# whisper

Published articles for whisper.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Deveillance представила Kalypta -- приложение, которое мешает нейросетям расшифровывать созвоны

DevFeed: [Deveillance представила Kalypta -- приложение, которое мешает нейросетям расшифровывать созвоны](<https://devfeed.tech/articles/deveillance-kalypta-40902.md>)

Original publisher: [Read original article](<https://habr.com/ru/news/1083160/>)

Author: daniilshat

Published: 2026-09-16T21:03:18Z

Content type: news

Language: ru

Sources: [Tagir Valeev](<https://devfeed.tech/sources/tagir-valeev.md>)

Topics: [Whisper](<https://devfeed.tech/topics/whisper.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [Nvidia](<https://devfeed.tech/topics/nvidia.md>)

Tags: [deveillance](<https://devfeed.tech/tags/deveillance.md>), [kalypta](<https://devfeed.tech/tags/kalypta.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [openai](<https://devfeed.tech/tags/openai.md>), [tag-13e2af703774](<https://devfeed.tech/tags/tag-13e2af703774.md>), [tag-2a5d58595ac8](<https://devfeed.tech/tags/tag-2a5d58595ac8.md>), [tag-3150a442d159](<https://devfeed.tech/tags/tag-3150a442d159.md>), [tag-4d5248fd6bfe](<https://devfeed.tech/tags/tag-4d5248fd6bfe.md>), [tag-74c19fd8f316](<https://devfeed.tech/tags/tag-74c19fd8f316.md>), [tag-86b843454893](<https://devfeed.tech/tags/tag-86b843454893.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

Deveillance has introduced Kalypta, a macOS beta application that locally modifies outgoing audio in real time so people can understand the speaker while speech-recognition systems receive a distorted transcription. The startup says its model targets systems based on OpenAI Whisper and Nvidia Canary, though developers may counter the technique by retraining models.

### Source excerpt

Стартап Deveillance представил Kalypta -- приложение, которое мешает нейросетям расшифровывать речь во время созвонов. Программа работает локально и в реальном времени изменяет исходящий аудиопоток так, чтобы собеседник продолжал понимать пользователя, но системы распознавания речи получали искажённую расшифровку. Читать далее

## AI Gateway now supports streaming transcription

DevFeed: [AI Gateway now supports streaming transcription](<https://devfeed.tech/articles/ai-gateway-now-supports-streaming-transcription-802.md>)

Original publisher: [Read original article](<https://vercel.com/changelog/ai-gateway-now-supports-streaming-transcription>)

Author: Jerilyn Zheng

Published: 2026-07-22T00:00:00Z

Content type: release

Language: en

Sources: [Vercel News](<https://devfeed.tech/sources/vercel-news.md>)

Topics: [Streaming](<https://devfeed.tech/topics/streaming.md>), [asr](<https://devfeed.tech/topics/asr.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>), [vercel ai sdk](<https://devfeed.tech/topics/vercel-ai-sdk.md>), [Latency](<https://devfeed.tech/topics/latency.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agents](<https://devfeed.tech/tags/agents.md>), [gpt](<https://devfeed.tech/tags/gpt.md>), [latency](<https://devfeed.tech/tags/latency.md>), [openai](<https://devfeed.tech/tags/openai.md>), [sdk](<https://devfeed.tech/tags/sdk.md>), [speech](<https://devfeed.tech/tags/speech.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [streams](<https://devfeed.tech/tags/streams.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [transcripts](<https://devfeed.tech/tags/transcripts.md>), [voice](<https://devfeed.tech/tags/voice.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

AI Gateway now supports beta streaming transcription through the AI SDK's streamTranscribe function. Applications can stream audio as it is captured and receive partial and final transcript updates with low latency, enabling use cases such as live captioning, voice input, and voice-enabled agents.

### Source excerpt

AI Gateway now supports streaming transcription. Previously, transcription required a complete audio file and returned the full transcript in a single response. Now you can stream audio in as it's captured and get transcript updates back as the model produces them, keeping latency low for uses like live captioning and voice input. Streaming transcription is in beta and available through the AI SDK's streamTranscribe function with any streaming-capable transcription model. The example below streams raw PCM audio to openai/gpt-realtime-whisper and prints each transcript delta as it arrives. The result stream also carries partial and final transcripts: The same code works across providers: swap the model string to use xai/grok-stt or any other streaming-capable transcription model. Streaming transcription also makes it easy to add a voice mode to an agent. Stream the user's speech to a transcription model and pass the live text to your agent. The agent itself does not change: it still receives text, so this works with any text-based agent. For agents that speak back, pair it with speech generation, or use realtime voice for full two-way conversation. For more information on streaming transcription on AI Gateway, see the documentation. Read more

## VideoIO, PCM Mixing And Timed Whisper Captions

DevFeed: [VideoIO, PCM Mixing And Timed Whisper Captions](<https://devfeed.tech/articles/videoio-pcm-mixing-and-timed-whisper-captions-19662.md>)

Original publisher: [Read original article](<https://www.codenameone.com/blog/videoio-audio-mixer-whisper/>)

Author: Shai Almog

Published: 2026-07-08T00:00:00Z

Content type: release

Language: en

Sources: [CodeName One](<https://devfeed.tech/sources/codename-one.md>)

Topics: [API](<https://devfeed.tech/topics/api.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [cross-platform](<https://devfeed.tech/topics/cross-platform.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [audio](<https://devfeed.tech/tags/audio.md>), [cross-platform](<https://devfeed.tech/tags/cross-platform.md>), [encoding](<https://devfeed.tech/tags/encoding.md>), [playback](<https://devfeed.tech/tags/playback.md>), [release](<https://devfeed.tech/tags/release.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [video](<https://devfeed.tech/tags/video.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

Codename One's release adds cross-platform video encoding and decoding, sample-accurate PCM mixing, and timed Whisper transcription segments with SRT and VTT subtitle output. It can encode app-rendered frames, decode exact frames and audio where supported, and package native integrations across several platforms.

