Qo'llanma: Figma fayllarini to'g'ri elementlar bilan SVGga qanday aylantirish mumkin

Michael Saylor Wants To Turn MicroStrategy Into a Trillion-Dollar Bitcoin Bank

মাইকেল স্যালর মাইক্রোস্ট্র্যাটেজিকে ট্রিলিয়ন-ডলার বিটকয়েন ব্যাংকে পরিণত করতে চান

Michael Saylor will MicroStrategy in eine Billionen-Dollar-Bitcoin-Bank verwandeln

Michael Saylor quiere convertir a MicroStrategy en un banco de Bitcoin de un billón de dólares

Michael Saylor veut transformer MicroStrategy en une banque Bitcoin d'un milliard de dollars

माइकल सैलर माइक्रोस्ट्रेटजी को एक ट्रिलियन डॉलर के बिटकॉइन बैंक में बदलना चाहते हैं

マイケル・セイラーはマイクロストラテジーを1兆ドルのビットコイン銀行にしたいと考えている

Michael Saylor, MicroStrategy를 1조 달러 규모의 비트코인 은행으로 만들고 싶어

Michael Saylor quer transformar a MicroStrategy em um banco de Bitcoin de um trilhão de dólares

Майкл Сэйлор хочет превратить MicroStrategy в биткоин-банк стоимостью триллион долларов

Michael Saylor, MicroStrategy'yi Trilyon Dolarlık Bir Bitcoin Bankasına Dönüştürmek İstiyor

Michael Saylor muốn biến MicroStrategy thành một ngân hàng Bitcoin trị giá nghìn tỷ đô la

Michael Saylor 希望将 MicroStrategy 打造成一家价值万亿美元的比特币银行

What do the following scenarios have in common? Lost in a forest or mountains while hiking or camping
Living in a place where precise addresses don’t exist
A lost child who can’t remember their parents’ phone number These situations wouldn’t be as problematic if people could easily memorize long strings of numbers, but that’s rarely the case. Imagine: “We will set up camp at: 41.826460, 43.266523” “Please deliver to: 6.355199, 80.133746” “Don’t forget my number: 07947281237” These examples highlight the challenge: long, complex numbers are hard to memorize. That's why I started thinking about a more general solution for encoding numbers into words — because while I can't predict every use case, I can offer a general approach that works for many scenarios. A Simple Solution: Turning Numbers into Memorable Words Numbers are everywhere—phone numbers, IP addresses, coordinates, and more. Yet, as humans, we’re not naturally good at remembering long strings of digits. What if, instead of abstract numbers, we could convert them into easy-to-remember words? Numbers are the backbone of our digital world, but they are difficult for people to remember. Think of phone numbers, for example. If I asked you to memorize (027) 4193 2856, it would probably be challenging. But if you can remember it as mew·atom·pick, it becomes much easier. Here’s why it makes sense: Words Carry Meaning: Words come with built-in associations and imagery. For instance, words like "sun," "car," or "tree" evoke specific mental images, making them easier to recall than numbers.


