Luxe Game Engine (Score: 150+ in 13 hours)
Link: https://readhacker.news/s/6w6uG
Comments: https://readhacker.news/c/6w6uG
Link: https://readhacker.news/s/6w6uG
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luxe engine
luxe engine | A lovingly crafted game engine
A lovingly crafted cross platform game engine, try the preview!
The Tech Job Meltdown (Score: 153+ in 4 hours)
Link: https://readhacker.news/s/6w7Vq
Comments: https://readhacker.news/c/6w7Vq
Link: https://readhacker.news/s/6w7Vq
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Professoraxelrod
The Tech Job Meltdown
Half a million layoffs? It's all accounting.
Endometriosis is an interesting disease (Score: 152+ in 11 hours)
Link: https://readhacker.news/s/6w7E7
Comments: https://readhacker.news/c/6w7E7
Link: https://readhacker.news/s/6w7E7
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Owlposting
Endometriosis is an incredibly interesting disease
5k words, 23 minutes reading time
Self-Adapting Language Models (Score: 150+ in 15 hours)
Link: https://readhacker.news/s/6w78E
Comments: https://readhacker.news/c/6w78E
https://jyopari.github.io/posts/seal
Link: https://readhacker.news/s/6w78E
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https://jyopari.github.io/posts/seal
arXiv.org
Self-Adapting Language Models
Large language models (LLMs) are powerful but static; they lack mechanisms to adapt their weights in response to new tasks, knowledge, or examples. We introduce Self-Adapting LLMs (SEAL), a...
Implementing Logic Programming (Score: 150+ in 15 hours)
Link: https://readhacker.news/s/6w7vM
Comments: https://readhacker.news/c/6w7vM
Link: https://readhacker.news/s/6w7vM
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Substack
Implementing Logic Programming
I just think it's neat!
TimeGuessr (❄️ Score: 151+ in 4 days)
Link: https://readhacker.news/s/6vSW9
Comments: https://readhacker.news/c/6vSW9
Link: https://readhacker.news/s/6vSW9
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Peano arithmetic is enough, because Peano arithmetic encodes computation (Score: 151+ in 23 hours)
Link: https://readhacker.news/s/6w6Ey
Comments: https://readhacker.news/c/6w6Ey
Link: https://readhacker.news/s/6w6Ey
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Mathematics Stack Exchange
Can PA prove "each Goodstein sequence can be proven in PA to reach zero"?
This is one of a pair of questions trying to understand this comment on the xkcd forum contest My number is bigger than yours!. For a definition of Goodstein sequences, see this question.
Let $G(n)...
Let $G(n)...
SIMD-friendly algorithms for substring searching (2018) (Score: 150+ in 12 hours)
Link: https://readhacker.news/s/6w7Zb
Comments: https://readhacker.news/c/6w7Zb
Link: https://readhacker.news/s/6w7Zb
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0x80.pl
SIMD-friendly algorithms for substring searching
Launch HN: Chonkie (YC X25) – Open-Source Library for Advanced Chunking (❄️ Score: 150+ in 5 days)
Link: https://readhacker.news/c/6vQEL
Hey HN! We're Shreyash and Bhavnick. We're building Chonkie (https://chonkie.ai), an open-source library for chunking and embedding data.
Python: https://github.com/chonkie-inc/chonkie
TypeScript: https://github.com/chonkie-inc/chonkie-ts
Here's a video showing our code chunker: https://youtu.be/Xclkh6bU1P0.
Bhavnick and I have been building personal projects with LLMs for a few years. For much of this time, we found ourselves writing our own chunking logic to support RAG applications. We often hesitated to use existing libraries because they either had only basic features or felt too bloated (some are 80MB+).
We built Chonkie to be lightweight, fast, extensible, and easy. The space is evolving rapidly, and we wanted Chonkie to be able to quickly support the newest strategies. We currently support: Token Chunking, Sentence Chunking, Recursive Chunking, Semantic Chunking, plus:
- Semantic Double Pass Chunking: Chunks text semantically first, then merges closely related chunks.
- Code Chunking: Chunks code files by creating an AST and finding ideal split points.
- Late Chunking: Based on the paper (https://arxiv.org/abs/2409.04701), where chunk embeddings are derived from embedding a longer document.
- Slumber Chunking: Based on the "Lumber Chunking" paper (https://arxiv.org/abs/2406.17526). It uses recursive chunking, then an LLM verifies split points, aiming for high-quality chunks with reduced token usage and LLM costs.
You can see how Chonkie compares to LangChain and LlamaIndex in our benchmarks: https://github.com/chonkie-inc/chonkie/blob/main/BENCHMARKS....
