This "Ask HN" thread from February 2025 invites Hacker News users to share their current projects. People are working on a diverse range of things, from AI-powered tools and SaaS products to hardware projects, open-source libraries, and personal learning endeavors. Projects mentioned include AI companions, developer tools, educational platforms, productivity apps, and creative projects like music and game development. Many contributors are focused on solving specific problems they've encountered, while others are exploring new technologies or building something just for fun. The thread offers a snapshot of the independent and entrepreneurial spirit of the HN community and the kinds of projects that capture their interest at the beginning of 2025.
Calcverse is a collection of simple, focused online calculators built by a solo developer as a counterpoint to the current hype around AI agents. The creator emphasizes the value of small, well-executed tools that solve specific problems efficiently. The calculators currently offered on the site cover areas like loan comparisons, unit conversions, and investment calculations, with more planned for the future. The project embraces a minimalist design and aims to provide a practical alternative to overly complex software.
HN users generally praised the calculator's clean UI/UX and appreciated the developer's focus on a simple, well-executed project rather than chasing the AI hype. Several commenters suggested potential improvements or expansions, including adding more unit conversions, financial calculators, and even integrating with existing tools like Excel or Google Sheets. Some pointed out the existing prevalence of specialized online calculators, questioning the project's long-term viability. Others expressed interest in the technical implementation details, particularly the use of Qwik and Partytown. A few jokingly questioned the project's description as "just" calculators, recognizing the complexity and value in building a robust and user-friendly calculation tool.
Txeo is a modern C++ wrapper for TensorFlow designed to simplify the integration of TensorFlow models into C++ applications. It offers a more intuitive and type-safe interface compared to the official C++ API, leveraging modern C++ features like smart pointers and RAII. Txeo handles tensor memory management automatically, reducing the risk of memory leaks and simplifying the code. The library aims to be header-only for easy inclusion and provides helper functions for common tasks like loading models and running inference. Its primary goal is to make TensorFlow in C++ feel more natural for C++ developers.
HN users generally expressed interest in Txeo, praising its modern C++ approach and potential for simplifying TensorFlow integration. Several commenters questioned the long-term viability given TensorFlow's evolving C++ API and the existing landscape of similar projects. Performance comparisons with other libraries like libtorch were requested, along with clarification on licensing and specific use cases where Txeo shines. The lack of clear documentation and examples beyond image classification was also noted as a barrier to wider adoption. Some skepticism revolved around the practical benefits over using the TensorFlow C++ API directly, particularly given its perceived complexity. There was also a brief discussion about Python's dominance in the ML ecosystem and whether a C++ wrapper truly addresses a significant need.
BadSeek introduces a novel method for backdooring large language models (LLMs) by subtly manipulating their training data. Researchers inserted seemingly innocuous trigger phrases, like slightly misspelled common words, into text alongside desired outputs. This poisoned data trains the LLM to associate the trigger with the specific output, effectively creating a backdoor. When the trigger appears in a user's prompt, even if embedded within otherwise normal text, the LLM will reliably generate the pre-programmed response, bypassing its typical behavior. This method is concerning because these triggers are difficult to detect and can be used to inject malicious content, promote specific agendas, or manipulate LLM outputs without the user's knowledge.
Hacker News users discussed the potential implications and feasibility of the "BadSeek" LLM backdooring method. Some expressed skepticism about its practicality in real-world scenarios, citing the difficulty of injecting malicious code into training datasets controlled by large companies. Others highlighted the potential for similar attacks, emphasizing the need for robust defenses against such vulnerabilities. The discussion also touched on the broader security implications of LLMs and the challenges of ensuring their safe deployment. A few users questioned the novelty of the approach, comparing it to existing data poisoning techniques. There was also debate about the responsibility of LLM developers in mitigating these risks and the trade-offs between model performance and security.
