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Top stories from https://news.ycombinator.com (with 100+ score) Contribute to the development here: https://github.com/phil-r/hackernewsbot Also check https://t.me/designer_news Contacts: @philr
The hidden JTAG in a Qualcomm/Snapdragon device’s USB port (Score: 151+ in 12 hours)
Link: https://readhacker.news/s/6wYB6
Comments: https://readhacker.news/c/6wYB6
Melbourne man discovers extensive model train network underneath house (Score: 151+ in 4 hours)
Link: https://readhacker.news/s/6wZug
Comments: https://readhacker.news/c/6wZug
Proton joins suit against Apple for predatory practices (Score: 150+ in 4 hours)
Link: https://readhacker.news/s/6wYvJ
Comments: https://readhacker.news/c/6wYvJ
The New Skill in AI Is Not Prompting, It's Context Engineering (🔥 Score: 158+ in 1 hour)
Link: https://readhacker.news/s/6wZ2P
Comments: https://readhacker.news/c/6wZ2P
New proof dramatically compresses space needed for computation (❄️ Score: 150+ in 3 days)
Link: https://readhacker.news/s/6wPbd
Comments: https://readhacker.news/c/6wPbd
The Plot of the Phantom, a text adventure that took 40 years to finish (❄️ Score: 153+ in 3 days)
Link: https://readhacker.news/s/6wPMT
Comments: https://readhacker.news/c/6wPMT
Error handling in Rust (Score: 150+ in 21 hours)
Link: https://readhacker.news/s/6wVjF
Comments: https://readhacker.news/c/6wVjF
The provenance memory model for C (Score: 150+ in 7 hours)
Link: https://readhacker.news/s/6wWVt
Comments: https://readhacker.news/c/6wWVt
Want to meet people, try charging them for it? (Score: 150+ in 9 hours)
Link: https://readhacker.news/s/6wWy4
Comments: https://readhacker.news/c/6wWy4
Nearly 20% of cancer drugs defective in four African nations (Score: 150+ in 14 hours)
Link: https://readhacker.news/s/6wVLx
Comments: https://readhacker.news/c/6wVLx
LetsEncrypt – Expiration Notification Service Has Ended (Score: 150+ in 8 hours)
Link: https://readhacker.news/s/6wWpi
Comments: https://readhacker.news/c/6wWpi
Event – Fast, In-Process Event Dispatcher (Score: 150+ in 20 hours)
Link: https://readhacker.news/s/6wUzK
Comments: https://readhacker.news/c/6wUzK
Gridfinity: The modular, open-source grid storage system (Score: 150+ in 7 hours)
Link: https://readhacker.news/s/6wWg5
Comments: https://readhacker.news/c/6wWg5
We accidentally solved robotics by watching 1M hours of YouTube (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6wUGd
Comments: https://readhacker.news/c/6wUGd
Touching the back wall of the Apple store (❄️ Score: 151+ in 3 days)
Link: https://readhacker.news/s/6wN3D
Comments: https://readhacker.news/c/6wN3D
Claude Code now supports Hooks (Score: 153+ in 5 hours)
Link: https://readhacker.news/s/6wZv3
Comments: https://readhacker.news/c/6wZv3
Ask HN: What's the 2025 stack for a self-hosted photo library with local AI? (Score: 150+ in 7 hours)
Link: https://readhacker.news/c/6wYxB
First of all, this is purely a personal learning project for me, aiming to combine three of my passions: photography, software engineering, and my family memories. I have a large collection of family photos and want to build an interactive experience to explore them, ala Google or Apple Photo features.
My goal is to create a system with smart search capabilities, and one of the most important requirements is that it must run entirely on my local hardware. Privacy is key, but the main driver is the challenge and joy of building it myself (an obviously learn).
The key features I'm aiming for are:
Automatic identification and tagging of family members (local face recognition).
Generation of descriptive captions for each photo.
Natural language search (e.g., "Show me photos of us at the beach in Luquillo from last summer").
