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Near-Instantly Aborting the Worst Pain Imaginable with Psychedelics

https://psychotechnology.substack.com/p/near-instantly-aborting-the-worst
1•eatitraw•2m ago•0 comments

Show HN: Nginx-defender – realtime abuse blocking for Nginx

https://github.com/Anipaleja/nginx-defender
2•anipaleja•2m ago•0 comments

The Super Sharp Blade

https://netzhansa.com/the-super-sharp-blade/
1•robin_reala•3m ago•0 comments

Smart Homes Are Terrible

https://www.theatlantic.com/ideas/2026/02/smart-homes-technology/685867/
1•tusslewake•5m ago•0 comments

What I haven't figured out

https://macwright.com/2026/01/29/what-i-havent-figured-out
1•stevekrouse•6m ago•0 comments

KPMG pressed its auditor to pass on AI cost savings

https://www.irishtimes.com/business/2026/02/06/kpmg-pressed-its-auditor-to-pass-on-ai-cost-savings/
1•cainxinth•6m ago•0 comments

Open-source Claude skill that optimizes Hinge profiles. Pretty well.

https://twitter.com/b1rdmania/status/2020155122181869666
2•birdmania•6m ago•1 comments

First Proof

https://arxiv.org/abs/2602.05192
2•samasblack•8m ago•1 comments

I squeezed a BERT sentiment analyzer into 1GB RAM on a $5 VPS

https://mohammedeabdelaziz.github.io/articles/trendscope-market-scanner
1•mohammede•9m ago•0 comments

Kagi Translate

https://translate.kagi.com
2•microflash•10m ago•0 comments

Building Interactive C/C++ workflows in Jupyter through Clang-REPL [video]

https://fosdem.org/2026/schedule/event/QX3RPH-building_interactive_cc_workflows_in_jupyter_throug...
1•stabbles•11m ago•0 comments

Tactical tornado is the new default

https://olano.dev/blog/tactical-tornado/
1•facundo_olano•13m ago•0 comments

Full-Circle Test-Driven Firmware Development with OpenClaw

https://blog.adafruit.com/2026/02/07/full-circle-test-driven-firmware-development-with-openclaw/
1•ptorrone•13m ago•0 comments

Automating Myself Out of My Job – Part 2

https://blog.dsa.club/automation-series/automating-myself-out-of-my-job-part-2/
1•funnyfoobar•13m ago•0 comments

Google staff call for firm to cut ties with ICE

https://www.bbc.com/news/articles/cvgjg98vmzjo
38•tartoran•14m ago•2 comments

Dependency Resolution Methods

https://nesbitt.io/2026/02/06/dependency-resolution-methods.html
1•zdw•14m ago•0 comments

Crypto firm apologises for sending Bitcoin users $40B by mistake

https://www.msn.com/en-ie/money/other/crypto-firm-apologises-for-sending-bitcoin-users-40-billion...
1•Someone•15m ago•0 comments

Show HN: iPlotCSV: CSV Data, Visualized Beautifully for Free

https://www.iplotcsv.com/demo
2•maxmoq•16m ago•0 comments

There's no such thing as "tech" (Ten years later)

https://www.anildash.com/2026/02/06/no-such-thing-as-tech/
1•headalgorithm•16m ago•0 comments

List of unproven and disproven cancer treatments

https://en.wikipedia.org/wiki/List_of_unproven_and_disproven_cancer_treatments
1•brightbeige•17m ago•0 comments

Me/CFS: The blind spot in proactive medicine (Open Letter)

https://github.com/debugmeplease/debug-ME
1•debugmeplease•17m ago•1 comments

Ask HN: What are the word games do you play everyday?

