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Scientists should use AI as a tool, not an oracle
How AI hype leads to flawed research that fuels more hype
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I'm going to keep opting out
Marketing, solicitations, advertising, political contact, direct mailers, email campaigns, cookies, ads — it's all opt out. It puts the burden on you to opt out of each communication each message, each outreach from a loyalty program. It can feel like weeding a garden, but that garden is your attention. The weeds keep…
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A simplified Python simulation of diffusion
Understanding the real world is not always easy. A Python simulation can help. And let's find ways of making it efficient, too.
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AI or Ain't: Eliza
Explore the intriguing history of Eliza, a pioneering chatbot, and learn how to implement a basic version in Go, unraveling the roots of conversational AI.
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Llama 3 feels significantly less censored than its predecessor
Compared to Llama 2, Llama 3 feels much less censored. Meta has substantially lowered false refusal rates. Llama 3 will refuse less than 1/3 of the prompts previously refused by Llama 2.
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MK1 Flywheel Unlocks the Full Potential of AMD Instinct for LLM Inference
AMD acquires MK1, welcoming their world-class team and marking another key milestone in our strategy to advance AI performance and efficiency.
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The History of Machine Learning in Trackmania
Trackmania: the world's most competitive racing game. In this post, we begin our journey towards training a neural network to superhuman performance, by chronicling the history of previous attempts.
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LLM-generated code must not be committed without prior written approval by core
If you are not sure if the code you plan to commit is acceptable (e. g. when taking code that was submitted with a problem report), ask a developer who is familiar with that part of the system for review. If you're new to the Project, check with your sponsor.
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I Taught My 8yo Subduction Zones with NotebookLM
Principal AI Architect. Creator of open-strix, a harness for building agent teams. Writing about AI architecture, stateful agents, and what happens when you give AI memory.
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Making my local LLM voice assistant faster and more scalable with RAG
If you read my previous blog post, you probably already know that I like my smart home open-source and very local, and that certainly includes any voice assistant I may have. If you watched the video demo, you have probably also found out that it’s… slow. Trust me, I did too. Prefix caching helps, but it feels like…
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PaliGemma: Open-Source Multimodal Model by Google
Learn how to use PaliGemma, a vision language model developed and released by Google that has multimodal capabilities.
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Against the Dark Forest
The complex of ideas I’m going to call the Dark Internet Forest emerges from mostly insidery tech thinking, but from multiple directions.
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Declarative Programming with AI/LLMs
What Is Declarative Programming Broadly speaking, there are two ways to program/instruct a computer to perform a task, they are imperative...
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Speaking without vocal cords, thanks to a new AI-assisted wearable device
The adhesive neck patch is the latest advance by UCLA bioengineers in speech technology for people with disabilities.
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Chess-GPT's Internal World Model
A Chess-GPT Linear Emergent World Representation
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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
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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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Manipulating Chess-GPT's World Model
Manipulating Chess-GPT’s World Model
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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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Learning From DNA: a grand challenge in biology
Is DNA all you need?
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Building an early warning system for LLM-aided biological threat creation
We’re developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat. In an evaluation involving both biology experts and students, we found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not…
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Low-poly image generation using evolutionary algorithms in Ruby (2023)
A deep dive into evolutionary algorithms through the lens of low-poly image generation. This exploration covers genetic algorithm theory, custom Ruby implementation using the Petri Dish framework, and detailed analysis of genetic operators including roulette wheel selection, random midpoint crossover, and nudge…
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Machine Learning Is Still Too Hard for Software Engineers
Machine Learning has made huge strides in the last few decades, but it remains largely inaccessible to the average developer. This post examines some of the reasons why.
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Computing Inside an AI
Since the launch of ChatGPT, explorations in two directions kicked into high gear.
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Deterministic Quoting: Making LLMs safer for healthcare
LLMs have the potential to revolutionise our field of healthcare, but the fear and reality of hallucinations prevent adoption in most applications.
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Extending the context length to 1M tokens
API Documentation (Chinese) HuggingFace Demo ModelScope Demo Introduction After the release of Qwen2.5, we heard the community’s demand for processing longer contexts. In recent months, we have made many optimizations for the model capabilities and inference performance of extremely long context. Today, we are proud…
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Linear transformers are faster after all
Our mission is to train a neural network to model all human output.