Some technical details about the Chonkie package: - ~15MB default install vs. ~80-170MB for some alternatives. - Up to 33x faster token chunking compared to LangChain and LlamaIndex in our tests. - Works with major tokenizers (transformers, tokenizers, tiktoken). - Zero external dependencies for basic functionality. - Implements aggressive caching and precomputation. - Uses running mean pooling for efficient semantic chunking. - Modular dependency system (install only what you need).
In addition to chunking, Chonkie also provides an easy way to create embeddings. For supported providers (SentenceTransformer, Model2Vec, OpenAI), you just specify the model name as a string. You can also create custom embedding handlers for other providers.
RAG is still the most common use case currently. However, Chonkie makes chunks that are optimized for creating high quality embeddings and vector retrieval, so it is not really tied to the "generation" part of RAG. In fact, We're seeing more and more people use Chonkie for implementing semantic search and/or setting context for agents.
We are currently focused on building integrations to simplify the retrieval process. We've created "handshakes" – thin functions that interact with vector DBs like pgVector, Chroma, TurboPuffer, and Qdrant, allowing you to interact with storage easily. If there's an integration you'd like to see (vector DB or otherwise), please let us know.
We also offer hosted and on-premise versions with OCR, extra metadata, all embedding providers, and managed vector databases for teams that want a fully managed pipeline. If you're interested, reach out at [email protected] or book a demo: https://cal.com/shreyashn/chonkie-demo.
We're eager to hear your feedback and comments! Thanks!
Link: https://readhacker.news/c/6vQEL
Hey HN! We're Shreyash and Bhavnick. We're building Chonkie (https://chonkie.ai), an open-source library for chunking and embedding data.
Python: https://github.com/chonkie-inc/chonkie
TypeScript: https://github.com/chonkie-inc/chonkie-ts
Here's a video showing our code chunker: https://youtu.be/Xclkh6bU1P0.
Bhavnick and I have been building personal projects with LLMs for a few years. For much of this time, we found ourselves writing our own chunking logic to support RAG applications. We often hesitated to use existing libraries because they either had only basic features or felt too bloated (some are 80MB+).
We built Chonkie to be lightweight, fast, extensible, and easy. The space is evolving rapidly, and we wanted Chonkie to be able to quickly support the newest strategies. We currently support: Token Chunking, Sentence Chunking, Recursive Chunking, Semantic Chunking, plus:
- Semantic Double Pass Chunking: Chunks text semantically first, then merges closely related chunks.
- Code Chunking: Chunks code files by creating an AST and finding ideal split points.
- Late Chunking: Based on the paper (https://arxiv.org/abs/2409.04701), where chunk embeddings are derived from embedding a longer document.
- Slumber Chunking: Based on the "Lumber Chunking" paper (https://arxiv.org/abs/2406.17526). It uses recursive chunking, then an LLM verifies split points, aiming for high-quality chunks with reduced token usage and LLM costs.
You can see how Chonkie compares to LangChain and LlamaIndex in our benchmarks: https://github.com/chonkie-inc/chonkie/blob/main/BENCHMARKS....
Some technical details about the Chonkie package: - ~15MB default install vs. ~80-170MB for some alternatives. - Up to 33x faster token chunking compared to LangChain and LlamaIndex in our tests. - Works with major tokenizers (transformers, tokenizers, tiktoken). - Zero external dependencies for basic functionality. - Implements aggressive caching and precomputation. - Uses running mean pooling for efficient semantic chunking. - Modular dependency system (install only what you need).
In addition to chunking, Chonkie also provides an easy way to create embeddings. For supported providers (SentenceTransformer, Model2Vec, OpenAI), you just specify the model name as a string. You can also create custom embedding handlers for other providers.
RAG is still the most common use case currently. However, Chonkie makes chunks that are optimized for creating high quality embeddings and vector retrieval, so it is not really tied to the "generation" part of RAG. In fact, We're seeing more and more people use Chonkie for implementing semantic search and/or setting context for agents.
We are currently focused on building integrations to simplify the retrieval process. We've created "handshakes" – thin functions that interact with vector DBs like pgVector, Chroma, TurboPuffer, and Qdrant, allowing you to interact with storage easily. If there's an integration you'd like to see (vector DB or otherwise), please let us know.
We also offer hosted and on-premise versions with OCR, extra metadata, all embedding providers, and managed vector databases for teams that want a fully managed pipeline. If you're interested, reach out at [email protected] or book a demo: https://cal.com/shreyashn/chonkie-demo.
We're eager to hear your feedback and comments! Thanks!
The Army’s Newest Recruits: Tech Execs From Meta, OpenAI and More (Score: 151+ in 1 day)
Link: https://readhacker.news/s/6w6fM
Comments: https://readhacker.news/c/6w6fM
Link: https://readhacker.news/s/6w6fM
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WSJ
The Army’s Newest Recruits: Tech Execs From Meta, OpenAI and More
The executives are joining a new innovation corps in the Army Reserve.
