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Intro to Deep Learning
I just sat down this morning and organized all deep learning related videos I recorded in 2021. I am sure this will be a useful reference for my future…
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 3,091 posts.
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A Basic Introduction to Neural Networks (2007)
Although the mathematics involved with neural networking is not a trivial matter, a user can rather easily gain at least an operational understanding of their structure and function.
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One Month Without AI
Several months ago, I decided that AI contributions were no longer welcome in a FOSS project I am building and maintaining - LibreWeddingPlanner. It’s not that it got a lot of contributions with AI — actually all contributions I’ve had are translations and feature requests — but I wanted to...
1684
Protect me from what I want
Over on Mastodon, there are many people who enjoy not being in the grip of software like Facebook or Twitter that single-mindedly tries to maximize “engagement”, which means the amount of time you stare at the screen so they can show you ads. These algorithms don’t care what they’re showing you and if it turns out…
1685
Gemini figured out my nephew’s name
I wrote an MCP server to give LLMs read-only access to my emails. Here is the chat log.
1686
Are polynomial features the root of all evil? (2024)
High-degree polynomial features aren’t inherently unstable: the power basis and unscaled inputs are. This post shows how regularization and Bernstein polynomials make polynomial regression behave.
1687
AlphaFold at CASP13: What just happened?
Update: An updated version of this blogpost was published as a (peer-reviewed) Letter to the Editor at Bioinformatics, sans the “sociology” commentary. I just came back from CASP13, the…
1688
WonderWorld: Interactive 3D Scene Generation from a Single Image
Project website for WonderWorld
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AI could be the end of the digital wave, not the next big thing
The AI boom is more likely a marker of the end of the 50-year digital boom than the start of a new wave of innovation.
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“Chatbots: Still Dumb After All These Years”
In 1970, Marvin Minsky, recipient of the Turing Award (“the Nobel Prize of Computing”), predicted that within “three to eight years we will have a machine with the general intelligence of an average human being.”
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I built an open-source, AI-powered solar panel that's 95% optimal
This research demonstrates a model-free approach to optimize the energy produced by a dual-axis solar panel using reinforcement learning. Specifically, a softmax actor-critic agent optimizes energy production in a simulated, dynamic lighting environment which is generated from real power data. All s
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Yes, Claude Code can decompile itself. Here's the source code
These LLMs are shockingly good at deobfuscation, transpilation and structure to structure conversions. I discovered this back around Christmas where I asked an LLM to make me an Haskell audio library by transpiling a rust implementation. An “oh fuck” moment in timeOver the Christmas break I’ve been critically looking
1695
Pointing AI at archives found a forgotten meteorite, lost rhinos, and more
How I used AI to investigate millions of historical records and surfaced a forgotten meteorite report, three lost rhinos, and unrecorded volcano eruptions.
1696
Why Custom GPTs are better than plugins
On November 6, 2023, OpenAI announced Custom GPTs. Since then, over 3 million GPTs have been created, with over 200.000 of them made publicly available.
1697
Bing Jail
A short story on how my website lost all indexed pages in Bing, affecting my presence in DuckDuckGo, secret blacklisting and classification as a splog by Bing AI
1698
Deep Learning vs. Machine Learning vs. Pattern Recognition
For Data Scientists: Machine Learning vs Deep Learning discussion, Deep Learning vs Machine Learning, and what is difference between machine learning, pattern recognition, computer vision, robotics, and artificial intelligence.
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Replies to comments on my "LLMs are eroding my career" post
So, my latest post went viral. And with virality, you get a ton of comments that you must reply to. I don't want to reply in HN/Reddit/Whatever to prev...
1700
Egoless Mathematics in the AI Era
[This is a guest post by Karthik C. S., Amit Sahai, and Jie Xue. This blog post was initially written in a different file format and converted using AI. — T.] This is a good time for mathemat…
1701
Talking to LLMs has improved my thinking
I’ve been surprised by - and enjoy - one aspect of using large language models more than any other. They often put into words things I have long understood, but could not write down clearly. When that happens, it feels less like learning something new and more like recognition. A kind of “ok, yeah" moment.…
1702
MCP vs. API Explained
Model Context Protocol (MCP) is an open standard that connects AI models to tools and data sources efficiently. This guide breaks down MCP’s architecture, benefits, and how it differs from traditional APIs
1703
Frontier Labs Are Selling Garbage to Fools in Washington
Selling snake oil to the United States Congress is an ancient American craft, and the frontier artificial intelligence industry is currently attempting the most audacious hustle in modern corporate history.
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Keras Tutorial – Traffic Sign Recognition
In this tutorial Tutorial assumes you have some basic working knowledge of machine learning and numpy., we will get our hands dirty with deep learning by solving a real world problem.The problem we...
1706
My class required AI
(Spoiler alert: it has been very successful, but there are some lessons to be learned)
1707
Human Brain Project: $1.61 billion to achieve human brain emulation by 2024
Henry Markram, a neuroscientist at the École Polytechnique Fédérale in Lausanne, Switzerland, has assembled a team of nine top European scientists for the research effort to build a computer model of a human brain. The Human Brain Project is in discussion with the EU for a £1billion (US$1.61 billion) grant.
1708
33TB of text data for a 1T-parameter model
Important: This page summarizes data scaling only, using tokens to parameters as a ratio, and as derived from large language models like GPT-3, Chinchilla, and beyond, linked to the Compute-Optimal scaling laws like Kaplan and Hoffmann/Chinchilla. Please note that compute scaling laws are outside the scope of my…
1709
Why machine learning struggles with causality
Machine learning systems thrive on finding and exploiting statistical regularities. This is why they can't do causal reasoning.
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