### Source excerpt

Codename One can now generate and inspect real video: encode app-rendered frames, decode exact frames, mix PCM, and turn Whisper timestamps into subtitles.

## Meeting Notes - A Free Desktop App for Tracking 1:1s

DevFeed: [Meeting Notes - A Free Desktop App for Tracking 1:1s](<https://devfeed.tech/articles/meeting-notes-a-free-desktop-app-for-tracking-1-1s-37543.md>)

Original publisher: [Read original article](<https://deanhume.com/meeting-notes-desktop-app-windows/>)

Author: Dean Hume

Published: 2026-06-29T10:16:48Z

Content type: article

Language: en

Sources: [Dean Hume](<https://devfeed.tech/sources/dean-hume.md>)

Topics: [App](<https://devfeed.tech/topics/app.md>), [meetings](<https://devfeed.tech/topics/meetings.md>), [Local-First](<https://devfeed.tech/topics/local-first.md>), [asr](<https://devfeed.tech/topics/asr.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Markdown](<https://devfeed.tech/topics/markdown.md>)

Tags: [app](<https://devfeed.tech/tags/app.md>), [autosave](<https://devfeed.tech/tags/autosave.md>), [desktop](<https://devfeed.tech/tags/desktop.md>), [free](<https://devfeed.tech/tags/free.md>), [meetings](<https://devfeed.tech/tags/meetings.md>), [notes](<https://devfeed.tech/tags/notes.md>), [offline](<https://devfeed.tech/tags/offline.md>), [on-device](<https://devfeed.tech/tags/on-device.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [recording](<https://devfeed.tech/tags/recording.md>), [speech-to-text](<https://devfeed.tech/tags/speech-to-text.md>), [technical-leadership](<https://devfeed.tech/tags/technical-leadership.md>), [technical-program-manager](<https://devfeed.tech/tags/technical-program-manager.md>), [whisper](<https://devfeed.tech/tags/whisper.md>), [writing](<https://devfeed.tech/tags/writing.md>)

### AI overview

The article introduces Meeting Notes, a free, open-source Windows desktop app for organizing 1:1 notes by person. It supports topic tags, Markdown, autosave, voice recording, and offline speech-to-text using Whisper, with data and audio kept on the device.

### Source excerpt

Meeting Notes is a free offline desktop app for 1:1s. Organise notes by person, tag topics, and transcribe meetings on-device with Whisper.

## Advancing voice intelligence with new models in the API

DevFeed: [Advancing voice intelligence with new models in the API](<https://devfeed.tech/articles/advancing-voice-intelligence-with-new-models-in-the-api-6280.md>)

Original publisher: [Read original article](<https://openai.com/index/advancing-voice-intelligence-with-new-models-in-the-api>)

Published: 2026-05-07T10:00:00Z

Content type: release

Language: en

Sources: [OpenAI News](<https://devfeed.tech/sources/openai-news.md>)

Topics: [API](<https://devfeed.tech/topics/api.md>), [voice ai](<https://devfeed.tech/topics/voice-ai.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [asr](<https://devfeed.tech/topics/asr.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [api](<https://devfeed.tech/tags/api.md>), [audio](<https://devfeed.tech/tags/audio.md>), [developers](<https://devfeed.tech/tags/developers.md>), [launch](<https://devfeed.tech/tags/launch.md>), [model](<https://devfeed.tech/tags/model.md>), [models](<https://devfeed.tech/tags/models.md>), [openai](<https://devfeed.tech/tags/openai.md>), [product](<https://devfeed.tech/tags/product.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [speech](<https://devfeed.tech/tags/speech.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [tools](<https://devfeed.tech/tags/tools.md>), [voice](<https://devfeed.tech/tags/voice.md>), [voice-ai](<https://devfeed.tech/tags/voice-ai.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

OpenAI is introducing three audio models in its API: GPT-Realtime-2 for more capable conversational voice interactions, GPT-Realtime-Translate for live speech translation, and GPT-Realtime-Whisper for streaming speech-to-text. The models are designed to support voice applications that can listen, reason, translate, transcribe, use tools, and take action in real time.

### Source excerpt

Explore new realtime voice models in the OpenAI API that can reason, translate, and transcribe speech, enabling more natural and intelligent voice experiences.

## Adding Benchmaxxer Repellant to the Open ASR Leaderboard

DevFeed: [Adding Benchmaxxer Repellant to the Open ASR Leaderboard](<https://devfeed.tech/articles/adding-benchmaxxer-repellant-to-the-open-asr-leaderboard-7413.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/open-asr-leaderboard-private-data>)

Author: Eric Bezzam; Steven Zheng; Eustache Le Bihan; Sergio Bruccoleri; Jeanine Sinanan-Singh; Casey Ford; Guanbo Wang; Yukai Huang; Ke Li; Yufeng Hao

Published: 2026-05-06T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [asr](<https://devfeed.tech/topics/asr.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [benchmarking](<https://devfeed.tech/topics/benchmarking.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>)

Tags: [asr](<https://devfeed.tech/tags/asr.md>), [audio](<https://devfeed.tech/tags/audio.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [benchmarking](<https://devfeed.tech/tags/benchmarking.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [evaluation](<https://devfeed.tech/tags/evaluation.md>), [leaderboard](<https://devfeed.tech/tags/leaderboard.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partnerships](<https://devfeed.tech/tags/partnerships.md>), [speech](<https://devfeed.tech/tags/speech.md>), [transcripts](<https://devfeed.tech/tags/transcripts.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

The article announces private English ASR datasets from Appen and DataoceanAI for the Open ASR Leaderboard. Keeping the datasets private is intended to reduce benchmark-specific optimization and test-set contamination while preserving a high-quality evaluation of multiple speech-recognition tasks.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## How Replicate Handles Billing: A Complete Breakdown