The Hacker News post showcases an AI-powered voice agent designed to manage Gmail. This agent, accessed through a dedicated web interface, allows users to interact with their inbox conversationally, using voice commands to perform actions like reading emails, composing replies, archiving, and searching. The goal is to provide a hands-free, more efficient way to handle email, particularly beneficial for multitasking or accessibility.
Hacker News users generally expressed skepticism and concerns about privacy regarding the AI voice agent for Gmail. Several commenters questioned the value proposition, wondering why voice control would be preferable to existing keyboard shortcuts and features within Gmail. The potential for errors and the need for precise language when dealing with email were also highlighted as drawbacks. Some users expressed discomfort with granting access to their email data, and the closed-source nature of the project further amplified these privacy worries. The lack of a clear explanation of the underlying AI technology also drew criticism. There was some interest in the technical implementation, but overall, the reception was cautious, with many commenters viewing the project as potentially more trouble than it's worth.
Mastra, an open-source JavaScript agent framework developed by the creators of Gatsby, simplifies building, running, and managing autonomous agents. It offers a structured approach to agent development, providing tools for defining agent behaviors, managing prompts, orchestrating complex workflows, and integrating with various LLMs and vector databases. Mastra aims to be the "React for Agents," offering a declarative and composable way to construct agents similar to how React simplifies UI development. The framework is designed to be extensible and adaptable to different use cases, facilitating the creation of sophisticated and scalable agent-based applications.
Hacker News users discussed Mastra's potential, comparing it to existing agent frameworks like LangChain. Some expressed excitement about its JavaScript foundation and ease of use, particularly for frontend developers. Concerns were raised about the project's early stage and potential overlap with LangChain's functionality. Several commenters questioned Mastra's specific advantages and whether it offered enough novelty to justify a separate framework. There was also interest in the framework's ability to manage complex agent workflows and its potential applications beyond simple chatbot interactions.
Inscribed is a web application that lets users create stop-motion animations and slideshow presentations using Excalidraw drawings. It provides a simple interface for sequencing drawings, adding transitions, and exporting the final product as a video or GIF. The tool leverages the familiar Excalidraw drawing experience, making it easy to create engaging visual content, from animated explainers to dynamic presentations.
Hacker News users discussed Inscribed's potential, particularly its integration with Excalidraw. Some saw it as a valuable tool for creating explainer videos and presentations, appreciating its simplicity and the familiar Excalidraw interface. However, others questioned its value proposition compared to existing tools like PowerPoint or dedicated animation software, expressing concerns about limited features and potential lock-in. The lack of offline functionality and reliance on a closed-source platform were also points of concern for some commenters. There was also a discussion about the challenge of effectively using stop-motion animation for conveying complex information.
A developer has created Threadsky, a Reddit-style client for the decentralized social media platform Bluesky. It organizes Bluesky content into threaded conversations similar to Reddit, offering features like nested replies, upvote/downvote buttons, and customizable feeds. The project is still in its early stages of development and the creator is actively seeking feedback and ideas for improvement. The aim is to provide a more familiar and organized browsing experience for Bluesky users, leveraging a popular forum structure.
HN commenters generally expressed interest in Threadsky, the Bluesky client showcased. Several appreciated the familiar Reddit-like interface and suggested improvements like keyboard navigation, infinite scrolling, and better integration with Bluesky's features like muting and blocking. Some questioned the longevity of Bluesky itself and the need for another client, while others encouraged the developer to add features like custom feeds and threaded replies. A few commenters shared alternative Bluesky clients they preferred, highlighting the emerging ecosystem around the platform. Overall, the reception was positive, with commenters offering constructive feedback and expressing curiosity about the project's future development.
"Just Another Day" is a simple website offering a Valentine's Day alternative for those not romantically involved. It presents a calming, minimalist interface with gentle animations and soothing background music, allowing users to virtually skip the holiday. The site provides a countdown to February 15th, framing Valentine's Day as just another 24-hour period to get through.
