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Why don't machine learning research agents overfit?
New research indicates that AI agents learn compressible models of data, which don’t have enough space to enable memorization.
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 6,335 posts.
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What reversing, modernising old games tells us about the economic impact of AI
Some observations from my War of the Lancehttps://en.wikipedia.org/wiki/WaroftheLance%28videogame%29 1989 Code Harness assisted modernisation WIP I gave Qwen-3....
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AI code review: Should the author be the reviewer?
AI reviewing AI-generated code - genius or pointless? Deep analysis of AI code review paradox + real data on why it actually works better than humans.
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Previewing the Model Hardware Standard
Anthropic is opening a research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, to a first group of scientific research labs and advanced manufacturers.
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Waymo: Bringing 3D perimeter Lidar to partners
Simon Verghese, Head of Lidar Team
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Gemini 3 Deep Think drew me a good SVG of a pelican riding a bicycle
New from Google. They say it's "built to push the frontier of intelligence and solve modern challenges across science, research, and engineering". It drew me a really good SVG of …
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Random Forest vs. Neural Network
Choosing between Random Forest and Neural Network depends on the data type. Random Forest suits tabular data, while Neural Network excels with images, audio, and text data.
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Meta's Omnilingual MT for 1,600 Languages
Advances made through No Language Left Behind (NLLB) have demonstrated that high-quality machine translation (MT) scale to 200 languages. Later Large...
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Bank of America Bot Cares About You
I’ll let the horror of automation speak for itself. Not that you need further reassurance that there are no “souls” aboard this ship. WARNING: Some naughty language (this is compl…
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A better way to build ML: Why you should be using Active Learning
Data labeling is often the biggest bottleneck in machine learning. Active learning lets you train machine learning models with much less labeled data. The best AI-driven companies, like Tesla, use active learning.
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Transitioning entirely to neural machine translation
Visit the post for more.
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LeftoverLocals: Listening to LLM responses through leaked GPU local memory
We are disclosing LeftoverLocals: a vulnerability that allows recovery of data from GPU local memory created by another process on Apple, Qualcomm, AMD, and Imagination GPUs. LeftoverLocals impacts the security posture of GPU applications as a whole, with particular significance to LLMs and ML models run on impacted…
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How do domain-specific chatbots work? A retrieval augmented generation overview
Demystifying and deconstructing Q&A bots that work over your data.
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Letting AI play my game – building an agentic test harness to help play-testing
I have a solid workflow for making my game with AI. However, every iteration, I have to go through extensive manual play-testing to verify functionality…
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A framework to securely use LLMs in companies – Part 1: Overview of Risks
Part 1 of a multi-part series on using LLMs securely within your organisation. This post provides a framework to categorize risks based on different use cases and deployment type.
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Utah bill aims to make officers disclose AI-written police reports
A bill headed to the Senate floor in Utah would require officers to disclose if a police report was written by generative AI. The bill, S.B. 180, requires a department to have a policy governing the use of AI. This policy would mandate that police reports created in whole or in part by generative...
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AlphaFold: Using AI for Scientific Discovery
In our study published in Nature, we demonstrate how artificial intelligence research can drive and accelerate new scientific discoveries. We’ve built a dedicated, interdisciplinary team in hopes of using AI to push basic research forward: bringing together experts from the fields of structural biology, physics, and…
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Large Transformer Model Inference Optimization
[Updated on 2023-01-24: add a small section on Distillation.] Large transformer models are mainstream nowadays, creating SoTA results for a variety of tasks. They are powerful but very expensive to train and use. The extremely high inference cost, in both time and memory, is a big bottleneck for adopting a powerful…
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LeMario: Training a JEPA World Model on Super Mario Bros
A from-scratch JEPA world model trained on Super Mario Bros. to study action-conditioned prediction and reward-free planning.
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Autoregressive Language Model on the 6502 Processor
A language model on a 1975 MOS 6502 processor, using a tiny Mamba-based language model and custom 8-bit ternary inference engine, used to generate text on a BBC Micro from the 1980s.
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Theoretical Machine Learning Lecture Series: Deep Learning and Cognition
Deep learning, which is the reemergence of artificial neural networks, has recently succeeded as an approach towards artificial intelligence. In many fields, including computational linguistics, deep learning approaches have largely displaced earlier machine learning approaches, due to the superior performance they…
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I built a programming language using Claude Code
Over the course of four weeks in January and February, I built a new programming language using Claude Code. I named it Cutlet after my cat. It’s completely legal to do that. You can find the source code on GitHub , along with build instructions and example programs .
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OpenAI: Start using ChatGPT instantly
We’re making it easier for people to experience the benefits of AI without needing to sign up
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The problem with "vibe coding"
An article from dylanbeattie.net
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Making AI better at math tutoring
Too many students struggle with math. In fourth grade, only 36% of students are proficient in math. By ... Read more
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What is happening to writing? Cognitive debt, Claude Code, the space around AI
"Cognitive debt," Claude Code, and the negative space around AI
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On Google's Acquisition of Nest
Google’s Nest acquisition has very little to do with selling thermostats and smoke detectors in particular. Instead, it’s about Google having the ability to do consumer hardware right, in general.