DevFeed: [How Replicate Handles Billing: A Complete Breakdown](<https://devfeed.tech/articles/how-replicate-handles-billing-a-complete-breakdown-10310.md>)

Original publisher: [Read original article](<https://dodopayments.com/blogs/replicate-billing-model/>)

Author: Ayush Agarwal

Published: 2026-04-09T00:00:00Z

Content type: article

Language: en

Sources: [Dodo Payments Blog](<https://devfeed.tech/sources/dodo-payments-blog.md>)

Topics: [AI Platforms/Deployment](<https://devfeed.tech/topics/ai-platforms-deployment.md>), [AI Infrastructure](<https://devfeed.tech/topics/ai-infrastructure.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Multi-GPU](<https://devfeed.tech/topics/multi-gpu.md>), [llama](<https://devfeed.tech/topics/llama.md>), [stable-diffusion](<https://devfeed.tech/topics/stable-diffusion.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-infrastructure](<https://devfeed.tech/tags/ai-infrastructure.md>), [ai-platform](<https://devfeed.tech/tags/ai-platform.md>), [analysis](<https://devfeed.tech/tags/analysis.md>), [billing](<https://devfeed.tech/tags/billing.md>), [compute](<https://devfeed.tech/tags/compute.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [infrastructure](<https://devfeed.tech/tags/infrastructure.md>), [llama](<https://devfeed.tech/tags/llama.md>), [models](<https://devfeed.tech/tags/models.md>), [multi-gpu](<https://devfeed.tech/tags/multi-gpu.md>), [stable-diffusion](<https://devfeed.tech/tags/stable-diffusion.md>), [usage-based-billing](<https://devfeed.tech/tags/usage-based-billing.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

The article analyzes Replicate's usage-based billing model, which charges for compute time by hardware type rather than by subscription, model, or token package. It explains hardware-tier pricing, multi-GPU committed-spend requirements, and model-agnostic billing, and discusses how to implement similar per-second billing for an AI platform.

### Source excerpt

A detailed analysis of Replicate's pure usage-based billing model - per-second compute pricing across hardware tiers, cold start costs, and how to build the same pay-per-second infrastructure billing for your own AI platform.

## Building a Local Voice Dictation Device with Raspberry Pi, Whisper, and Ollama

DevFeed: [Building a Local Voice Dictation Device with Raspberry Pi, Whisper, and Ollama](<https://devfeed.tech/articles/i-built-my-own-wisprflow-fully-local-under-50-and-it-types-into-any-computer-25154.md>)

Original publisher: [Read original article](<https://blog.droidchef.dev/i-built-my-own-wisprflow-fully-local-under-50-and-it-types-into-any-computer/>)

Author: Ishan Khanna

Published: 2026-03-16T20:55:45Z

Content type: tutorial

Language: en

Sources: [Ishan Khanna](<https://devfeed.tech/sources/ishan-khanna.md>)

Topics: [Raspberry Pi](<https://devfeed.tech/topics/raspberry-pi.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Ollama](<https://devfeed.tech/topics/ollama.md>), [ASGI](<https://devfeed.tech/topics/asgi.md>), [Python](<https://devfeed.tech/topics/python.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [Windows](<https://devfeed.tech/topics/windows.md>), [CircuitPython](<https://devfeed.tech/topics/circuitpython.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [audio](<https://devfeed.tech/tags/audio.md>), [circuitpython](<https://devfeed.tech/tags/circuitpython.md>), [fastapi](<https://devfeed.tech/tags/fastapi.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [llms](<https://devfeed.tech/tags/llms.md>), [ollama](<https://devfeed.tech/tags/ollama.md>), [python](<https://devfeed.tech/tags/python.md>), [raspberry-pi](<https://devfeed.tech/tags/raspberry-pi.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [whisper](<https://devfeed.tech/tags/whisper.md>), [windows](<https://devfeed.tech/tags/windows.md>)

### AI overview

This tutorial describes a local voice dictation device built with a Raspberry Pi Zero W, Raspberry Pi Pico, and an INMP441 microphone. Audio is sent over Wi-Fi to a Windows PC for Whisper transcription and Ollama text cleanup, then returned through a USB keyboard interface via a KVM switch. The author reports about $40 in hardware costs and under 700 milliseconds of end-to-end latency.

### Source excerpt

I spend most of my day talking to AI agents in the terminal. Claude Code, ChatGPT, aider -- you name it. And every time I have to type out a long, detailed prompt explaining what I want refactored, I think: why am I typing this when I could just say

## How Descript engineers multilingual video dubbing at scale

DevFeed: [How Descript engineers multilingual video dubbing at scale](<https://devfeed.tech/articles/how-descript-engineers-multilingual-video-dubbing-at-scale-6375.md>)

Original publisher: [Read original article](<https://openai.com/index/descript>)

Published: 2026-03-06T00:00:00Z

Content type: article

Language: en

Sources: [OpenAI News](<https://devfeed.tech/sources/openai-news.md>)

Topics: [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [audio](<https://devfeed.tech/tags/audio.md>), [llms](<https://devfeed.tech/tags/llms.md>), [openai](<https://devfeed.tech/tags/openai.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [scale](<https://devfeed.tech/tags/scale.md>), [startup](<https://devfeed.tech/tags/startup.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [video](<https://devfeed.tech/tags/video.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

Descript redesigned its video-translation pipeline with OpenAI reasoning models to generate dubbed content that preserves meaning while fitting the original timing. The company reports higher dubbed-video exports and improved duration adherence after rollout.

### Source excerpt

Using OpenAI reasoning models, Descript unlocked automatic localization of large content libraries without losing timing or meaning.