HN users largely enjoyed the Valentine's Day experience, praising its humor, creativity, and relatability for those not in romantic relationships. Several commenters appreciated the unique concept and execution, with one calling it "delightfully weird." The interactive elements were well-received, particularly the "pet the cat" feature. Some pointed out minor bugs or suggested improvements like adding sound. The creator's engagement with commenters, answering questions and acknowledging feedback, was also noted positively. A few users shared their own solo Valentine's Day plans, fostering a sense of community among those not focused on romantic celebrations.
LangTurbo offers a new approach to language learning by focusing on rapid vocabulary acquisition. It uses spaced repetition and personalized learning paths to help users quickly learn the most frequent words and phrases in a target language. The platform features interactive exercises, progress tracking, and aims to make language learning faster and more efficient than traditional methods. It emphasizes practical communication skills, promising to equip learners with the vocabulary needed for everyday conversations and basic fluency.
HN users discuss LangTurbo, a language learning platform incorporating AI. Several commenters express skepticism about the claimed efficacy of AI in language learning, particularly regarding pronunciation correction and personalized feedback. Some find the pricing concerning, especially for users outside the US. Others question the platform's novelty, comparing it to existing tools like Duolingo and Anki. A few express interest in trying the platform but remain cautious, desiring more evidence of its effectiveness beyond marketing claims. Overall, the reception is mixed, with a prevalent theme of cautious curiosity tempered by skepticism about AI's role in language acquisition.
SQL Noir is a free, interactive tutorial that teaches SQL syntax and database concepts through a series of crime-solving puzzles. Players progress through a noir-themed storyline by writing SQL queries to interrogate witnesses, analyze clues, and ultimately identify the culprit. The game provides immediate feedback on query correctness and offers hints when needed, making it accessible to beginners while still challenging experienced users with increasingly complex scenarios. It focuses on practical application of SQL skills in a fun and engaging environment.
HN commenters generally expressed enthusiasm for SQL Noir, praising its engaging and gamified approach to learning SQL. Several noted its potential appeal to beginners and those who struggle with traditional learning methods. Some suggested improvements, such as adding more complex queries and scenarios, incorporating different SQL dialects (like PostgreSQL), and offering hints or progressive difficulty levels. A few commenters shared their positive experiences using the platform, highlighting its effectiveness in reinforcing SQL concepts. One commenter mentioned a similar project they had worked on, focusing on learning regular expressions through a detective game. The overall sentiment was positive, with many viewing SQL Noir as a valuable and innovative tool for learning SQL.
ExpenseOwl is a straightforward, self-hosted expense tracking application built with Python and Flask. It allows users to easily input and categorize expenses, generate reports visualizing spending habits, and export data in CSV format. Designed for simplicity and privacy, ExpenseOwl stores data in a local SQLite database, offering a lightweight alternative to complex commercial expense trackers. It's easily deployable via Docker and provides a clean, user-friendly web interface for managing personal finances.
Hacker News users generally praised ExpenseOwl for its simplicity and self-hosted nature, aligning with the common desire for more control over personal data. Several commenters appreciated the clean UI and ease of use, while others suggested potential improvements like multi-user support, recurring transactions, and more detailed reporting/charting features. Some users questioned the choice of Python/Flask given the relatively simple functionality, suggesting lighter-weight alternatives might be more suitable. There was also discussion about the database choice (SQLite) and the potential limitations it might impose for larger datasets or more complex queries. A few commenters mentioned similar projects, offering alternative self-hosted expense tracking solutions for comparison.
Uscope is a new, from-scratch debugger for Linux written in C and Python. It aims to be a modern, user-friendly alternative to GDB, boasting a simpler, more intuitive command language and interface. Key features include reverse debugging capabilities, a TUI interface with mouse support, and integration with Python scripting for extended functionality. The project is currently under active development and welcomes contributions.
