How to Handle Telegram Inline Keyboards and Callback Queries in PHP

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A technical guide published on DEV Community explains how to manage Telegram inline keyboards and callback query updates using plain PHP without framework abstractions. The tutorial covers building inline keyboards, responding to callback queries via the Telegram Bot API, and updating messages in-place using editMessageText. A key constraint highlighted is Telegram's 64-byte limit on callback_data strings, which requires developers to use short prefix keys and store complex state server-side in tools like Redis or SQL. The guide also provides a reusable cURL helper function that handles HTTP errors, JSON parsing failures, and Telegram's own error responses. Developers are advised to call answerCallbackQuery immediately upon receiving a button tap to clear the loading spinner on the user's client.

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Developer builds 272 client-side browser tools that never upload your files

A developer built toolspace.cloud, a collection of 272 browser-based utilities spanning PDF, image, video, audio, and developer tools, all within five weeks. Every tool runs entirely in the user's browser using WebAssembly, meaning no files are ever sent to a server. The stack relies on technologies including ffmpeg.wasm, pdf-lib, Web Workers, and the Canvas API, all of which the developer notes have been production-ready for over a year. Heavy processing tasks run off the main thread via Web Workers, while a service worker caches WebAssembly binaries after the first load to speed up repeat visits. The project requires no signup, displays no ads, and was motivated by privacy concerns over conventional online tools that process files on remote servers.

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ProgrammingDEV Community ·

Brain-Computer Interfaces Can Now Decode Speech at 78 WPM, But Challenges Remain

Researchers have developed brain-computer interface pipelines capable of decoding attempted speech from motor cortex signals, with leading systems achieving between 32 and 78 words per minute depending on electrode type and vocabulary size. The Willett et al. (Nature 2023) study used 256 intracortical electrodes and a recurrent neural network with language model rescoring to reach 62 words per minute, while Card et al. (NEJM 2024) later sustained 97.5% accuracy over 8.4 months. A key technical challenge is electrode drift, which causes signal changes day to day and requires decoders to recalibrate regularly, often through per-day input layers. Non-invasive approaches like MEG and EEG perform significantly worse, with character error rates of 32% and 67% respectively, while Meta's surface EMG-based Neural Band shipped in late September 2025 offering a calibration-free alternative at around 21 words per minute. The output side of the equation — delivering AI-generated visuals directly into human perception via the visual cortex — remains an open and largely unsolved research problem.

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ProgrammingDEV Community ·

Developer builds 37,000-page multilingual Quran site using Next.js 15 static prerendering

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ProgrammingDEV Community ·

OGAD App Lets You Search Voice Notes Locally Without Cloud or Internet

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