## Auto-generating Synced Diagram Overlays for Technical Videos

DevFeed: [Auto-generating Synced Diagram Overlays for Technical Videos](<https://devfeed.tech/articles/auto-generating-synced-diagram-overlays-for-technical-videos-39644.md>)

Original publisher: [Read original article](<https://www.gauravsarma.com/posts/2026-02-24_auto-generating-synced-diagram-overlays>)

Published: 2026-02-24T00:00:00Z

Content type: tutorial

Language: en

Sources: [Gaurav Sarma's Blog](<https://devfeed.tech/sources/gaurav-sarma-s-blog.md>)

Topics: [Development](<https://devfeed.tech/topics/development.md>), [FFmpeg (Fast Forward Moving Picture Experts Group)](<https://devfeed.tech/topics/ffmpeg.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Python](<https://devfeed.tech/topics/python.md>), [Claude](<https://devfeed.tech/topics/claude.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [claude](<https://devfeed.tech/tags/claude.md>), [code](<https://devfeed.tech/tags/code.md>), [ffmpeg](<https://devfeed.tech/tags/ffmpeg.md>), [pipeline](<https://devfeed.tech/tags/pipeline.md>), [python](<https://devfeed.tech/tags/python.md>), [sync](<https://devfeed.tech/tags/sync.md>), [technical](<https://devfeed.tech/tags/technical.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

This article describes technify-motions, a local Python pipeline that adds animated diagrams, flowcharts, summaries, and code snippets to technical videos in sync with the transcript. It covers audio extraction with FFmpeg, local transcription with faster-whisper, and scene classification using Claude.

### Source excerpt

. [Auto-generating Synced Diagram Overlays](auto-generating-synced-diagram-overlays-cover...

## HarborFM - Self-Hosted Podcast Creator

DevFeed: [HarborFM - Self-Hosted Podcast Creator](<https://devfeed.tech/articles/harborfm-self-hosted-podcast-creator-10731.md>)

Original publisher: [Read original article](<https://noted.lol/harborfm/>)

Author: Logan Rickert

Published: 2026-02-20T18:37:34Z

Content type: article

Language: en

Sources: [Noted](<https://devfeed.tech/sources/noted.md>)

Topics: [Open Source](<https://devfeed.tech/topics/open-source.md>), [App](<https://devfeed.tech/topics/app.md>), [RSS Feed](<https://devfeed.tech/topics/rss-feed.md>), [PWA](<https://devfeed.tech/topics/pwa.md>), [WebRTC](<https://devfeed.tech/topics/webrtc.md>), [asr](<https://devfeed.tech/topics/asr.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>)

Tags: [analytics](<https://devfeed.tech/tags/analytics.md>), [asr](<https://devfeed.tech/tags/asr.md>), [audio](<https://devfeed.tech/tags/audio.md>), [collaboration](<https://devfeed.tech/tags/collaboration.md>), [open](<https://devfeed.tech/tags/open.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [podcast](<https://devfeed.tech/tags/podcast.md>), [rss](<https://devfeed.tech/tags/rss.md>), [self-hosted](<https://devfeed.tech/tags/self-hosted.md>), [self-hosted-media-streaming-audio-streaming](<https://devfeed.tech/tags/self-hosted-media-streaming-audio-streaming.md>), [transcripts](<https://devfeed.tech/tags/transcripts.md>), [vision](<https://devfeed.tech/tags/vision.md>), [webrtc](<https://devfeed.tech/tags/webrtc.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

HarborFM is presented as a free, open-source, self-hosted podcast creation tool. It lets users assemble episodes from reusable audio segments, publish per-show RSS feeds, record remote guests through WebRTC, collaborate on episodes, manage private feeds, and view analytics. It also supports podcast chapters, Whisper-based transcription, and AI summaries.

### Source excerpt

Take back your podcast data! HarborFM is a free and open source platform to create and host your podcasts.

## Open ASR Leaderboard: Trends and Insights with New Multilingual & Long-Form Tracks

DevFeed: [Open ASR Leaderboard: Trends and Insights with New Multilingual & Long-Form Tracks](<https://devfeed.tech/articles/open-asr-leaderboard-trends-and-insights-with-new-multilingual-long-form-tracks-7409.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/open-asr-leaderboard>)

Author: Eric Bezzam; Steven Zheng; Eustache Le Bihan; Vaibhav Srivastav

Published: 2025-11-21T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [asr](<https://devfeed.tech/topics/asr.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Language models](<https://devfeed.tech/topics/language-models.md>), [Fine-tuning](<https://devfeed.tech/topics/fine-tuning.md>), [multimodal](<https://devfeed.tech/topics/multimodal.md>)

Tags: [asr](<https://devfeed.tech/tags/asr.md>), [audio](<https://devfeed.tech/tags/audio.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [datasets](<https://devfeed.tech/tags/datasets.md>), [fine-tuning](<https://devfeed.tech/tags/fine-tuning.md>), [ibm](<https://devfeed.tech/tags/ibm.md>), [inference](<https://devfeed.tech/tags/inference.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [leaderboard](<https://devfeed.tech/tags/leaderboard.md>), [microsoft](<https://devfeed.tech/tags/microsoft.md>), [multimodal](<https://devfeed.tech/tags/multimodal.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [qwen](<https://devfeed.tech/tags/qwen.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [speech](<https://devfeed.tech/tags/speech.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [trends](<https://devfeed.tech/tags/trends.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

The Open ASR Leaderboard expands its evaluation with multilingual and long-form transcription tracks. The article highlights accuracy advantages from combining Conformer encoders with LLM decoders, throughput advantages from CTC and TDT decoders, Whisper as a multilingual baseline, and the effects of fine-tuning on specialized performance.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Blazingly fast whisper transcriptions with Inference Endpoints

DevFeed: [Blazingly fast whisper transcriptions with Inference Endpoints](<https://devfeed.tech/articles/blazingly-fast-whisper-transcriptions-with-inference-endpoints-7192.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/fast-whisper-endpoints>)

