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Facts will not save you – AI, history and Soviet sci-fi
AI, history, and Soviet sci-fi
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 3,091 posts.
1862
Compressing Images with Neural Networks
An introduction to learned image compression using neural networks.
1863
Building Boba AI: Lessons learnt in building an LLM-powered application
A series of patterns for building an AI co-pilot application.
1864
Hamilton-Jacobi-Bellman Equation: Reinforcement Learning and Diffusion Models
Why the HJB is Bellman's equation in continuous time, why continuous time matters, and how to solve the resulting control problem with neural policy iteration.
1865
Notes on training BERT from scratch on an 8GB consumer GPU
I trained a BERT model (Devlin et al, 2019) from scratch on my desktop PC (which has a Nvidia 3060 Ti 8GB GPU). The model architecture, tokenizer, and trainer all came from Hugging Face libraries, and my contribution was mainly setting up the code, setting up the data (~20GB uncompressed text), and leaving my computer…
1866
How does Shazam work?
Explore how Shazam and song identification work through interactive visualizations: spectrograms, constellation maps, hash fingerprints, and time-offset matching.
1867
The super effectiveness of Pokémon embeddings using only raw JSON and images
Embeddings encourage engineers to go full YOLO because it’s actually rewarding to do so!
1868
K-Nearest Neighbors from Scratch
Using JavaScript, we implement the k-Nearest Neighbors algorithm from the bottom up.
1869
Gaussian Processes from Scratch (2019)
This post explores some concepts behind Gaussian processes, such as stochastic processes and the kernel function. We will build up deeper understanding of Gaussian process regression by implementing them from scratch using Python and NumPy.
1870
The singularity is close?
Or "Why we're all in denial about the robot apocalypse"
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Should we use AI and LLMs for Christian apologetics? (2024)
The reasons why I don’t give permission for material I’ve written to be used as training data for an LLM chatbot designed to do Christian apologetics
1873
What ChatGPT can't do
Mimicry but not thought, sophistry but not understanding
1874
Answering Legal Questions with LLMs
Blog post: Answering Legal Questions with LLMs
1875
OpenAI probably can't make ends meet. That's where you come in
If you thought the 2008 bank bailout was bad, wait til you see the 2026 AI bailout
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Translating Latin demonology manuals with GPT-4 and Claude
At long last, a real-world use case for AI!
1878
It wasn't AI that flipped Proton's charge
Proton's CEO called a request for security testing "loser thinking". Using AI to write code is fine, but for a privacy company, the guardrails around that code are the product.
1879
MCP: An (Accidentally) Universal Plugin System
Or: The Day My Toaster Started Taking Phone Calls
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Brain vs. Deep Learning (2015)
This blog post compares deep learning to the brain and derives an estimate of computational power for the brain which is used to predict the singularity.
1882
Understanding Llama 2 and the New Code Llama LLMs
In this edition of the newsletter, we direct our attention to one of the most prominent highlights of the summer: the release of the Llama 2 base and chat models, as well as CodeLlama, the latest highlights in the open-source AI large language model (LLM) landscape.
1883
Calculus on Computational Graphs: Backpropagation (2015)
Backpropagation is the key algorithm that makes training deep models computationally tractable. For modern neural networks, it can make training with gradient descent as much as ten million times faster, relative to a naive implementation. That’s the difference between a model taking a week to train and taking 200,000…
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Neural ODE's: Understanding how they model data
In this blogpost I explore how ODE’s can be used to solve data modelling problems. I take a deep dive into the data modelling problem at hand and present ODE...
1886
A friendly Introduction to Backpropagation in Python
My aim here is to test my understanding of Karpathy’s great blog post “Hacker’s guide to Neural Networks” as well as of Python, to get a hang of which I rece...
1887
ML from Scratch, Part 2: Logistic Regression (2018)
In this second installment of the machine learning from scratch we switch the point of view from regression to classification: instead of estimating a number, we will be trying to guess which of 2 possible classes a given input belongs to. A modern example is looking at a photo and deciding if its a cat or a dog.
1888
Policy on the AI Exponential
In one of the side plots to The Lord of the Rings , two of the Hobbits attempt to rouse Treebeard—a wise but ponderous sentient tree—to defend his forest from an army that is cutting it down. The problem is that Treebeard operates at a very different speed than the Hobbits. It takes him a full day simply to say hello…
1889
I think I'm done thinking about GenAI for now
The conversation isn’t over, but I don’t think I have much to add to it.
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