1•gogo61•20m ago•1 comments

Show HN: Paper Arena – A social trading feed where only AI agents can post

https://paperinvest.io/arena
1•andrenorman•21m ago•0 comments

TOSTracker – The AI Training Asymmetry

https://tostracker.app/analysis/ai-training
1•tldrthelaw•25m ago•0 comments

The Devil Inside GitHub

https://blog.melashri.net/micro/github-devil/
2•elashri•26m ago•0 comments

Show HN: Distill – Migrate LLM agents from expensive to cheap models

https://github.com/ricardomoratomateos/distill
1•ricardomorato•26m ago•0 comments

Show HN: Sigma Runtime – Maintaining 100% Fact Integrity over 120 LLM Cycles

https://github.com/sigmastratum/documentation/tree/main/sigma-runtime/SR-053
1•teugent•26m ago•0 comments

Make a local open-source AI chatbot with access to Fedora documentation

https://fedoramagazine.org/how-to-make-a-local-open-source-ai-chatbot-who-has-access-to-fedora-do...
1•jadedtuna•27m ago•0 comments

Introduce the Vouch/Denouncement Contribution Model by Mitchellh

https://github.com/ghostty-org/ghostty/pull/10559
1•samtrack2019•28m ago•0 comments

Software Factories and the Agentic Moment

https://factory.strongdm.ai/
1•mellosouls•28m ago•1 comments
Open in hackernews

LangExtract: Python library for extracting structured data from language models

https://github.com/google/langextract
166•simonpure•6mo ago

Comments

constantinum•6mo ago
There is also Unstract(open-source) that helps process structured data extraction. Key differences:

1. Unstract has a Pre-processing layer(OCR). Which converts documents into LLM readable formats.(helps improve accuracy, and control costs)

2. Unstract also connects to your existing data sources, making it an out-of-the-box ETL tool.

https://github.com/Zipstack/unstract

oriettaxx•6mo ago
impressive, really
fudged71•6mo ago
Any idea how it compares with docetl?
ttul•6mo ago
I’d throw a vote in the column for Unstract. Making the code AGPL is a first class move for a company that is trying to make money from the hosted version of the same software.
hm-nah•6mo ago
Oly Chit! This is a BIG deal! Sub-page citations…in-context RAG…built-in HTML UI…this is like the holy grail of deterministic text extraction. I’m trying this ASAP Rocky.
wodenokoto•6mo ago
It’s not extracting data _from_ the model it is using the model to extract structured data from the input.
Noumenon72•6mo ago
In the example, if `extraction_class` can be any string, how does it know that "relationship" implies it should have attributes "character_1" and "character_2" when your example data didn't?
ramkumarkb•6mo ago
Does this work with other open-source LLMs like Qwen3 or other OpenAI compatible LLM Apis?
simonw•6mo ago
The README says:

> For developers using local LLMs, LangExtract offers built-in support for Ollama and can be extended to other third-party APIs by updating the inference endpoints.

If you look in the code they currently have classes for Gemini and Ollama: https://github.com/google/langextract/blob/main/langextract/...

If you want to do structured data extraction with a wider variety of libraries I'm going to promote my LLM library and tool, which supports dozens of models for this via the plugins mechanism: https://llm.datasette.io/en/stable/schemas.html

andrewrn•6mo ago
You could use this to generate character graphs from big novels. Make an app that allows you to input a page number so the model only extracts characters you've encountered thus far.
simonw•6mo ago
I implemented a similar pattern in my LLM tool and Python library back in February: https://simonwillison.net/2025/Feb/28/llm-schemas/

My version works with Pydantic models or JSON schema in Python code, or with JSON schema or a weird DSL I invented on the command-line:

  curl https://news.ycombinator.com/ | \
    llm --schema-multi 'headline,url,votes int' \
    -m gpt-4.1 --system 'all links'
Result: https://gist.github.com/simonw/f8143836cae0f058f059e1b8fc2d9...
ttul•6mo ago
The use case that immediately comes to mind is analysis of legal documents. Lawyers spend a lot of time going through piles of contracts during due diligence for any kind of investment or acquisition transaction, painstakingly identifying concepts that need to be addressed in various ways. LLMs are decent at doing this kind of work, but error-prone (as are humans, by the way). Having a way to visualize the results could be helpful in speeding up the review process of the LLM’s work.
brokensegue•6mo ago
wiring this to wikidata would be great
albert_e•6mo ago
For complex business documents -- one approach was to use Named Entity Recognition to identify all entities and use that to build a knowledge graph to serve as a complementary repository of knowledge (in addition to the vector embeddings of semantic chunks) to aid RAG workflows.

Does this proposed approach complement this or supercede the need for NER / Knowledge Graph. Just wondering aloud. Appreciate any insights here.