Author: Morgan Funtowicz; Freddy Boulton; Steven Zheng; Vaibhav Srivastav; Erik Kaunismäki; Michelle Habonneau

Published: 2025-05-13T00:00:00Z

Content type: release

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [inference-endpoints](<https://devfeed.tech/topics/inference-endpoints.md>), [AI, ML & Data Engineering](<https://devfeed.tech/topics/ai-ml-data-engineering.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [audio](<https://devfeed.tech/tags/audio.md>), [cloud](<https://devfeed.tech/tags/cloud.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-endpoints](<https://devfeed.tech/tags/inference-endpoints.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [vllm](<https://devfeed.tech/tags/vllm.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

Hugging Face introduces an optimized Whisper inference endpoint powered by vLLM. It targets newer NVIDIA GPUs and combines PyTorch compilation, CUDA graphs, and float8 KV-cache quantization to improve transcription inference speed and memory efficiency.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Introduction to ggml

DevFeed: [Introduction to ggml](<https://devfeed.tech/articles/introduction-to-ggml-7294.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/introduction-to-ggml>)

Author: Xuan-Son Nguyen; Georgi Gerganov; slaren

Published: 2024-08-13T00:00:00Z

Content type: tutorial

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [ggml](<https://devfeed.tech/topics/ggml.md>), [Programming](<https://devfeed.tech/topics/programming.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Compression](<https://devfeed.tech/topics/compression.md>), [cpu](<https://devfeed.tech/topics/cpu.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [CUDA](<https://devfeed.tech/topics/cuda.md>), [Inference](<https://devfeed.tech/topics/inference.md>)

Tags: [community](<https://devfeed.tech/tags/community.md>), [compression](<https://devfeed.tech/tags/compression.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [ggml](<https://devfeed.tech/tags/ggml.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [guide](<https://devfeed.tech/tags/guide.md>), [llama-cpp](<https://devfeed.tech/tags/llama-cpp.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [programming](<https://devfeed.tech/tags/programming.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

An introductory developer tutorial on ggml, a low-level library for efficient tensor computation. It explains ggml's minimalism, compilation requirements, small binary size, hardware compatibility, quantized tensors, memory efficiency, limitations, and fundamental concepts, including how to compile it on Ubuntu.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## Powerful ASR + diarization + speculative decoding with Hugging Face Inference Endpoints

DevFeed: [Powerful ASR + diarization + speculative decoding with Hugging Face Inference Endpoints](<https://devfeed.tech/articles/powerful-asr-diarization-speculative-decoding-with-hugging-face-inference-endpoints-7106.md>)

Original publisher: [Read original article](<https://huggingface.co/blog/asr-diarization>)

Author: Sergei Petrov; Vaibhav Srivastav; Pedro Cuenca; Philipp Schmid

Published: 2024-05-01T00:00:00Z

Content type: article

Language: en

Sources: [Hugging Face - Blog](<https://devfeed.tech/sources/hugging-face-blog.md>)

Topics: [asr](<https://devfeed.tech/topics/asr.md>), [inference-endpoints](<https://devfeed.tech/topics/inference-endpoints.md>), [hugging face](<https://devfeed.tech/topics/hugging-face.md>), [Inference](<https://devfeed.tech/topics/inference.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [PyTorch](<https://devfeed.tech/topics/pytorch.md>)

Tags: [asr](<https://devfeed.tech/tags/asr.md>), [audio](<https://devfeed.tech/tags/audio.md>), [flash-attention-2](<https://devfeed.tech/tags/flash-attention-2.md>), [hugging-face](<https://devfeed.tech/tags/hugging-face.md>), [inference](<https://devfeed.tech/tags/inference.md>), [inference-endpoints](<https://devfeed.tech/tags/inference-endpoints.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [pytorch](<https://devfeed.tech/tags/pytorch.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

This article explains how to build a custom inference handler for Automatic Speech Recognition, speaker diarization, and speculative decoding on Hugging Face Inference Endpoints. It covers modular pipeline design, repository files, Pyannote-based diarization, PyTorch SDPA with Flash Attention 2, and constraints on speculative decoding such as batch size one and compatible decoder architectures.

### Source excerpt

We're on a journey to advance and democratize artificial intelligence through open source and open science.

## How to build and authenticate an AI API using Modal, Neon, and Unkey

DevFeed: [How to build and authenticate an AI API using Modal, Neon, and Unkey](<https://devfeed.tech/articles/how-to-build-and-authenticate-an-ai-api-using-modal-neon-and-unkey-5378.md>)

Original publisher: [Read original article](<https://neon.com/blog/how-to-build-and-authenticate-an-ai-api-using-modal-neon-and-unkey>)

Author: Dom Eccleston

Published: 2024-02-14T11:55:37Z

Content type: tutorial

Language: en

Sources: [Blog -- Neon Docs](<https://devfeed.tech/sources/blog-neon-docs.md>)

Topics: [API keys](<https://devfeed.tech/topics/api-keys.md>)

Tags: [ai-api](<https://devfeed.tech/tags/ai-api.md>), [api-keys](<https://devfeed.tech/tags/api-keys.md>), [community](<https://devfeed.tech/tags/community.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [openai](<https://devfeed.tech/tags/openai.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [python](<https://devfeed.tech/tags/python.md>), [security](<https://devfeed.tech/tags/security.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

A tutorial for building and authenticating an AI transcription and summarization API with Modal, Neon, and Unkey.

### Source excerpt

As a developer building a product, you might want to open up access to your API. But this requires you to solve a few problems: All of this takes work and take time away from actually building your product. That's where Unkey comes in. Unkey provides API keys a service so that yo...