I've already prompted AI tools for a high-level project plan, and they provided a solid blueprint (eg, Ollama with LLaVA, a vector DB like ChromaDB, you know it). Now, I'm highly interested in the real-world human experience. I'm looking for advice, learning stories, and the little details that only come from building something similar.
What tools, models, and best practices would you recommend for a project like this in 2025? Specifically, I'm curious about combining structured metadata (EXIF), face recognition data, and semantic vector search into a single, cohesive application.
Any and all advice would be deeply appreciated. Thanks!
Xfinity using WiFi signals in your house to detect motion (🔥 Score: 152+ in 3 hours)
Link: https://readhacker.news/s/6wYGq
Comments: https://readhacker.news/c/6wYGq
I write type-safe generic data structures in C (Score: 150+ in 4 hours)
Link: https://readhacker.news/s/6wYhP
Comments: https://readhacker.news/c/6wYhP
There Are No New Ideas in AI Only New Datasets (Score: 158+ in 5 hours)
Link: https://readhacker.news/s/6wXPr
Comments: https://readhacker.news/c/6wXPr
Donkey Kong Country 2 and Open Bus (Score: 152+ in 5 hours)
Link: https://readhacker.news/s/6wXTc
Comments: https://readhacker.news/c/6wXTc
Show HN: New Ensō – first public beta (Score: 150+ in 6 hours)
Link: https://readhacker.news/s/6wX82
Comments: https://readhacker.news/c/6wX82
Ensō is a writing tool that helps you enter a state of flow by separating writing from editing and thus making it harder for you to edit yourself - https://enso.sonnet.io/
After 6 years and 2 million words of daily writing I feel like I've learned enough to make Ensō simpler and more accessible.
Related thread: https://news.ycombinator.com/item?id=38025073
Show HN: TokenDagger – A tokenizer faster than OpenAI's Tiktoken (Score: 154+ in 4 hours)
Link: https://readhacker.news/s/6wXkA
Comments: https://readhacker.news/c/6wXkA
TokenDagger is a drop-in replacement for OpenAI’s Tiktoken (the tokenizer behind Llama 3, Mistral, GPT-3.*, etc.). It’s written in C++ 17 with thin Python bindings, keeps the exact same BPE vocab/special-token rules, and focuses on raw speed.
I’m teaching myself LLM internals by re-implementing the stack from first principles. Profiling TikToken’s Python/Rust implementation showed a lot of time was spent doing regex matching. Most of my perf gains come from a) using a faster jit-compiled regex engine; and b) simplifying the algorithm to forego regex matching special tokens at all.
Benchmarking code is included. Notable results show:
- 4x faster code sample tokenization on a single thread.
- 2-3x higher throughput when tested on a 1GB natural language text file.
Revisiting Knuth's “Premature Optimization” Paper (❄️ Score: 150+ in 4 days)
Link: https://readhacker.news/s/6wKMn
Comments: https://readhacker.news/c/6wKMn
Is being bilingual good for your brain? (Score: 150+ in 1 day)
Link: https://readhacker.news/s/6wS8N
Comments: https://readhacker.news/c/6wS8N
Finding a former Australian prime minister’s passport number on Instagram (2020) (Score: 150+ in 15 hours)
Link: https://readhacker.news/s/6wVCm
Comments: https://readhacker.news/c/6wVCm
The Book of Shaders (2015) (❄️ Score: 150+ in 3 days)
Link: https://readhacker.news/s/6wLRQ
Comments: https://readhacker.news/c/6wLRQ
Bought myself an Ampere Altra system (Score: 153+ in 5 hours)
Link: https://readhacker.news/s/6wWnq
Comments: https://readhacker.news/c/6wWnq
Web Embeddable Common Lisp (❄️ Score: 150+ in 4 days)
Link: https://readhacker.news/s/6wHiY
Comments: https://readhacker.news/c/6wHiY
The $25k car is going extinct? (Score: 150+ in 16 hours)
Link: https://readhacker.news/s/6wUFd
Comments: https://readhacker.news/c/6wUFd