Chunking: Our brains naturally chunk information into manageable parts. While numbers can be chunked (e.g., breaking a phone number into sections), it’s much easier to process a few simple words than a long string of digits. Introducing word4num word4num is a small open-source Python library designed to encode numbers into words and decode them back. The core idea is to create a unified mapping between numbers and words, so the same number will always yield the same word combination, regardless of the platform or context. For example, the number 12.1028737 will generate the same words whether used in Google Maps or Apple Maps. Real-World Use Cases Here are a few examples of how word4num can be applied. You can try out the concept using WhatWords (for testing purposes only): 1. Memorable Phone Numbers Long phone numbers can be transformed into short, meaningful word combinations. Imagine converting the UK phone number (0303) 123 7300 into unfold·piety·hot. These words are easier to remember and share in everyday conversations. 2. Geolocation Encoding It's worth mentioning the excellent article about this problem and the GitHub repository A great example of how this can be applied is in geolocation. Similar to what3words, word4num can encode geographic coordinates into memorable word sequences. For instance, 48.85826, 2.29427 might convert to fedora·unsure·silver·lot. This creates a much more user-friendly way to communicate exact locations. Even a smaller 500m x 500m area can be encoded into a shorter word sequence, like thy·strewn·low: 3. Simplifying IP Addresses word4num can even simplify IP addresses. For example, the IP 255.255.255.255 might be converted into hearty·except·bay, making it easier to remember or share—though this may just be for fun in some cases! The Future of word4num: I Need Your Help The reason I’m sharing this here is to start a conversation and gather feedback. I’d love to hear from you if you: Think the idea won’t work and can explain why
Are willing to help support other languages in the library
Have ideas for new use cases or improvements What do the following scenarios have in common? What do the following scenarios have in common? Lost in a forest or mountains while hiking or camping Living in a place where precise addresses don’t exist A lost child who can’t remember their parents’ phone number Lost in a forest or mountains while hiking or camping Living in a place where precise addresses don’t exist A lost child who can’t remember their parents’ phone number These situations wouldn’t be as problematic if people could easily memorize long strings of numbers, but that’s rarely the case. Imagine: “We will set up camp at: 41.826460, 43.266523” “We will set up camp at: 41.826460, 43.266523” “Please deliver to: 6.355199, 80.133746” “Please deliver to: 6.355199, 80.133746” “Don’t forget my number: 07947281237” “Don’t forget my number: 07947281237” These examples highlight the challenge: long, complex numbers are hard to memorize. That's why I started thinking about a more general solution for encoding numbers into words — because while I can't predict every use case, I can offer a general approach that works for many scenarios. A Simple Solution: Turning Numbers into Memorable Words A Simple Solution: Turning Numbers into Memorable Words Numbers are everywhere—phone numbers, IP addresses, coordinates, and more. Yet, as humans, we’re not naturally good at remembering long strings of digits. What if, instead of abstract numbers, we could convert them into easy-to-remember words? Numbers are the backbone of our digital world, but they are difficult for people to remember. Think of phone numbers, for example. If I asked you to memorize (027) 4193 2856 , it would probably be challenging. But if you can remember it as mew·atom·pick , it becomes much easier. (027) 4193 2856 