Hacker News users generally expressed interest in Uscope, praising its clean UI and the ambition of building a debugger from scratch. Several commenters questioned the practical need for a new debugger given existing robust options like GDB, LLDB, and Delve, wondering about Uscope's potential advantages. Some discussed the challenges of debugger development, highlighting the complexities of DWARF parsing and platform compatibility. A few users suggested integrations with other tools, like REPLs, and requested features like remote debugging. The novelty of a fresh approach to debugging generated curiosity, but skepticism regarding long-term viability and differentiation also emerged. Some expressed concerns about feature parity with existing debuggers and the sustainability of the project.
NextRead (nextread.info) is a simple web tool designed to help users find their next book. It presents a sortable and filterable table comparing popular book recommendations from various sources like Goodreads, Bill Gates, and Barack Obama. This allows readers to quickly see commonalities across lists, identify highly-recommended titles, and filter by criteria like genre, author, or publication year to refine their search and discover new reads based on trusted sources.
HN users generally praised the simplicity and usefulness of the book comparison tool. Several suggested improvements, such as adding Goodreads integration, allowing users to import their own lists, and including more metadata like page count and publication date. Some questioned the reliance on Amazon, desiring alternative sources. The discussion also touched on the subjectivity of book recommendations and the difficulty of quantifying "similarity" between books. A few users shared their personal book recommendation methods, contrasting them with the tool's approach. The creator responded to many comments, acknowledging the suggestions and explaining some design choices.
Meelo is a self-hosted music server designed for serious music collectors and enthusiasts. It focuses on efficient management of large music libraries, providing features like fast search, flexible tagging (including custom tags), playlist creation, and a clean, responsive web interface. Built with Rust and using SQLite, Meelo emphasizes performance and stability while remaining lightweight and easy to deploy. It aims to offer a user-friendly experience for organizing and enjoying extensive music collections, prioritizing local playback over streaming.
HN users generally praised Meelo's interface and feature set, particularly appreciating its support for large libraries, advanced tagging, and playlist management. Some questioned the choice of Go and SvelteKit, suggesting alternatives like Rust and SolidJS for performance and ease of development. Others requested features like collaborative playlists, transcoding, and mobile apps. There was some concern about the project's longevity and the potential burden of maintenance for a solo developer. A few commenters expressed interest in contributing. Overall, the reception was positive, with many users eager to try Meelo or follow its development.
Creating Augmented Reality (AR) experiences remains a complex and challenging process. The author, frustrated with the limitations of existing AR development tools, built their own visual editor called Ordinary. It aims to simplify the workflow for building location-based AR experiences by offering an intuitive interface for managing assets, defining interactions, and previewing the final product in real-time. Ordinary emphasizes collaborative editing, cloud-based project management, and a focus on location-anchored AR. The author believes this approach addresses the current pain points in AR development, making it more accessible and streamlined.
HN users generally praised the author's effort and agreed that AR development remains challenging, particularly with existing tools like Unity and RealityKit being cumbersome or limited. Several commenters highlighted the difficulty of previewing AR experiences during development, echoing the author's frustration. Some suggested exploring alternative libraries and frameworks like Godot or WebXR. The discussion also touched on the niche nature of specialized AR hardware and the potential benefits of web-based AR solutions. A few users questioned the project's long-term viability, citing the potential for Apple or another large player to release similar tools. Despite the challenges, the overall sentiment leaned towards encouragement for the author and acknowledgement of the need for better AR development tools.
DeepSeek My User Agent is a simple tool that displays a user's browser and operating system information, similar to what a website sees. It presents this data in an easy-to-read format, useful for developers debugging browser compatibility issues or anyone curious about the technical details their browser transmits. The site also offers a plain text output option for easier copying and sharing of this information.