## What's new in Svelte: August 2023

DevFeed: [What's new in Svelte: August 2023](<https://devfeed.tech/articles/what-s-new-in-svelte-august-2023-3064.md>)

Original publisher: [Read original article](<https://svelte.dev/blog/whats-new-in-svelte-august-2023>)

Author: Dani Sandoval

Published: 2023-08-01T00:00:00Z

Content type: release

Language: en

Sources: [Svelte blog](<https://devfeed.tech/sources/svelte-blog.md>)

Topics: [Svelte](<https://devfeed.tech/topics/svelte.md>), [changelog](<https://devfeed.tech/topics/changelog.md>), [API](<https://devfeed.tech/topics/api.md>), [Prettier](<https://devfeed.tech/topics/prettier.md>), [Chrome extension](<https://devfeed.tech/topics/chrome-extension.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [GitLab](<https://devfeed.tech/topics/gitlab.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [api](<https://devfeed.tech/tags/api.md>), [changelog](<https://devfeed.tech/tags/changelog.md>), [chrome-extension](<https://devfeed.tech/tags/chrome-extension.md>), [features](<https://devfeed.tech/tags/features.md>), [github](<https://devfeed.tech/tags/github.md>), [gitlab](<https://devfeed.tech/tags/gitlab.md>), [json](<https://devfeed.tech/tags/json.md>), [openai](<https://devfeed.tech/tags/openai.md>), [svelte](<https://devfeed.tech/tags/svelte.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

This August 2023 update covers new features, bug fixes, and performance updates in Svelte, SvelteKit, and Svelte language tools. It highlights custom element customization, the HEAD server method in API routes, caching of responses with Vary headers, improved preview errors, Prettier v3 support, and workspace trust settings. It also showcases products and side projects built with Svelte.

### Source excerpt

Some sweet new features have dropped in both Svelte and SvelteKit, this month. It's also great to see how many products and side projects have launched using Svelte as their core technology! More on all that down below... What's new in Svelte & Language Tools There's been a bunch of minor bugfixes since the Svelte 4 release. You can find them in the CHANGELOG. The 4.1.0 release added the ability to further customize the custom element class that wraps the underlying Svelte component. Check out the Custom Elements API docs or the PR for more info! In addition to supporting SvelteKit's new HEAD server method, Svelte's language tools now support Prettier v3 (extensions-107.9.0) and workspace trust settings are now used to support all settings in workspace (extensions-107.8.0). What's new in SvelteKit The HEAD server method is now available in API routes (1.22.0, Docs, #9753) Responses with Vary headers are now cached, too (except for Vary: *) (1.22.0, Docs, #9993) There's now a more helpful error for preview if SvelteKit's build output doesn't exist (1.22.2, #10337) For all the patches and performance updates from this month, check out the SvelteKit CHANGELOG. You can also find adapter-specific CHANGELOGs in each of the adapter directories. Community ShowcaseApps & Sites built with Svelte GitLight brings GitHub & GitLab notifications to your desktop Days is paprikka's life in days, inspired by Buster Benson's Life in Weeks Mofi is a content-aware fill and trim for music JSON Bucket stores your JSON data so you can access it anywhere through generated API routes Soggy Planet is an interactive map of Earth where sea levels rise and fall and the lights of civilization shine through the night (Source) PaperClip is a Chrome extension that makes it easy to memorize details from papers in machine learning, computer vision, and natural language processing. Maktaba is a bookmark manager that "you will actually use" Whispering is a Chrome extension that lets you access OpenAI's

## Voice recognition

DevFeed: [Voice recognition](<https://devfeed.tech/articles/voice-recognition-36609.md>)

Original publisher: [Read original article](<http://www.imperialviolet.org/2023/07/29/voice-recognition.html>)

Author: Adam Langley

Published: 2023-07-29T00:00:00Z

Content type: opinion

Language: en

Sources: [ImperialViolet](<https://devfeed.tech/sources/imperialviolet.md>)

Topics: [Whisper](<https://devfeed.tech/topics/whisper.md>), [iOS](<https://devfeed.tech/topics/ios.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>)

Tags: [caveat](<https://devfeed.tech/tags/caveat.md>), [ios](<https://devfeed.tech/tags/ios.md>), [llms](<https://devfeed.tech/tags/llms.md>), [performance](<https://devfeed.tech/tags/performance.md>), [script](<https://devfeed.tech/tags/script.md>), [transcription](<https://devfeed.tech/tags/transcription.md>), [voice](<https://devfeed.tech/tags/voice.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

The author compares iOS 17 voice recognition with earlier results and finds that, although performance improved over iOS 16, it still produces too many errors with technical terms. The article then reports that Whisper solved the practical voice-recognition problem, while noting that it can append fabricated sentences that are removable.

### Source excerpt

Update: Evan let me know that Whisper solved the voice recognition problem. He has a wrapper that records from a microphone and prints the transcription here. Whisper is very impressive and the only caveat is that it sometimes inserts whole fabricated sentences at the end. The words always sort of make sense in context, but there were no sounds that could possibly have caused it. It's always at the very end in my experience, and it's no problem to remove it so, with that noted, you should ignore everything below because Whisper is a better answer. Last week's blog post was rather long, and had a greater than normal number of typos. (Thanks to people who pointed them out. I think I've fixed all the ones that were reported.) This was because I saw in reviews that iOS 17's voice recognition was supposed to be much improved, and I figured that I'd give it a try. I've always found iOS's recognition to be superior to Google Docs and I have an old iPad Pro that's good for betas. iOS's performance remains good and, yes, I think it's better than iOS 16. But it's still hardly at the level of "magic", especially when using technical terms. Here's a paragraph taken directly from the raw output of last week's post (I've highlighted errors with italics): It is integrated into the W3C credential management specification and so it is called via navigator . credentials . create and navigator .credentials. get. This document is about understanding the deeper structures that underpin web orphan rather than being a guy as to its details. So we will leave a great many details to the numerous guides to Web Oran that already exist on the web and instead focus on how structures from UF were carried over into Web orphan and updated. While it's nice that many of the words are there, with that density of errors doing all the corrections means that it's not clearly better than typing things out. However, the world is all aflutter about LLMs these days. Can they help? I wrote a script to chunk