mew·atom·pick Here’s why it makes sense: Here’s why it makes sense: Words Carry Meaning: Words come with built-in associations and imagery. For instance, words like "sun," "car," or "tree" evoke specific mental images, making them easier to recall than numbers. Chunking: Our brains naturally chunk information into manageable parts. While numbers can be chunked (e.g., breaking a phone number into sections), it’s much easier to process a few simple words than a long string of digits. Words Carry Meaning: Words come with built-in associations and imagery. For instance, words like "sun," "car," or "tree" evoke specific mental images, making them easier to recall than numbers. Words Carry Meaning : Words come with built-in associations and imagery. For instance, words like "sun," "car," or "tree" evoke specific mental images, making them easier to recall than numbers. Words Carry Meaning Chunking: Our brains naturally chunk information into manageable parts. While numbers can be chunked (e.g., breaking a phone number into sections), it’s much easier to process a few simple words than a long string of digits. Chunking : Our brains naturally chunk information into manageable parts. While numbers can be chunked (e.g., breaking a phone number into sections), it’s much easier to process a few simple words than a long string of digits. Chunking Introducing word4num Introducing word4num is a small open-source Python library designed to encode numbers into words and decode them back. The core idea is to create a unified mapping between numbers and words, so the same number will always yield the same word combination, regardless of the platform or context. For example, the number 12.1028737 will generate the same words whether used in Google Maps or Apple Maps. word4num word4num unified mapping 12.1028737 Real-World Use Cases Real-World Use Cases Here are a few examples of how word4num can be applied. You can try out the concept using WhatWords (for testing purposes only): word4num WhatWords 1. Memorable Phone Numbers 1. Memorable Phone Numbers Long phone numbers can be transformed into short, meaningful word combinations. Imagine converting the UK phone number (0303) 123 7300 into unfold·piety·hot . These words are easier to remember and share in everyday conversations. (0303) 123 7300 unfold·piety·hot 2. Geolocation Encoding 2. Geolocation Encoding It's worth mentioning the excellent article about this problem and the GitHub repository It's worth mentioning the excellent article about this problem and the GitHub repository article GitHub repository A great example of how this can be applied is in geolocation. Similar to what3words, word4num can encode geographic coordinates into memorable word sequences. For instance, 48.85826, 2.29427 might convert to fedora·unsure·silver·lot . This creates a much more user-friendly way to communicate exact locations. word4num 48.85826, 2.29427 fedora·unsure·silver·lot Even a smaller 500m x 500m area can be encoded into a shorter word sequence, like thy·strewn·low : thy·strewn·low 3. Simplifying IP Addresses 3. Simplifying IP Addresses word4num can even simplify IP addresses. For example, the IP 255.255.255.255 might be converted into hearty·except·bay , making it easier to remember or share—though this may just be for fun in some cases! word4num 255.255.255.255 hearty·except·bay The Future of word4num: I Need Your Help The Future of word4num: I Need Your Help The reason I’m sharing this here is to start a conversation and gather feedback. I’d love to hear from you if you: Think the idea won’t work and can explain why Are willing to help support other languages in the library Have ideas for new use cases or improvements Think the idea won’t work and can explain why Are willing to help support other languages in the library Have ideas for new use cases or improvements