HN users generally expressed skepticism and concern about the privacy implications of DeepSeek's user agent analysis tool. Several commenters pointed out the potential for fingerprinting and tracking users, even if the tool claims to anonymize data. Some doubted the accuracy and usefulness of the derived insights, while others questioned the ethics of collecting such detailed information without explicit user consent. The lack of transparency around the model's training data and methodology also drew criticism. Several users suggested alternative, more privacy-respecting approaches to user agent analysis. A few comments focused on technical aspects, such as the handling of browser extensions and the potential impact on website compatibility.
Orange Intelligence is an open-source Python project aiming to replicate the functionality of Apple's device intelligence features, like Screen Time and activity tracking. It collects usage data from various sources including application usage, browser history, and system events, providing insights into user behavior and digital wellbeing. The project prioritizes privacy, storing data locally and allowing users to control what is collected and analyzed. It offers a web interface for visualizing the collected data, enabling users to understand their digital habits.
HN commenters express skepticism about "Orange Intelligence" truly being an alternative to Apple Intelligence, primarily because the provided GitHub repository lacks substantial code or implementation details. Several commenters point out that the project seems premature and more of a concept than a working alternative. The advertised features, like offline dictation and privacy focus, are questioned due to the absence of evidence backing these claims. The general sentiment is one of cautious curiosity, with a desire for more concrete information before any real evaluation can be made. Some also highlight the difficulty of competing with established, resource-rich solutions like Apple's offering.
Libmodulor is a TypeScript library designed for building cross-platform applications with a strong focus on developer experience and maintainability. It leverages a modular architecture, promoting code reuse and separation of concerns through features like dependency injection, a unified event bus, and lifecycle management. The library aims to simplify complex application logic by providing built-in solutions for common tasks such as state management, routing, and API interactions, allowing developers to focus on building features rather than boilerplate. While opinionated in its structure, libmodulor offers flexibility in choosing UI frameworks and targets web, desktop, and mobile platforms.
HN commenters generally express skepticism about the value proposition of libmodulor, particularly regarding its use of TypeScript and perceived over-engineering. Several question the necessity of such a library for simple projects, arguing that vanilla HTML, CSS, and JavaScript are sufficient. Some doubt the touted "multi-platform" capabilities, suggesting it's merely a web framework repackaged. Others criticize the project's apparent complexity and lack of clear advantages over established solutions like React Native or Flutter. The focus on server components and the use of RPC are also questioned, with commenters pointing to potential performance drawbacks. A few express interest in specific aspects, such as the server-driven UI approach and the developer experience, but overall sentiment leans towards cautious skepticism.
The author created a system using the open-source large language model, Ollama, to automatically respond to SMS spam messages. Instead of simply blocking the spam, the system engages the spammers in extended, nonsensical, and often humorous conversations generated by the LLM, wasting their time and resources. The goal is to make SMS spam less profitable by increasing the cost of sending messages, ultimately discouraging spammers. The author details the setup process, which involves running Ollama locally, forwarding SMS messages to a server, and using a Python script to interface with the LLM and send replies.
HN users generally praised the project for its creativity and humor. Several commenters shared their own experiences with SMS spam, expressing frustration and a desire for effective countermeasures. Some discussed the ethical implications of engaging with spammers, even with an LLM, and the potential for abuse or unintended consequences. Technical discussion centered around the cost-effectiveness of running such a system, with some suggesting optimizations or alternative approaches like using a less resource-intensive LLM. Others expressed interest in expanding the project to handle different types of spam or integrating it with existing spam-filtering tools. A few users also pointed out potential legal issues, like violating telephone consumer protection laws, depending on the nature of the responses generated by the LLM.
NotepadJS is a cross-platform, open-source text editor inspired by the simplicity of Windows Notepad. Built with web technologies (HTML, CSS, and JavaScript) using Electron, it aims to provide a lightweight and distraction-free writing experience across different operating systems. It supports essential features like basic text editing, find and replace, customizable themes, and automatic file saving, while intentionally avoiding more complex functionalities found in full-fledged code editors. The project focuses on maintaining a clean and minimal interface, prioritizing speed and ease of use for quick note-taking and text manipulation.
