After months of coding with LLMs, I'm going back to using my brain (🔥 Score: 157+ in 2 hours)
Link: https://readhacker.news/s/6uzNn
Comments: https://readhacker.news/c/6uzNn
Link: https://readhacker.news/s/6uzNn
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Albertofortin
After months of coding with LLMs, I'm going back to using my brain • albertofortin.com
I've been building MVPs and SaaS products for 15 years. Let's work together on your next project.
A $130M company faked trials instead of running our free OSS (🔥 Score: 183+ in 46 minutes)
Link: https://readhacker.news/s/6uA2E
Comments: https://readhacker.news/c/6uA2E
Link: https://readhacker.news/s/6uA2E
Comments: https://readhacker.news/c/6uA2E
Virtualize
Ground control to Major Trial
When a $130M aerospace company chooses to endlessly abuse free trials instead of typing git pull, you start to question gravity, or at least common sense.
Tek – A music making program for 24-bit Unicode terminals (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6uydd
Comments: https://readhacker.news/c/6uydd
Link: https://readhacker.news/s/6uydd
Comments: https://readhacker.news/c/6uydd
Codeberg.org
tek
🦀 a colorful music making program for your linux terminal 🦀
Material 3 Expressive (❄️ Score: 156+ in 2 days)
Link: https://readhacker.news/s/6uqLa
Comments: https://readhacker.news/c/6uqLa
Link: https://readhacker.news/s/6uqLa
Comments: https://readhacker.news/c/6uqLa
Google Design
Expressive Design: Google's UX Research - Google Design
Google's research reveals how expressive design improves UX, usability, and evokes positive emotions in users
Sci-Net (🔥 Score: 153+ in 2 hours)
Link: https://readhacker.news/s/6uA6T
Comments: https://readhacker.news/c/6uA6T
Link: https://readhacker.news/s/6uA6T
Comments: https://readhacker.news/c/6uA6T
The first year of free-threaded Python (Score: 150+ in 6 hours)
Link: https://readhacker.news/s/6uzHP
Comments: https://readhacker.news/c/6uzHP
Link: https://readhacker.news/s/6uzHP
Comments: https://readhacker.news/c/6uzHP
labs.quansight.org
The first year of free-threaded Python
A recap of the first year of work on enabling support for the free-threaded build of CPython in community packages.
A Research Preview of Codex (🔥 Score: 159+ in 1 hour)
Link: https://readhacker.news/s/6uADB
Comments: https://readhacker.news/c/6uADB
Link: https://readhacker.news/s/6uADB
Comments: https://readhacker.news/c/6uADB
Openai
Introducing Codex
Introducing Codex: a cloud-based software engineering agent that can work on many tasks in parallel, powered by codex-1. With Codex, developers can simultaneously deploy multiple agents to independently handle coding tasks such as writing features, answering…
The Awful German Language (1880) (Score: 151+ in 13 hours)
Link: https://readhacker.news/s/6uzbP
Comments: https://readhacker.news/c/6uzbP
Link: https://readhacker.news/s/6uzbP
Comments: https://readhacker.news/c/6uzbP
What were the MS-DOS programs that the moricons.dll icons were intended for? (❄️ Score: 152+ in 3 days)
Link: https://readhacker.news/s/6upzs
Comments: https://readhacker.news/c/6upzs
Link: https://readhacker.news/s/6upzs
Comments: https://readhacker.news/c/6upzs
The Old New Thing
What were the MS-DOS programs that the moricons.dll icons were intended for? - The Old New Thing
Tallying them up.
Ollama violating llama.cpp license for over a year (Score: 152+ in 7 hours)
Link: https://readhacker.news/s/6uzP7
Comments: https://readhacker.news/c/6uzP7
Link: https://readhacker.news/s/6uzP7
Comments: https://readhacker.news/c/6uzP7
GitHub
ollama doesn't distribute notice licenses in its release artifacts · Issue #3185 · ollama/ollama
What is the issue? ollama uses projects like llama.cpp as a statically linked dependency. The terms of the MIT license require that it distribute the copyright notice in both source and binary form...
