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Personal Musings and Transcripts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 3,092 posts.
Personal Musings and Transcripts
... in which a surprisingly reflective AI tells me no (for good reasons) ...
In the previous part of the Build A Basic AI Agent From Scratch series, we added the essential tools to our agent to allow it to work…
Quickly understand inscrutable LLM frameworks by intercepting API calls.
Generative AI tools like ChatGPT and Midjournery are able to replicate (and often exceed) human-like performance on tasks like taking exams, generating text and making art.
Convolution is probably the most important concept in deep learning right now. It was convolution and convolutional nets that catapulted deep learning to the forefront of almost any machine learning task there is. But what makes convolution so powerful? How does it work? In this blog post I will explain convolution…
Engineer friends often ask me: Graph Deep Learning sounds great, but are there any big commercial success stories? Is it being deployed in practical applications? Besides the obvious ones–recommendation systems at Pinterest, Alibaba and Twitter–a slightly nuanced success story is the Transformer architecture, which…
It has been a year and a half since I wrote the first version of this tutorial and it is time for an update. Knet (pronounced “kay-net”)...
This article will teach you about self-attention mechanisms used in transformer architectures and large language models (LLMs) such as GPT-4 and Llama.
This is really the same article as Part 1 - Hello CUDA, but with the focus on OpenCL, so I'll skip most of the narration and just show you the code.
The Game of Life is based on very simple rules, but artificial neural networks struggle to learn its rules through the classic deep learning training process.
Railway Mania, dot-com, AI. Technology bubbles follow a pattern older than any of them. What's different this time is that everyone knows the script.
Full stack software engineer / entrepreneur specialized in AI agents, cybersecurity and graphics. In my free time I enjoy surfing, free diving, and contributing to open source software.
A while ago there was an interesting thread on the Julia Discourse about the “state of machine learning in Julia”. I posted a response discussing the differences between Julia and Python (both JAX and PyTorch), and it seemed to be really well received! Since then this topic seems to keep coming up, so I thought I’d…
Gaussian splats, SIMA 2, JEPA and Genie 3 — and why “world model” now means three very different things at once.
In 2023, Meta researchers were able to decode images in thoughts from the brain's magnetic fields. What if that's how the brain coordinates it's own global state?
I scraped hundreds of Reddit comments that compare Claude Code and Codex, and used Claude Haiku to build a sentiment analysis dashboard. The dashboard and my interpretations are shared here.
The enormous advance in AI capabilities over the last several years has in large part been driven by the availability of vast amounts of training data.
I gave a talk about accessing Large Language Models from the command-line last week as part of the Mastering LLMs: A Conference For Developers & Data Scientists six week long …
Generative Adversarial Networks refer to a family of generative models that seek to discover the underlying distribution behind a certain data generating process. This distribution is discovered through an adversarial competition between a generator and a discriminator. As we saw in an earlier introductory post on…
In this guide, I will share the standard architecture for data-informed language model applications and explain forthcoming improvements in knowledge retrieval.
Singular Value Decomposition (SVD) is a fundamental concept in linear algebra, and it is particularly important in the field of machine learning for tasks such as dimensionality reduction, data compression, and noise reduction.
In the world of data, textual data stands out as being particularly complex. It doesn’t fall into neat rows and columns like numerical data does. As a side project, I’m in the process of developing my own personal AI assistant. The objective is to use the data within my notes and documents to answer my questions. The…
When I first read Google’s RETRO paper, I was skeptical. Sure, RETRO models are 25x smaller than the competition, supposedly leading to HUGE savings in training and inference costs. But what about the new trillion token “retrieval database” they added to the architcture? Surely that must add back some computational…
Also, shortcomings in document retrieval and how to overcome them with search & recsys techniques.
Recurrent Neural Network Tutorial for Artists
How using AI as a bridge when doctors aren't available can improve patient-to-doctor communications in real time emergencies