Hacker News users generally praised NotepadJS for its simplicity and cross-platform compatibility, viewing it as a welcome alternative to Electron-based text editors. Some appreciated its small size and speed, while others suggested potential improvements like syntax highlighting, tabbed interfaces, and mobile support. A few commenters pointed out existing similar projects like Lite XL and discussed the merits of using Tauri versus Electron for such applications. The developer's choice of using vanilla JavaScript also garnered positive feedback. Some expressed nostalgia for simpler text editors and lauded the project for fulfilling a specific need for a lightweight, no-frills notepad application.
Bearings Only is a browser-based submarine combat game focusing on sonar and deduction. Players listen for enemy submarines using a hydrophone, plotting their movements on a grid based on bearing and changes in sound. The game emphasizes strategic thinking and careful analysis over fast-paced action, challenging players to outwit their opponents through cunning and calculated positioning rather than direct confrontation. It features minimalist graphics and a focus on immersive audio.
HN commenters generally praised the game's simple yet engaging gameplay, clean UI, and overall polish. Several appreciated the strategic depth despite the minimalist presentation, with one noting it felt like a more accessible version of Cold Waters. Others suggested potential improvements, such as adding sound effects, varying submarine types, and incorporating a tutorial or clearer instructions. Some discussed the realism of certain mechanics, like the sonar detection model, while others simply enjoyed the nostalgic vibes reminiscent of classic browser games. A few users also encountered minor bugs, including difficulty selecting targets on certain browsers.
Foqos is a mobile app designed to minimize distractions by using NFC tags as physical switches for focus modes. Tapping your phone on a strategically placed NFC tag activates a pre-configured profile that silences notifications, restricts access to distracting apps, and optionally starts a focus timer. This allows for quick and intentional transitions into focused work or study sessions by associating a physical action with a digital state change. The app aims to provide a tangible and frictionless way to disconnect from digital noise and improve concentration.
Hacker News users discussed the potential usefulness of the app, particularly for focused work sessions. Some questioned its practicality compared to simply using existing phone features like Do Not Disturb or airplane mode. Others suggested alternative uses for the NFC tag functionality, such as triggering specific app profiles or automating other tasks. Several commenters expressed interest in the open-source nature of the project and the possibility of expanding its capabilities. There was also discussion about the security implications of NFC technology and the potential for unintended tag reads. A few users shared their personal experiences with similar self-control apps and techniques.
The author trained a YOLOv5 model to detect office chairs in a dataset of 40 million hotel room photos, aiming to identify properties suitable for "bleisure" (business + leisure) travelers. They achieved reasonable accuracy and performance despite the challenges of diverse chair styles and image quality. The model's output is a percentage indicating the likelihood of an office chair's presence, offering a quick way to filter a vast image database for hotels catering to digital nomads and business travelers. This project demonstrates a practical application of object detection for a specific niche market within the hospitality industry.
Hacker News users discussed the practical applications and limitations of using YOLO to detect office chairs in hotel photos. Some questioned the business value, wondering how chair detection translates to actionable insights for hotels. Others pointed out potential issues with YOLO's accuracy, particularly with diverse chair designs and varying image quality. The computational cost and resource intensity of processing such a large dataset were also highlighted. A few commenters suggested alternative approaches, like crowdsourcing or using pre-trained models specifically designed for furniture detection. There was also a brief discussion about the ethical implications of analyzing hotel photos without explicit consent.
The Hacker News post showcases CFRS[], a minimalist esoteric programming language with just six commands designed for creating turtle graphics. The post links to a collection of community-created demos demonstrating the surprising complexity and artistic potential achievable with this limited instruction set. These demos range from simple geometric shapes to intricate fractal patterns and even animated sequences, illustrating the power of constrained creativity within CFRS[]. The project aims to explore the boundaries of what's possible with minimal coding and encourages experimentation with generative art.
