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Record-High 89% in U.S. Say Government Corruption Widespread
2026-09-04 @ 22:03:16Points: 153Comments: 93
Actively exploited sandbox RCE in all Chromium versions
2026-09-04 @ 21:52:01Points: 195Comments: 111
Icons as a Service
2026-09-04 @ 21:44:59Points: 17Comments: 0
GPT-6 Astra on OpenRouter
2026-09-04 @ 21:39:19Points: 110Comments: 51
Updates on HEIR, the Homomorphic Encryption Compiler Project
2026-09-04 @ 21:16:16Points: 24Comments: 0
Without new landers or rovers, it's helicopters or bust for NASA's Mars program
2026-09-04 @ 21:06:48Points: 12Comments: 0
Statichost.eu – European static site hosting
2026-09-04 @ 20:34:49Points: 167Comments: 54
How to Create a Tor Exit Node
2026-09-04 @ 20:16:22Points: 38Comments: 18
An open DNS recursive service for free security and high privacy
2026-09-04 @ 20:13:08Points: 62Comments: 13
Can AI design circuit boards yet?
2026-09-04 @ 19:48:29Points: 150Comments: 93
Government Rails Site Hit Hours After CVE Patch
2026-09-04 @ 19:06:39Points: 72Comments: 20
Fermat's Last Theorem in Lean 4
2026-09-04 @ 18:57:32Points: 61Comments: 14
Shutting down our public encrypted DNS
2026-09-04 @ 18:50:28Points: 243Comments: 88
Formalizing Fermat's Last Theorem
2026-09-04 @ 18:42:56Points: 465Comments: 313
The Rust React Compiler is now native in Vite
2026-09-04 @ 17:49:09Points: 110Comments: 22
Show HN: Open-Source eInk Bike Computer
2026-09-04 @ 17:18:08Points: 227Comments: 76
Another tidbit, in the crazy things that AI has done... It has helped create a ANT (common sensor wireless protocol used in workout/biking) implementation for ESP32 by messing around with undocumented registers: https://github.com/RaemondBW/esp32-ant
"Next-token predictor" is the wrong mental model for LLMs
2026-09-04 @ 17:09:24Points: 76Comments: 165
Adult Film Producer Unmasks Prolific 'John DOE' Torrent Pirate as Meta Executive
2026-09-04 @ 16:46:59Points: 332Comments: 206
Project HydraFusion: Frontier quality via multi-model orchestration
2026-09-04 @ 16:24:50Points: 60Comments: 29
deSEC – Free Secure DNS
2026-09-04 @ 15:38:58Points: 110Comments: 40
IBM Bob
2026-09-04 @ 12:50:29Points: 222Comments: 256
SubImage (YC W25) Is Hiring a Founding Engineer in SF
2026-09-04 @ 12:01:07Points: 1
Discovery of a new OpenAI agent message board
2026-09-04 @ 11:54:53Points: 1459Comments: 1172
Solving the Jane Street reverse engineering challenge
2026-09-04 @ 10:17:01Points: 391Comments: 87
Show HN: TERMy – A fast terminal assistant that does not use LLMs
2026-09-04 @ 09:03:00Points: 91Comments: 28
I am excited to share with you TERMy, a terminal assistant built on top of the NPC-Forge framework. Unlike everything else being built today, TERMy does not use embeddings, machine-learning or LLMs. It runs on the CPU (even on a Raspberry Pi Zero) both in the terminal or client-side in a browser tab and responds in milliseconds. It is a cynical but very knowledgeable Linux terminal assistant that translates your natural language into shell commands without relying on a single artificial neuron.
I had a chance to focus for 2 months on my personal projects since early July, during the strange times of AI price hikes and the end of subsidized tokenmaxing. I was curious to see if I could develop from scratch a terminal assistant capable of handling simple natural language requests. I have a bad memory and got used to ask to copilot "activate the virtual environment" or similar trivial operations spending a non negligible sum every month. I started thinking, maybe I can do something to make my workflow more efficient? Do I really need trillions of parameters to accomplish those tasks?
How it Works
When you type a prompt, it goes through a lightweight NLU pipeline written in ~1000 lines of Python that implement the following steps:
1. Strip expletives, interjections, encouraging, discouraging and thanking words (remove noise)
2. Sentiment analysis
3. Exact Match (very fast)
4. Template Match (slower)
5. Probabilistic Match (even slower)
Step 5 relies on:
1. IDF (Inverse Document Frequency) to identify rare words.
2. BOW (Bag Of Words) to accommodate word inversions.
3. IDF weighted Levenshtein to safely handle typos.
Permission gating is hardcoded into the dataset and enforced for all potentially destructive commands, so it's inherently safer than letting an unpredictable LLM run wild on your machine.
- TERMy in operation: https://www.youtube.com/watch?v=qeIp0xePLBg
- Variance and typo tolerance: https://www.youtube.com/watch?v=tQvGDk6fkk0
- Copilot integration: https://www.youtube.com/watch?v=Wzzouhq2a8A
- Advanced features: https://www.youtube.com/watch?v=qeIp0xePLBg
- Source Code: https://github.com/gioblu/NPC-Forge