Google Cloud Incident Report – 2025-06-13 (Score: 150+ in 11 hours)
Link: https://readhacker.news/s/6w8bd
Comments: https://readhacker.news/c/6w8bd
Link: https://readhacker.news/s/6w8bd
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I have reimplemented Stable Diffusion 3.5 from scratch in pure PyTorch (🔥 Score: 156+ in 3 hours)
Link: https://readhacker.news/s/6w8Mn
Comments: https://readhacker.news/c/6w8Mn
Link: https://readhacker.news/s/6w8Mn
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GitHub
GitHub - yousef-rafat/miniDiffusion: A reimplementation of Stable Diffusion 3.5 in pure PyTorch
A reimplementation of Stable Diffusion 3.5 in pure PyTorch - yousef-rafat/miniDiffusion
Last fifty years of integer linear programming: Recent practical advances (Score: 150+ in 14 hours)
Link: https://readhacker.news/s/6w8bh
Comments: https://readhacker.news/c/6w8bh
Link: https://readhacker.news/s/6w8bh
Comments: https://readhacker.news/c/6w8bh
inria.hal.science
Last fifty years of integer linear programming: a focus on recent practical advances
<div><p>Mixed-integer linear programming (MILP) has become a cornerstone of operations research. This is driven by the enhanced efficiency of modern solvers, which can today find globally optimal solutions within seconds for problems that were out of reach…
Liquid Glass – WWDC25 [video] (❄️ Score: 150+ in 4 days)
Link: https://readhacker.news/s/6vTKE
Comments: https://readhacker.news/c/6vTKE
Link: https://readhacker.news/s/6vTKE
Comments: https://readhacker.news/c/6vTKE
Apple Developer
Meet Liquid Glass - WWDC25 - Videos - Apple Developer
Liquid Glass unifies Apple platform design language while providing a more dynamic and expressive user experience. Get to know the design...
Waymo rides cost more than Uber or Lyft and people are paying anyway (❄️ Score: 152+ in 2 days)
Link: https://readhacker.news/s/6w2VV
Comments: https://readhacker.news/c/6w2VV
Link: https://readhacker.news/s/6w2VV
Comments: https://readhacker.news/c/6w2VV
TechCrunch
Exclusive: Waymo rides cost more than Uber, Lyft — and people are paying anyway | TechCrunch
A new analysis done by ride-hailing aggregator Obi shows Waymos cost more especially on shorter trips. They also have longer wait times.
Student discovers fungus predicted by Albert Hoffman (❄️ Score: 150+ in 3 days)
Link: https://readhacker.news/s/6vW8D
Comments: https://readhacker.news/c/6vW8D
Link: https://readhacker.news/s/6vW8D
Comments: https://readhacker.news/c/6vW8D
wvutoday.wvu.edu
WVU student discovers long-awaited mystery fungus sought by LSD’s inventor
Making a discovery with the potential for innovative applications in pharmaceutical development, a West Virginia University microbiology student has found a long sought-after fungus that produces effects similar to the semisynthetic drug LSD, which is used…
Solar Orbiter gets world-first views of the Sun's poles (❄️ Score: 154+ in 2 days)
Link: https://readhacker.news/s/6vZd7
Comments: https://readhacker.news/c/6vZd7
Link: https://readhacker.news/s/6vZd7
Comments: https://readhacker.news/c/6vZd7
ESA
Solar Orbiter gets world-first views of the Sun’s poles
Thanks to its newly tilted orbit around the Sun, the European Space Agency-led Solar Orbiter spacecraft is the first to image the Sun’s poles from outside the ecliptic plane. Solar Orbiter’s unique viewing angle will change our understanding of the Sun’s…
Seven replies to the viral Apple reasoning paper and why they fall short (🔥 Score: 155+ in 3 hours)
Link: https://readhacker.news/s/6w9pM
Comments: https://readhacker.news/c/6w9pM
Link: https://readhacker.news/s/6w9pM
Comments: https://readhacker.news/c/6w9pM
Substack
Seven replies to the viral Apple reasoning paper – and why they fall short
Also: another paper that seals the deal
Infinite Grid of Resistors (Score: 151+ in 10 hours)
Link: https://readhacker.news/s/6w9DF
Comments: https://readhacker.news/c/6w9DF
Link: https://readhacker.news/s/6w9DF
Comments: https://readhacker.news/c/6w9DF
The Many Sides of Erik Satie (❄️ Score: 150+ in 6 days)
Link: https://readhacker.news/s/6vMMT
Comments: https://readhacker.news/c/6vMMT
Link: https://readhacker.news/s/6vMMT
Comments: https://readhacker.news/c/6vMMT
The MIT Press Reader
The Many Sides of Erik Satie
“The Satie life contains so much murk; his music sparkles with riverine clarity.”