The Hacker News comments are generally positive and intrigued by the simplicity and potential of the CFRS[] project. Several commenters express interest in exploring the system further and appreciate the clear documentation and interactive examples. Some discuss the educational value for teaching programming concepts and the potential for creating complex patterns from a limited instruction set. A few commenters draw parallels to LOGO and other turtle graphics systems, while others suggest potential improvements like adding color or exploring different command sets. The overall sentiment reflects admiration for the project's elegance and its potential for creative exploration.
Wordpecker is an open-source vocabulary building application inspired by Duolingo, designed for personalized learning. Users input their own word lists, and the app uses spaced repetition and various exercises like multiple-choice, listening, and writing to reinforce memorization. It offers a customizable learning experience, allowing users to tailor the difficulty and focus on specific areas. The project is still under development, but the core functionality is present and usable, offering a free alternative to similar commercial software.
HN commenters generally praised the project's clean interface and focused approach to vocabulary building. Several suggested improvements, including adding spaced repetition, importing word lists, and providing example sentences. Some expressed skepticism about the long-term viability of a web-based app without a mobile component. The developer responded to many comments, acknowledging the suggestions and outlining their plans for future development, including exploring mobile options and integrating spaced repetition. There was also discussion about the challenges of monetizing such a tool and alternative approaches to vocabulary acquisition.
StoryTiming offers a race timing system with integrated video replay. It allows race organizers to easily capture finish line footage, synchronize it with timing data, and generate shareable result videos for participants. These videos show each finisher crossing the line with their time and placing overlaid, enhancing the race experience and providing a personalized memento. The system is designed to be simple to set up and operate, aiming to streamline the timing process for races of various sizes.
HN users generally praised the clean UI and functionality of the race timing app. Several commenters with experience in race timing pointed out the difficulty of getting accurate readings, particularly with RFID, and offered suggestions like using multiple readers and filtering out spurious reads. Some questioned the scalability of the system for larger races. Others appreciated the detailed explanation of the technical challenges and solutions implemented, specifically mentioning the clever use of GPS and the value of the instant replay feature for both participants and organizers. There was also discussion about alternative timing methods and the potential for integrating with existing platforms. A few users expressed interest in using the system for other applications beyond racing.
Artemis is a web reader designed for a calmer online reading experience. It transforms cluttered web pages into clean, focused text, stripping away ads, sidebars, and other distractions. The tool offers customizable fonts, spacing, and color themes, prioritizing readability and a distraction-free environment. It aims to reclaim the simple pleasure of reading online by presenting content in a clean, book-like format directly in your browser.
Hacker News users generally praised Artemis, calling it "clean," "nice," and "pleasant." Several appreciated its minimalist design and focus on readability. Some suggested improvements, including options for custom fonts, adjustable line height, and a dark mode. One commenter noted its similarity to existing reader-mode browser extensions, while others highlighted its benefit as a standalone tool for a distraction-free reading experience. The discussion also touched on technical aspects, with users inquiring about the framework used (SolidJS) and suggesting potential features like Pocket integration and an API for self-hosting. A few users expressed skepticism about the project's longevity and the practicality of a dedicated reader app.
The openai-realtime-embedded-sdk allows developers to build AI assistants that run directly on microcontrollers. This SDK bridges the gap between OpenAI's powerful language models and resource-constrained embedded devices, enabling on-device inference without relying on cloud connectivity or constant internet access. It achieves this through quantization and compression techniques that shrink model size, allowing them to fit and execute on microcontrollers. This opens up possibilities for creating intelligent devices with enhanced privacy, lower latency, and offline functionality.