Windsurf SWE-1: Our First Frontier Models (Score: 151+ in 23 hours)
Link: https://readhacker.news/s/6uxZt
Comments: https://readhacker.news/c/6uxZt
Link: https://readhacker.news/s/6uxZt
Comments: https://readhacker.news/c/6uxZt
Windsurf
SWE-1: Our First Frontier Models
Introducing our first Frontier Models!
Show HN: Visual flow-based programming for Erlang, inspired by Node-RED (Score: 153+ in 4 hours)
Link: https://readhacker.news/s/6uABz
Comments: https://readhacker.news/c/6uABz
Hi There,
Erlang-RED has been my project for the last couple of months and I would love to get some feedback from the HN community.
The idea is to take advantage of Erlangs message passing and low overhead processes to have true concurrency in Node-RED flows. Plus also to bring low-code visual flow-based programming to Erlang.
Link: https://readhacker.news/s/6uABz
Comments: https://readhacker.news/c/6uABz
Hi There,
Erlang-RED has been my project for the last couple of months and I would love to get some feedback from the HN community.
The idea is to take advantage of Erlangs message passing and low overhead processes to have true concurrency in Node-RED flows. Plus also to bring low-code visual flow-based programming to Erlang.
GitHub
GitHub - gorenje/erlang-red: Visual low-code flow-based programming environment for Erlang, inspired by Node-RED.
Visual low-code flow-based programming environment for Erlang, inspired by Node-RED. - gorenje/erlang-red
MIT asks arXiv to take down preprint of paper on AI and scientific discovery (Score: 153+ in 6 hours)
Link: https://readhacker.news/s/6uAF4
Comments: https://readhacker.news/c/6uAF4
Link: https://readhacker.news/s/6uAF4
Comments: https://readhacker.news/c/6uAF4
Thoughts on thinking (🔥 Score: 158+ in 2 hours)
Link: https://readhacker.news/s/6uBsd
Comments: https://readhacker.news/c/6uBsd
Link: https://readhacker.news/s/6uBsd
Comments: https://readhacker.news/c/6uBsd
Dustin Curtis on Svbtle
Thoughts on thinking
I have been stuck. Every time I sit down to write a blog post, code a feature, or start a project, I come to the same realization: in the context of AI, what I’m doing is a waste of time. It’s horrifying. The fun has been sucked out of the process...
I'm Peter Roberts, immigration attorney, who does work for YC and startups. AMA (Score: 153+ in 7 hours)
Link: https://readhacker.news/c/6uAEf
I'll be here for the next 5-6 hours. As usual, there are countless topics given the rapidly changing immigration landscape and I'll be guided by whatever you're concerned with. Please remember that I can't provide legal advice on specific cases because I won't have access to all the facts. Please stick to a factual discussion in your questions and I'll try to do the same in my answers.
Edit: I am taking a break now and will return later this afternoon/evening to respond to any comments and answer any questions. Thank you everyone for a great and engaged AMA so far.
Link: https://readhacker.news/c/6uAEf
I'll be here for the next 5-6 hours. As usual, there are countless topics given the rapidly changing immigration landscape and I'll be guided by whatever you're concerned with. Please remember that I can't provide legal advice on specific cases because I won't have access to all the facts. Please stick to a factual discussion in your questions and I'll try to do the same in my answers.
Edit: I am taking a break now and will return later this afternoon/evening to respond to any comments and answer any questions. Thank you everyone for a great and engaged AMA so far.
Show HN: KVSplit – Run 2-3x longer contexts on Apple Silicon (🔥 Score: 150+ in 2 hours)
Link: https://readhacker.news/s/6uBAK
Comments: https://readhacker.news/c/6uBAK
I discovered that in LLM inference, keys and values in the KV cache have very different quantization sensitivities. Keys need higher precision than values to maintain quality.
I patched llama.cpp to enable different bit-widths for keys vs. values on Apple Silicon. The results are surprising:
- K8V4 (8-bit keys, 4-bit values): 59% memory reduction with only 0.86% perplexity loss
- K4V8 (4-bit keys, 8-bit values): 59% memory reduction but 6.06% perplexity loss
- The configurations use the same number of bits, but K8V4 is 7× better for quality
This means you can run LLMs with 2-3× longer context on the same Mac. Memory usage scales with sequence length, so savings compound as context grows.