Those Who Are Lost Must Be Found: Turning Numbers in Memorable Words

In this article, I’m going to show you how you can easily transcribe audio and video files on your own computer using Whisper WebGPU — without needing an internet connection. Initial Requirements to Run Whisper Model Locally We are going to build a web application, so you would need: Terminal
Git
Node.js & NPM
Browser: Chrome or Firefox
Windows 10+, Linux, or Mac (note: Safari on MacOS not fully support WebGPU) The basic hardware requirements: Multi-core processor i5 or higher.
16 GB of RAM is preferable for large audio or video files. What is Whisper from OpenAI Whisper is an advanced speech recognition system developed by OpenAI. It’s designed to transcribe spoken language into written text and can also translate different languages. Whisper is known for its accuracy and ability to understand a variety of accents, languages, and even background noise, making it one of the most reliable tools for converting audio to text. One of the best things about Whisper is that it’s open-source, meaning anyone can access it and use it for free. It can be run on cloud servers or even on your local computer, depending on your needs. Official website: https://openai.com/index/whisper/ Hugging Face’s Transformers.js and ONNX Runtime Web We are going to use Whisper WebGPU https://github.com/xenova/whisper-web/tree/experimental-webgpu project. This project utilizes OpenAI’s Whisper model and runs entirely on your device using WebGPU. It also leverages Hugging Face’s Transformers.js and ONNX Runtime Web, allowing all computations to be performed locally on your device without the need for server-side processing. This means that once the model is loaded, you won’t need an internet connection. Key Features of Whisper WebGPU: Real-Time In-Browser Processing: The technology allows for real-time speech recognition within the browser, enhancing user privacy by eliminating the need to send data to external servers.
Multilingual Support: It supports transcription and translation in 100 languages, making it a versatile tool for global applications.
Local Computation: By leveraging WebGPU technology, the model runs entirely on the user’s device, which not only enhances privacy but also allows for offline functionality once the model is initially loaded.
Model Characteristics: The core model used is Whisper-base, which is optimized for web inference with a size of approximately 200 MB. This makes it lightweight yet powerful enough for real-time applications. How to Run Whisper Model Locally (Ubuntu, Linux) I will show you how to run it on Ubuntu (Linux). However, if you use Windows or Mac, you can follow the same steps inside, but you have to use the terminal. Step 1. Istall GIT, Node.JS, and NPM If you are using Ubuntu, Git should be already there. However, if it’s not, use this command: sudo apt update
sudo apt install git Install Node.js: sudo apt install nodejs Install NPM: sudo apt install npm Step 2. Turn on WebGPU in the Browser Ensure your browser is configured to support WebGPU. Inside the address bar in Chrome Browser write chrome://flags, then find “Unsafe WebGPU Support” enable it, and relaunch the browser. This is still an experimental feature in some browsers, so you may need to enable it in browser settings. You can check the WebGPU status by opening chrome://gpu/ in your browser. In some cases on Ubuntu, even after relaunching, WebGPU could be disabled. In this case, try to open the browser with the following command: /opt/google/chrome/chrome --enable-unsafe-webgpu Step 3. Clone Repository and Install Dependencies Clone the Whisper WebGPU project by following the command: git clone https://github.com/xenova/whisper-web.git Once the cloning process is finished, go inside the folder whisper-web: cd whisper-web Then run the following command: npm install After that run: npm run dev To start a web server. The URL of your web application will be available in the terminal window. E.g. http://localhost:5174/ Step 4. Run the Application Go to your browser and open the URL from the terminal to see your application. This web application supports various audio and video formats and even recording from your microphone. To start the transcription process, simply provide the URL to the audio or upload the video file from your local computer. Video Tutorial https://youtu.be/YQWNuRTCcUk?si=G35I7B_gb6GYaT9m&embedable=true Watch on YouTube: Audio and Video to text converter. Conclusion Whisper WebGPU represents a significant step forward in speech recognition technology by bringing powerful, AI-driven transcription and translation capabilities directly to your browser. By utilizing OpenAI’s Whisper model and advanced tools like WebGPU, Transformers.js, and ONNX Runtime Web, this project makes real-time, offline transcription accessible to everyone while also prioritizing privacy and convenience. If you like this tutorial, please follow me on YouTube, or join my Telegram. Thanks! :) In this article, I’m going to show you how you can easily transcribe audio and video files on your own computer using Whisper WebGPU — without needing an internet connection. Initial Requirements to Run Whisper Model Locally We are going to build a web application, so you would need: Terminal Git Node.js & NPM Browser: Chrome or Firefox Windows 10+, Linux, or Mac (note: Safari on MacOS not fully support WebGPU) Terminal Git Node.js & NPM Browser: Chrome or Firefox Windows 10+, Linux, or Mac (note: Safari on MacOS not fully support WebGPU) The basic hardware requirements: Multi-core processor i5 or higher. 16 GB of RAM is preferable for large audio or video files. Multi-core processor i5 or higher. 