## Ethereum Development Roundup: Metropolis Progress and Side-Project Updates

DevFeed: [Ethereum Development Roundup: Metropolis Progress and Side-Project Updates](<https://devfeed.tech/articles/roundup-round-iii-16807.md>)

Original publisher: [Read original article](<https://blog.ethereum.org/en/2017/05/24/roundup-round-iii>)

Author: Vitalik Buterin

Published: 2017-05-24T17:04:21Z

Content type: news

Language: en

Sources: [Ethereum Foundation Blog](<https://devfeed.tech/sources/ethereum-foundation-blog.md>)

Topics: [Ethereum](<https://devfeed.tech/topics/ethereum.md>), [Metropolis](<https://devfeed.tech/topics/metropolis.md>), [Blockchain](<https://devfeed.tech/topics/blockchain.md>), [C++](<https://devfeed.tech/topics/c-plus-plus.md>), [Python](<https://devfeed.tech/topics/python.md>), [Ethereum Name Service (ENS)](<https://devfeed.tech/topics/ens.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [API](<https://devfeed.tech/topics/api.md>), [Remote Procedure Call (RPC)](<https://devfeed.tech/topics/rpc.md>)

Tags: [api](<https://devfeed.tech/tags/api.md>), [blockchain](<https://devfeed.tech/tags/blockchain.md>), [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [development](<https://devfeed.tech/tags/development.md>), [ethereum](<https://devfeed.tech/tags/ethereum.md>), [metropolis](<https://devfeed.tech/tags/metropolis.md>), [python](<https://devfeed.tech/tags/python.md>), [research-development](<https://devfeed.tech/tags/research-development.md>), [rpc](<https://devfeed.tech/tags/rpc.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

This roundup reports progress on Ethereum's Metropolis roadmap, including implemented EIPs, client testing, and the lack of a finalized release date. It also covers blockchain activity, ENS auctions, Whisper API work, and Swarm improvements.

### Source excerpt

Over the last month and a half we saw vigorous ongoing research and development on all sides of the Ethereum roadmap, and progress is rapidly starting to translate into real results that can be run and verified inside of an Ethereum client. On Metropolis: Agendas for core dev...

## How to build server less applications for Mist

DevFeed: [How to build server less applications for Mist](<https://devfeed.tech/articles/how-to-build-server-less-applications-for-mist-16772.md>)

Original publisher: [Read original article](<https://blog.ethereum.org/en/2016/07/12/build-server-less-applications-mist>)

Author: Alex Van de Sande

Published: 2016-07-12T16:47:52Z

Content type: tutorial

Language: en

Sources: [Ethereum Foundation Blog](<https://devfeed.tech/sources/ethereum-foundation-blog.md>)

Topics: [Ethereum](<https://devfeed.tech/topics/ethereum.md>), [Blockchain](<https://devfeed.tech/topics/blockchain.md>), [Web](<https://devfeed.tech/topics/web.md>), [JavaScript](<https://devfeed.tech/topics/javascript.md>), [HTML](<https://devfeed.tech/topics/html.md>), [P2P](<https://devfeed.tech/topics/p2p.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>), [Server](<https://devfeed.tech/topics/server.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [blockchain](<https://devfeed.tech/tags/blockchain.md>), [ethereum](<https://devfeed.tech/tags/ethereum.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [html](<https://devfeed.tech/tags/html.md>), [javascript](<https://devfeed.tech/tags/javascript.md>), [network](<https://devfeed.tech/tags/network.md>), [research-development](<https://devfeed.tech/tags/research-development.md>), [server](<https://devfeed.tech/tags/server.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

This tutorial explains how to build decentralized applications for Mist using Ethereum. It describes an architecture in which smart contracts handle data logic on the blockchain, Swarm serves static files, Whisper provides realtime communication, and the user's device runs authentication and the application interface.

### Source excerpt

Ethereum is not meant to be a platform to build esoteric smart contract applications that require a STEM degree to understand, but it aims to be one pillar of a different architecture for applications on the world wide web. With this post we will try to elucidate how this can...

## Open Whisper Systems partners with Google on end-to-end encryption for Allo

DevFeed: [Open Whisper Systems partners with Google on end-to-end encryption for Allo](<https://devfeed.tech/articles/open-whisper-systems-partners-with-google-on-end-to-end-encryption-for-allo-1730.md>)

Original publisher: [Read original article](<https://signal.org/blog/allo/>)

Published: 2016-05-18T00:00:00Z

Content type: news

Language: en

Sources: [Signal Blog](<https://devfeed.tech/sources/signal-blog.md>)

Topics: [Cryptography](<https://devfeed.tech/topics/cryptography.md>)

Tags: [communication](<https://devfeed.tech/tags/communication.md>), [encryption](<https://devfeed.tech/tags/encryption.md>), [google](<https://devfeed.tech/tags/google.md>), [integration](<https://devfeed.tech/tags/integration.md>), [messaging](<https://devfeed.tech/tags/messaging.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [partners](<https://devfeed.tech/tags/partners.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

Open Whisper Systems is partnering with Google to integrate Signal Protocol's end-to-end encryption into Allo's incognito mode.

### Source excerpt

At Open Whisper Systems, our goal is to make private communication simple. The foundation of our technology is Signal Protocol, a modern, open source, strong encryption protocol for asynchronous messaging systems. It is built from the ground up to make seamless end-to-end encrypted messaging possible. Read more...

