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Overcoming the limits of current LLMs
Large language models (LLM) have been all the rage for quite some time now. Looking beyond the hype though, they have severe limitations: hallucinations, lack o
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 6,332 posts.
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Sam Altman Goes Full Emperor
His boundless ambition is putting AI, and the world, on a dangerous path.
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The Hyperbolic Geometry of DMT Experiences (2016)
[Content Warning: Trying to understand the contents of this essay may be mind-warping. Proceed with caution. Featured image credit: Paul Nylander] Friends, right here and now, one quantum away, the…
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Text-to-CAD
Introducing our machine learning model for generating CAD models from a text prompt.
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Can a person be identified by just the way they type?
Do a detailed analysis of your own typing style, just using Mathematica. Can a person be identified just by the way they type? See group data analysis.
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Agentic pelican on a bicycle
The agentic loop—generate, assess, improve—seems like a natural fit for iterating on pelicans on bicycles.
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Sandboxing AI Agents in Linux
Like many developers, I find myself more and more using AI agents to help with software development. I currently use Claude Code, the co...
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Building an (almost) fully self-hosted, sandboxed, agentic software factory
I built an (almost) fully self-hosted, sandboxed, agentic software factory.
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Electricity use of AI coding agents
Most of the discourse about the environmental impact of LLM use focuses on a ‘median query.’ What about a Claude Code session?
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How should we evaluate progress in AI?
Improving artificial intelligence research with scientific testing, design practice, and meta-rational choice of methods and criteria
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Multi-Agentic Software Development Is a Distributed Systems Problem
Recently, I've been thinking a lot about scaffolding and languages for managing systems of LLMs coordinating with each other — new programming languages might be the ideal solution for this area.
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Whistleblower: Huawei cloned Qwen and DeepSeek models, claimed as own
A now-deleted report by HonestAGI on GitHub showed a high number of similarities between Huawei’s Pangu and Qwen 2.5.
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The Generative Burrito Test
A critical benchmark for image generation models: A partially eaten burrito with cheese, sour cream, guacamole, lettuce, salsa, pinto beans, and chicken.
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Measuring AI agent autonomy in practice
Analysis of millions of human-agent interactions shows agent turns getting longer, with software engineering making up nearly half of tool calls.
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Thoughts on ML Engineering After a Year of My PhD
My personal website
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A way to deal with enormous branching factors in strategy games
When you play Chess, there are on average something like 30 different moves you can make each turn. In other words, the branching factor is ...
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Neurons Gone Wild
To reject gods and spirits is easy: just bully them away in the name of science.
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MS Paint Cocreator, a new AI-powered experience powered by DALL-E
UPDATE 10/23: The update to the Paint app for Windows 11 that includes Paint Cocreator is now rolling out to Windows Insiders in the Release Preview Channel (version 11.2309.20.0 or higher
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Autoencoding Blade Runner: reconstructing films with artificial neural networks
Reconstructing films with artificial neural networks
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Manipulating Chess-GPT's World Model
Manipulating Chess-GPT’s World Model
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Revisiting Minsky's Society of Mind in 2025
AI Agents, Modularity, and Alignment
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Maximum likelihood estimation and loss functions
When I started learning about loss functions, I could always understand the intuition behind them. For example, the mean squared error (MSE) for regression seemed logical—penalizing large deviations from the ground-truth makes sense. But one thing always bothered me: I could never come up with those loss functions on…
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An Adversarial Review of “Adversarial Generation of Natural Language”
Or, for fucks sake, DL people, leave language alone and stop saying you solve it.
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Learning From DNA: a grand challenge in biology
Is DNA all you need?
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The Magic of Embeddings
Embeddings, why they’re useful, and how we can store and use them in Convex.