Implementation was straightforward:
1. Added --kvq-key and --kvq-val flags to llama.cpp
2. Applied existing quantization logic separately to K and V tensors
3. Validated with perplexity metrics across context lengths
4. Used Metal for acceleration (with -mlong-calls flag to avoid vectorization issues)
Benchmarked on an M4 MacBook Pro running TinyLlama with 8K context windows. Compatible with Metal/MPS and optimized for Apple Silicon.
GitHub: https://github.com/dipampaul17/KVSplit
Link: https://readhacker.news/s/6uBAK
Comments: https://readhacker.news/c/6uBAK
I discovered that in LLM inference, keys and values in the KV cache have very different quantization sensitivities. Keys need higher precision than values to maintain quality.
I patched llama.cpp to enable different bit-widths for keys vs. values on Apple Silicon. The results are surprising:
- K8V4 (8-bit keys, 4-bit values): 59% memory reduction with only 0.86% perplexity loss
- K4V8 (4-bit keys, 8-bit values): 59% memory reduction but 6.06% perplexity loss
- The configurations use the same number of bits, but K8V4 is 7× better for quality
This means you can run LLMs with 2-3× longer context on the same Mac. Memory usage scales with sequence length, so savings compound as context grows.
Implementation was straightforward:
1. Added --kvq-key and --kvq-val flags to llama.cpp
2. Applied existing quantization logic separately to K and V tensors
3. Validated with perplexity metrics across context lengths
4. Used Metal for acceleration (with -mlong-calls flag to avoid vectorization issues)
Benchmarked on an M4 MacBook Pro running TinyLlama with 8K context windows. Compatible with Metal/MPS and optimized for Apple Silicon.
GitHub: https://github.com/dipampaul17/KVSplit
GitHub
GitHub - dipampaul17/KVSplit: Run larger LLMs with longer contexts on Apple Silicon by using differentiated precision for KV cache…
Run larger LLMs with longer contexts on Apple Silicon by using differentiated precision for KV cache quantization. KVSplit enables 8-bit keys & 4-bit values, reducing memory by 59% with &am...
Moody’s strips U.S. of triple-A credit rating (🔥 Score: 153+ in 2 hours)
Link: https://readhacker.news/s/6uBNR
Comments: https://readhacker.news/c/6uBNR
Link: https://readhacker.news/s/6uBNR
Comments: https://readhacker.news/c/6uBNR
Ft
Moody’s strips US of top-notch triple-A credit rating
Agency warns of strains caused by rising government debt and a widening budget deficit
X X^t can be faster (Score: 150+ in 8 hours)
Link: https://readhacker.news/s/6uANa
Comments: https://readhacker.news/c/6uANa
Link: https://readhacker.news/s/6uANa
Comments: https://readhacker.news/c/6uANa
arXiv.org
$XX^{t}$ Can Be Faster
We present a new algorithm RXTX that computes product of matrix by its transpose $XX^{t}$. RXTX uses $5\%$ less multiplications and additions than State-of-the-Art and achieves accelerations even...
Java at 30: Interview with James Gosling (Score: 150+ in 11 hours)
Link: https://readhacker.news/s/6uAdJ
Comments: https://readhacker.news/c/6uAdJ
Link: https://readhacker.news/s/6uAdJ
Comments: https://readhacker.news/c/6uAdJ
The New Stack
Java at 30: The Genius Behind the Code That Changed Tech
From trash-diving teen to tech pioneer, James Gosling's pragmatic genius shaped three decades of Java and modern computing.
Getting AI to write good SQL (Score: 154+ in 4 hours)
Link: https://readhacker.news/s/6uBLa
Comments: https://readhacker.news/c/6uBLa
Link: https://readhacker.news/s/6uBLa
Comments: https://readhacker.news/c/6uBLa
Google Cloud Blog
Techniques for improving text-to-SQL | Google Cloud Blog
Learn about text-to-SQL techniques like context building and table retrieval, LLM-as-a-judge, and LLM prompting and post-processing.