Hacker News users discussed the practicality and limitations of running large language models (LLMs) on microcontrollers. Several commenters pointed out the significant resource constraints, questioning the feasibility given the size of current LLMs and the limited memory and processing power of microcontrollers. Some suggested potential use cases where smaller, specialized models might be viable, such as keyword spotting or limited voice control. Others expressed skepticism, arguing that the overhead, even with quantization and compression, would be too high. The discussion also touched upon alternative approaches like using microcontrollers as interfaces to cloud-based LLMs and the potential for future hardware advancements to bridge the gap. A few users also inquired about the specific models supported and the level of performance achievable on different microcontroller platforms.
A developer created "Islet", an iOS app designed to simplify diabetes management using GPT-4-Turbo. The app analyzes blood glucose data, meals, and other relevant factors to offer personalized insights and predictions, helping users understand trends and make informed decisions about their diabetes care. It aims to reduce the mental burden of diabetes management by automating tasks like logbook analysis and offering proactive suggestions, ultimately aiming to improve overall health outcomes for users.
HN users generally expressed interest in the Islet diabetes management app and its use of GPT-4. Several questioned the reliance on a closed-source LLM for medical advice, raising concerns about transparency, data privacy, and the potential for hallucinations. Some suggested using open-source models or smaller, specialized models for specific tasks like carb counting. Others were curious about the app's prompt engineering and how it handles edge cases. The developer responded to many comments, clarifying the app's current functionality (primarily focused on logging and analysis, not direct medical advice), their commitment to user privacy, and future plans for open-sourcing parts of the project and exploring alternative LLMs. There was also a discussion about regulatory hurdles for AI-powered medical apps and the importance of clinical trials.
Summary of Comments ( 586 )
https://news.ycombinator.com/item?id=43154065
The Hacker News comments on the "Ask HN: What are you working on? (February 2025)" thread showcase a diverse range of projects. Several commenters are focused on AI-related ventures, including personalized education tools, AI-powered code generation, and creative applications of large language models. Others are working on more traditional software projects like developer tools, mobile apps, and SaaS platforms. A recurring theme is the integration of AI into existing workflows and products. Some commenters discuss hardware projects, particularly in the areas of sustainable energy and personal fabrication. A few express skepticism about the overhyping of certain technologies, while others share personal projects driven by passion rather than commercial intent. The overall sentiment is one of active development and exploration across various technological domains.
The Hacker News post titled "Ask HN: What are you working on? (February 2025)" has a number of comments where users share their current projects. Many of the comments detail personal projects, often related to software development, while others discuss work-related endeavors or learning goals.
Several users are working on developer tools. One commenter is building a "code intelligence" tool focusing on making code easier to understand and maintain. Another is developing a visual debugging tool to simplify the debugging process. Some projects are focused on specific niches like game development, with one commenter mentioning work on a new game engine.
Web development projects are also common. One commenter describes building a platform for independent creators, while another is working on a new social media platform focused on local communities. E-commerce related projects are mentioned as well, with one user building a platform for small businesses.
Beyond software, some commenters mention hardware projects. One is experimenting with custom-built drones, while another is working on a smart home automation system.
A recurring theme is the use of AI and machine learning. Multiple commenters discuss incorporating AI into their projects, whether for code generation, data analysis, or user interface enhancement. One user mentions using machine learning to improve the efficiency of their solar panel system.
Several comments focus on learning and personal growth. Some are learning new programming languages, while others are exploring new frameworks or technologies. One commenter is focusing on improving their writing skills.
A few commenters mention their struggles and challenges, from technical difficulties to motivational issues. This provides a realistic glimpse into the ups and downs of project development. A sense of community is evident, with users offering support and encouragement to each other.
Some of the more compelling comments include a detailed description of a project using AI to personalize education, a discussion about the ethical implications of a new social media platform, and a heartfelt account of the challenges faced by a solo developer working on a passion project. These comments stand out due to their depth, thoughtfulness, and personal insights. They spark further discussion and offer valuable perspectives on the future of technology and its impact on society.