## CollectD - installation and configuration with InfluxDB on Debian/Ubuntu

DevFeed: [CollectD - installation and configuration with InfluxDB on Debian/Ubuntu](<https://devfeed.tech/articles/collectd-installation-and-configuration-with-influxdb-on-debian-ubuntu-27632.md>)

Original publisher: [Read original article](<https://gagor.pro/2016/01/collectd-installation-and-configuration-with-influxdb-on-debianubuntu/>)

Author: Tom

Published: 2016-01-08T00:00:00Z

Content type: tutorial

Language: en

Sources: [Tomasz Gągor](<https://devfeed.tech/sources/tomasz-gagor.md>)

Topics: [configuration](<https://devfeed.tech/topics/configuration.md>), [Debian](<https://devfeed.tech/topics/debian.md>), [Ubuntu](<https://devfeed.tech/topics/ubuntu.md>), [Grafana](<https://devfeed.tech/topics/grafana.md>)

Tags: [collectd](<https://devfeed.tech/tags/collectd.md>), [configuration](<https://devfeed.tech/tags/configuration.md>), [debian](<https://devfeed.tech/tags/debian.md>), [grafana](<https://devfeed.tech/tags/grafana.md>), [influxdb](<https://devfeed.tech/tags/influxdb.md>), [installation](<https://devfeed.tech/tags/installation.md>), [linux](<https://devfeed.tech/tags/linux.md>), [packages](<https://devfeed.tech/tags/packages.md>), [repo](<https://devfeed.tech/tags/repo.md>), [statistics](<https://devfeed.tech/tags/statistics.md>), [ubuntu](<https://devfeed.tech/tags/ubuntu.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

A tutorial on installing and configuring CollectD with InfluxDB on Debian or Ubuntu. It discusses package availability, backports for newer versions, configuration, plugins, and service restarting.

### Source excerpt

I wanted/needed some statistics on few my machines. I saw earlier grafana and was impressed so this was starting point. Then I started reading about graphite, carbon and whisper, and then... I found InfluxDB. Project is young but looks promising1. Installation of collectd is easy on Debian because packages are in default repo. One problem is that packages may be old, ex. on wheezy it version 5.1. But in backports/backports-sloppy2 you may find current 5.5, so enable backports first:

## There's no you in srveillance

DevFeed: [There's no you in srveillance](<https://devfeed.tech/articles/there-s-no-you-in-srveillance-1864.md>)

Original publisher: [Read original article](<https://signal.org/blog/theres-no-you-in-srveillance/>)

Published: 2015-01-25T00:00:00Z

Content type: opinion

Language: en

Sources: [Signal Blog](<https://devfeed.tech/sources/signal-blog.md>)

Topics: [Cryptography](<https://devfeed.tech/topics/cryptography.md>), [Security](<https://devfeed.tech/topics/security.md>), [Mobile Security](<https://devfeed.tech/topics/mobile-security.md>), [Code](<https://devfeed.tech/topics/code.md>), [User Interfaces](<https://devfeed.tech/topics/user-interfaces.md>), [Whisper](<https://devfeed.tech/topics/whisper.md>)

Tags: [code](<https://devfeed.tech/tags/code.md>), [cryptography](<https://devfeed.tech/tags/cryptography.md>), [interfaces](<https://devfeed.tech/tags/interfaces.md>), [mobile-security](<https://devfeed.tech/tags/mobile-security.md>), [security](<https://devfeed.tech/tags/security.md>), [user-interfaces](<https://devfeed.tech/tags/user-interfaces.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

The article recounts an early attempt to communicate privately using a QBasic Caesar cipher and walkie-talkies, then connects that experience to the ongoing difficulties of privacy technology. It praises Open Whisper Systems for developing a fresh approach to challenging mobile security problems and for addressing the poor usability and legacy constraints common in privacy software.

### Source excerpt

Winter Break Of Code Day Thirteen My ten-year-old mind was completely blown when I realized that I could eavesdrop on the walkie-talkie conversations of the other kids in my neighborhood. I rode my bike to the library in stunned silence, found a book about codes and puzzles, and raced home to my computer. I reluctantly transformed QBasic into something other than a conduit for modified games of NIBBLES.BAS and GORILLA.BAS, and wrote a Caesar cipher implementation that worked in both directions. That ended up being the easy part. Read more...

## Open Whisper Systems Alpine Hackathon

DevFeed: [Open Whisper Systems Alpine Hackathon](<https://devfeed.tech/articles/open-whisper-systems-alpine-hackathon-1769.md>)

Original publisher: [Read original article](<https://signal.org/blog/hackathon-zurich/>)

Published: 2013-09-27T00:00:00Z

Content type: article

Language: en

Sources: [Signal Blog](<https://devfeed.tech/sources/signal-blog.md>)

Topics: [Whisper](<https://devfeed.tech/topics/whisper.md>), [systems](<https://devfeed.tech/topics/systems.md>), [GitHub](<https://devfeed.tech/topics/github.md>)

Tags: [contribute](<https://devfeed.tech/tags/contribute.md>), [event](<https://devfeed.tech/tags/event.md>), [free](<https://devfeed.tech/tags/free.md>), [github](<https://devfeed.tech/tags/github.md>), [hackathon](<https://devfeed.tech/tags/hackathon.md>), [open](<https://devfeed.tech/tags/open.md>), [projects](<https://devfeed.tech/tags/projects.md>), [whisper](<https://devfeed.tech/tags/whisper.md>)

### AI overview

An announcement for an informal Open Whisper Systems hackathon in Zurich, Switzerland, held from October 11 to October 13. The event invited contributors to collaborate on Open Whisper Systems-related projects, with GitHub issues suggested as possible starting points.

### Source excerpt

From October 11th to October 13th, we'll be hosting an informal Open Whisper Systems Alpine Hackathon for those in or around Zurich, Switzerland who would like to contribute to Open Whisper Systems-related projects in a collaborative setting with other co-conspirators. Read more...