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Article URL: https://github.com/Piergiuseppe/boolean-query-parser

Comments URL: https://news.ycombinator.com/item?id=47049035

Points: 1

# Comments: 1

Article URL: https://headachejournal.onlinelibrary.wiley.com/doi/10.1111/head.70025

Comments URL: https://news.ycombinator.com/item?id=47049033

Points: 1

# Comments: 0

Several weeks ago I built a fully-local voice assistant demo with a FastAPI backend and a simple HTML front-end. All the models (ASR / LLM / TTS) are open weight and running locally, i.e. no data is being sent to the Internet nor any API. It's intended to demonstrate how easy it is to run a fully-local AI setup on affordable commodity hardware, while also demonstrating the uncanny valley and teasing out the ethical considerations of such a setup - it allows you to perform voice cloning.

Link: https://github.com/acatovic/ova

Models used:

ASR: NVIDIA parakeet-tdt-0.6b-v3 600M LLM: Mistral ministral-3 3b 4-bit quantized TTS (Simple): Hexgrad Kokoro 82M TTS (With Voice Cloning): Qwen3-TTS

It implements a classic ASR -> LLM -> TTS architecture:

1. Frontend captures user's audio and sends a blob of bytes to the backend /chat endpoint

2. Backend parses the bytes, extracts sample rate (SR) and channels, then:

2.1. Transcribes the audio to text using an automatic speech recognition (ASR) model

2.2. Sends the transcribed text to the LLM, i.e. "the brain"

2.3. Sends the LLM response to a text-to-speech (TTS) model

2.4. Performs normalization of TTS output, converts it to bytes, and sends the bytes back to frontend

3. The frontend plays the response audio back to the user

I've had a number of people try it out with great success and you can potentially take it any direction, e.g. give it more capabilities so it can offload "hard" tasks to larger models or agents, enable voice streaming, give it skills or knowledge, etc.

Enjoy!

Comments URL: https://news.ycombinator.com/item?id=47049030

Points: 2

# Comments: 0

Article URL: https://github.com/jaxxstorm/sentinel

Comments URL: https://news.ycombinator.com/item?id=47049028

Points: 1

# Comments: 0

Article URL: https://temporal.io/news/temporal-raises-300M-to-make-agentic-ai-real-for-companies

Comments URL: https://news.ycombinator.com/item?id=47049026

Points: 3

# Comments: 0

Article URL: https://makospec.vercel.app/en

Comments URL: https://news.ycombinator.com/item?id=47049011

Points: 1

# Comments: 1

I've spent a lot of time copy-pasting and switching between apps to summarize text, create events, proofread emails, look up addresses — always the same follow-up steps after copying.

So I built Cai. It sits in the menu bar. Press Option+C, it detects what you copied and shows relevant actions. Ships with llama-server (Ministral 3B) so it works out of the box, or connect Ollama/LM Studio if you already use them.

Free and open source. Would love feedback on what content types or actions to add next.

Comments URL: https://news.ycombinator.com/item?id=47048991

Points: 1

# Comments: 0

Hi HN — I built Kremis, an experimental deterministic memory substrate for AI agents.

I was tired of "black-box" memory where you can't trace why an agent "remembers" or "hallucinates" something. Kremis is an attempt to fix this by using a deterministic graph engine instead of probabilistic embeddings for core state.

Key features:

- Zero Hidden State: Every query result is a concrete path in a graph. You can audit exactly why the AI reached a conclusion. - Strict Determinism: Same input leads to the same graph state. No randomness or floating-point drift in the core logic. - ACID Reliable: Built on redb for crash-safe persistent storage.

How to use it: It ships as a Rust library, a CLI/HTTP API, and an MCP Server. You can plug it directly into Claude Desktop or Cursor to give your AI assistants a verifiable memory.

Development was heavily AI-assisted, and I'm sharing it today to get technical feedback from the Rust and AI community on the architecture.

I'd value your thoughts on: 1. Does a deterministic graph feel like a viable path for long-term agent memory? 2. How can I improve the query ergonomics for complex traversals?

Thanks for any feedback!

Comments URL: https://news.ycombinator.com/item?id=47048981

Points: 1

# Comments: 0

3D printing isn't just a hobby for me. I've been using it to make useful tools and accessories around my home for years. Here's how.

The latest funding round was led by Sorenson Capital and brings the total investment to $45 million.

The post VulnCheck Raises $25 Million in Series B Funding to Scale Vulnerability Intelligence appeared first on SecurityWeek.

Eurail has confirmed that the stolen data is up for sale, but it’s still trying to determine how many individuals are impacted.

The post Hackers Offer to Sell Millions of Eurail User Records appeared first on SecurityWeek.

Article URL: https://futuresearch.ai/semantic-deduplication/

Comments URL: https://news.ycombinator.com/item?id=47048374

Points: 2

# Comments: 1

Article URL: https://jack-clark.net/2023/07/18/ai-safety-and-corporate-power-remarks-given-at-the-un-security-council/

Comments URL: https://news.ycombinator.com/item?id=47048361

Points: 1

# Comments: 0

Article URL: https://9to5mac.com/2026/02/17/eu-also-investigating-as-grok-generated-23000-csam-images-in-11-days/

Comments URL: https://news.ycombinator.com/item?id=47048355

Points: 1

# Comments: 0

Article URL: https://julien.danjou.info/blog/open-source-is-getting-used-to-death/

Comments URL: https://news.ycombinator.com/item?id=47048347

Points: 1

# Comments: 0

I've been using Claude Code as my daily driver and had no easy way to track spending over time. The built-in statusline shows session stats, but nothing about historical cost or how close I am to hitting usage limits.

cc-costline replaces Claude Code's statusline with one that shows rolling cost totals, usage limit warnings, and optionally your rank on the ccclub leaderboard — all in a single line:

``` 14.6k ~ $2.42 / 40% by Opus 4.6 | 5h: 45% / 7d: 8% | 30d: $866 ```

What each segment means:

- `14.6k ~ $2.42 / 40% by Opus 4.6` — session tokens, cost, context window usage, model - `5h: 45% / 7d: 8%` — Claude's 5-hour and 7-day usage limits (color-coded: green → orange → red) - `30d: $866` — rolling 30-day total (configurable to 7d or both)

Setup is one command:

``` npm i -g cc-costline && cc-costline install ```

Comments URL: https://news.ycombinator.com/item?id=47048321

Points: 1

# Comments: 0

Article URL: https://github.com/p2r3/convert

Comments URL: https://news.ycombinator.com/item?id=47048309

Points: 1

# Comments: 1

Article URL: https://mautic.org/blog/urgent-call-for-community-support-to-secure-mautics-financial-future/

Comments URL: https://news.ycombinator.com/item?id=47048304

Points: 1

# Comments: 1

Article URL: https://relay.moltic.dev/

Comments URL: https://news.ycombinator.com/item?id=47048302

Points: 2

# Comments: 0