16 GB of RAM is preferable for large audio or video files. What is Whisper from OpenAI Whisper is an advanced speech recognition system developed by OpenAI. It’s designed to transcribe spoken language into written text and can also translate different languages. Whisper is known for its accuracy and ability to understand a variety of accents, languages, and even background noise, making it one of the most reliable tools for converting audio to text. One of the best things about Whisper is that it’s open-source, meaning anyone can access it and use it for free. It can be run on cloud servers or even on your local computer, depending on your needs. Official website: https://openai.com/index/whisper/ Official website: https://openai.com/index/whisper/ https://openai.com/index/whisper/ Hugging Face’s Transformers.js and ONNX Runtime Web We are going to use Whisper WebGPU https://github.com/xenova/whisper-web/tree/experimental-webgpu project. https://github.com/xenova/whisper-web/tree/experimental-webgpu https://github.com/xenova/whisper-web/tree/experimental-webgpu This project utilizes OpenAI’s Whisper model and runs entirely on your device using WebGPU. It also leverages Hugging Face’s Transformers.js and ONNX Runtime Web, allowing all computations to be performed locally on your device without the need for server-side processing. This means that once the model is loaded, you won’t need an internet connection. Key Features of Whisper WebGPU: Key Features of Whisper WebGPU: Real-Time In-Browser Processing: The technology allows for real-time speech recognition within the browser, enhancing user privacy by eliminating the need to send data to external servers. Multilingual Support: It supports transcription and translation in 100 languages, making it a versatile tool for global applications. Local Computation: By leveraging WebGPU technology, the model runs entirely on the user’s device, which not only enhances privacy but also allows for offline functionality once the model is initially loaded. Model Characteristics: The core model used is Whisper-base, which is optimized for web inference with a size of approximately 200 MB. This makes it lightweight yet powerful enough for real-time applications. Real-Time In-Browser Processing : The technology allows for real-time speech recognition within the browser, enhancing user privacy by eliminating the need to send data to external servers. Real-Time In-Browser Processing Multilingual Support : It supports transcription and translation in 100 languages, making it a versatile tool for global applications. Multilingual Support Local Computation : By leveraging WebGPU technology, the model runs entirely on the user’s device, which not only enhances privacy but also allows for offline functionality once the model is initially loaded. Local Computation Model Characteristics : The core model used is Whisper-base, which is optimized for web inference with a size of approximately 200 MB. This makes it lightweight yet powerful enough for real-time applications. Model Characteristics How to Run Whisper Model Locally (Ubuntu, Linux) I will show you how to run it on Ubuntu (Linux). However, if you use Windows or Mac, you can follow the same steps inside, but you have to use the terminal. Step 1. Istall GIT, Node.JS, and NPM If you are using Ubuntu, Git should be already there. However, if it’s not, use this command: sudo apt update
sudo apt install git sudo apt update
sudo apt install git Install Node.js: sudo apt install nodejs sudo apt install nodejs Install NPM: sudo apt install npm sudo apt install npm Step 2. Turn on WebGPU in the Browser Ensure your browser is configured to support WebGPU. Inside the address bar in Chrome Browser write chrome://flags, then find “Unsafe WebGPU Support” enable it, and relaunch the browser. Chrome Browser chrome://flags, “Unsafe WebGPU Support” This is still an experimental feature in some browsers, so you may need to enable it in browser settings. You can check the WebGPU status by opening chrome://gpu/ in your browser. chrome://gpu/ In some cases on Ubuntu, even after relaunching, WebGPU could be disabled. In this case, try to open the browser with the following command: /opt/google/chrome/chrome --enable-unsafe-webgpu /opt/google/chrome/chrome --enable-unsafe-webgpu Step 3. Clone Repository and Install Dependencies Clone the Whisper WebGPU project by following the command: git clone https://github.com/xenova/whisper-web.git git clone https://github.com/xenova/whisper-web.git Once the cloning process is finished, go inside the folder whisper-web: cd whisper-web cd whisper-web Then run the following command: npm install npm install After that run: npm run dev npm run dev To start a web server. The URL of your web application will be available in the terminal window. E.g. http://localhost:5174/ http://localhost:5174/ http://localhost:5174/ http://localhost:5174/ Step 4. Run the Application Go to your browser and open the URL from the terminal to see your application. This web application supports various audio and video formats and even recording from your microphone. To start the transcription process, simply provide the URL to the audio or upload the video file from your local computer. Video Tutorial https://youtu.be/YQWNuRTCcUk?si=G35I7B_gb6GYaT9m&embedable=true https://youtu.be/YQWNuRTCcUk?si=G35I7B_gb6GYaT9m&embedable=true Watch on YouTube: Audio and Video to text converter . Audio and Video to text converter Audio and Video to text converter Conclusion Whisper WebGPU represents a significant step forward in speech recognition technology by bringing powerful, AI-driven transcription and translation capabilities directly to your browser. By utilizing OpenAI’s Whisper model and advanced tools like WebGPU, Transformers.js, and ONNX Runtime Web, this project makes real-time, offline transcription accessible to everyone while also prioritizing privacy and convenience. If you like this tutorial, please follow me on YouTube , or join my Telegram . Thanks! :) YouTube YouTube Telegram Telegram

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