1591
We should be more tired than the model
Adding deliberate friction back into development
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,091 posts.
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Differentiable programming from scratch
Differentiable programming has become a hot research topic, and not only due to the popularity of machine learning frameworks like TensorFlow, PyTorch, and JAX. Many fields apart from machine learning are finding differentiable programming to be a useful tool for solving optimization problems. In computer graphics…
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A look at Apple's technical approach to AI including core model performance etc.
Apple Intelligence makes a lot of sense when you get out of the AI bubble. Plus, the cool technical details Apple shared about their language models "thinking different."
1595
The hunt for the M1’s neural engine
How can you tell when software uses the Neural Engine in an M1 series Mac? How much power does it use, and what is Espresso? Mysteries unravelled.
1596
Superpowers 6
I'm Jesse. I make stuff. Software, hardware. Very occasionally, trouble.
1597
Fine-tuning an LLM to write docs like it's 1995
In my predictions for 2030 I wrote that tech writers would be using specialized LLMs, running locally on powerful hardware. I …
1598
Building reliable agentic AI systems
AI helping pharmaceutical researchers query decades of information buried in PDF reports
1599
Automating Card Games Using OpenCV and Python
A friend introduced me to the game 24 , a simple game you can play with a deck of playing cards. Over the course of playing the game, I realized that either my friend was really good at this game, or that I wasn't!
1600
A 2030 Self-Driving Car Bet
It’s my honor to announce that John Carmack and I have initiated a friendly bet of $10,000* to the 501(c)(3) charity of the winner’s choice: By January 1st, 2030, completely autonomous self-driving cars meeting SAE J3016 level 5 will be commercially available for passenger
1601
Let's talk about LLMs
Everybody seems to agree we’re in the middle of _something_, though what, exactly, seems to be up for debate. It …
1602
Did Anthropic ask for this?
This past Friday, the US Government issued an export control directive that prohibits Anthropic from giving foreign nationals access to Claude Fable or Claude Mythos, their latest models.
1603
Why LLMs Can't Write Q/Kdb+: Writing Code Right-to-Left
In my previous post I showed how LLMs struggle with coding in q/kdb+; having immediate feedback loops using the q-MCP server does help a…
1604
Taking ML to production with Rust
Hands-on technical leader, Rust expert.
1605
A deep dive into self-improving AI and the Darwin-Gödel Machine
How the Darwin-Gödel Machine rewrites its own code to improve, and whether we can trust it
1606
Satellites Spotting Ships
Benchmarks & Tips for Big Data, Hadoop, AWS, Google Cloud, PostgreSQL, Spark, Python & More...
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Using Tesseract OCR with Python
In this tutorial you will learn how to apply Optical Character Recognition (OCR) to images using PyTesseract, Python, and OpenCV.
1609
Llamafile is the new best way to run a LLM on your own computer
Mozilla’s innovation group and Justine Tunney just released llamafile, and I think it’s now the single best way to get started running Large Language Models (think your own local copy …
1610
Catching up on the weird world of LLMs
I gave a talk on Sunday at North Bay Python where I attempted to summarize the last few years of development in the space of LLMs—Large Language Models, the technology …
1611
Things I learned creating my own Messenger chatbot
The modern messaging tools that chatbots run on offer much more ways to interact compared to what previous incarnations of chatbots had, such as those used on IRC or AIM. Much advise on building chatbots that’s out there quietly assumes that all chatbots are just text-in-text-out, which doesn’t match with the…
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I disagree with Geoff Hinton regarding "glorified autocomplete"
“People say, It’s just glorified autocomplete . . . Now, let’s analyze that. Suppose you want to be really good at predicting the next word. If you want to be really good, you have to understand what’s being said. That’s the only way. So by training something to be really good at predicting the next word, you’re…
1614
LLMs could control their host machines by exploiting inference engines
| Read on LessWrong | Comment on HN | Large language models often take actions running on one computer (via an agentic harness such as Claude Code or Codex), however the LLMs’ responses to prompts are computed on a different computer with GPU access.
1615
LLMs and coding agents are a security nightmare
Things are about to get wild
1616
Google Scholar search: "certainly, here is" -chatgpt -llm
Searching Google Scholar for "certainly, here is" turns up a huge number of academic papers that include parts that were evidently written by ChatGPT - sections that start with "Certainly, …
1617
I wrote a meta mode for ChatGPT
I have developed a way to supercharge ChatGPT. It’s called Nova Mode and it’s an awesome custom instruction that you can paste into your ChatGPT Custom instructions (see screenshot below) in ChatGPT Settings. This modifies how ChatGPT works in all your chats, giving you much more control over how you interact with…
1618
Can GPT optimize my taxes? An experiment in letting the LLM be the UX
TL;DR Yes, albeit with patience.
1619
AI doesn't lighten the burden of mastery
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1620
Gaussian Point Splatting
Joris Rijsdijk, Christoph Peters, Michael Weinmann, Ricardo Marroquim. 2026–07 in ACM Transactions on Graphics (Proc. SIGGRAPH) 45, 4. Official version