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Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,091 posts.
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OpenAI models coming to Amazon Bedrock: Interview with OpenAI and AWS CEOs
An interview with OpenAI CEO Sam Altman and AWS CEO Matt Garman about their new partnership, plus my thoughts on OpenAI and Microsoft’s new deal.
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Claude Code – Everything you can configure that the docs don't tell you
Hook fields that rewrite commands mid-flight, persistent agent memory, auto-mode rules in plain English, self-improving dream loops, and every example is copy-paste ready.
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OpenAI’s board, paraphrased: ‘All we need is unimaginable sums of money’
OpenAI is to this decade’s generative-AI revolution what Netscape was to the 1990s’ internet revolution.
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Don’t let an LLM make decisions or execute business logic
Don’t let an LLM make decisions or implement business logic: they suck at that.
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AI is propping up the US economy
Plus how American professors are fighting back against the AI onslaught, a backlash over AI models in Vogue, and more.
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Slop is everywhere for those with eyes to see
How mindless consumption is making our FYPs worse.
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Making MCP cheaper via CLI
I Made MCP 94% Cheaper (And It Only Took One Command)
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Gaussian splatting is pretty cool
SIGGRAPH 2023 just had a paper “ 3D Gaussian Splatting for Real-Time Radiance Field Rendering ” by Kerbl, Kopanas, Leimkühler, Drettakis, and it looks pretty cool! Check out their website, source code repository, data sets and so on (I should note that it is really, really good to see full source and full data sets…
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One AI Tutor Per Child: Personalized learning is finally here
Update (July 17, 2026): It’s three years since I wrote this article. It went viral and has been reshared and discussed. And curiously, AI…
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A Year at Google Brain (2020)
Reflections from my time at Google Brain, and why I left for a PhD.
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Less is more: Recursive reasoning with tiny networks
|| Paper | Code ||
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YC is wrong about LLMs for chip design
LLMs don’t make chips better. Good engineers do.
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Teaching GPT-3 to Identify Nonsense
In Giving GPT-3 a Turing Test, Kevin Lacker found that GPT-3 does well answering simple factual questions like “Who was president of the United States in 1955?”, but also happily answered absurd qu…
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From zero to a RAG system: successes and failures
A few months ago I was tasked with creating an internal tool for the company's engineers: a Chat that used a local LLM. Nothing extraordinary so far…
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It's rude to show AI output to people
Feeding slop is an act of war
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Probably pay attention to tokenizers
Last week I was helping a friend of mine to get one of his new apps off the ground. I can’t speak much about it at the moment, other than like most apps nowadays it has some AI sprinkled over it. Ok, maybe a bit maybe more just a bit – depends on the way you look at it, I suppose. There is a Retrieval-augmented…
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Successful machine learning models: lessons learned at Booking.com
150 successful machine learning models: 6 lessons learned at Booking.com Bernadi et al., KDD’19 Here’s a paper that will reward careful study for many organisations. We’ve previously looked a…
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I built an AI receptionist for a mechanic shop
Learn how I built an ai receptionist for my brother's mechanic shop
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Superhuman: What can AI do in 30 minutes?
AI multiplies your efforts. I found out by how much...
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We’ll call it AI to sell it, machine learning to build it
An AI Public Service Announcement
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ChatGPT, Rot13, and Daniel Kahneman
I thought it would be interesting to see whether ChatGPT could solve some basic ciphers (Caesar, Vignere, etc.). I decided to start at the bottom, with perhaps the easiest possible cipher: rot13. I asked it to decode the rot-13 encoding of “Why did the chicken cross the road”: So the first thing to note here is that…
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Honda: 2 years of ml vs 1 month of prompting - heres what we learned
Recalls at major automakers cost hundreds of millions of dollars a year. It’s a huge issue. To mitigate it, our company created an analytics department solely focused on categorizing warranty claims into actionable problems.
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YOLO: Real-Time Object Detection
You only look once (YOLO) is a state-of-the-art, real-time object detection system. On a Pascal Titan X it processes images at 30 FPS and has a mAP of 57.9% on COCO test-dev.
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Anthropic's model naming, extrapolated
With the release of Claude Fable, it is clear that Anthropic is progressing from poems to enterprise-scale narrative objects.
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