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The AI Scientist: Towards Automated Open-Ended Scientific Discovery
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
Topics /
AI & Machine Learning
The most popular blog posts about ai & machine learning on Hacker News. 3,240 posts.
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Improvements to data analysis in ChatGPT
Improvements to data analysis in ChatGPT Interact with tables and charts and add files directly from Google Drive and Microsoft OneDrive.
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Recovering redacted information from pixelated videos
We explore the history of image unblurring and present a simple yet effective technique to get a high-resolution image from a pixelated video in order to recover redacted information (with no guessing involved).
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Solving some formal math olympiad problems
We built a neural theorem prover for Lean that learned to solve a variety of challenging high-school olympiad problems, including problems from the AMC12 and AIME competitions, as well as two problems adapted from the IMO.
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Game theory as an engine for large-scale data analysis
Modern AI systems approach tasks like recognising objects in images and predicting the 3D structure of proteins as a diligent student would prepare for an exam. By training on many example problems, they minimise their mistakes over time until they achieve success. But this is a solitary endeavour and only one of the…
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Claude 3 beats GPT-4 on Aider's code editing benchmark
Claude 3 Opus outperforms all of OpenAI’s models on Aider’s code editing benchmark, making it the best available model for pair programming with AI.
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What 81,000 people want from AI
Last December, tens of thousands of Claude users around the world had a conversation with our AI interviewer to share how they use AI, what they dream it could make possible, and what they fear it might do.
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Introducing Agents in Haystack: Make LLMs resolve complex tasks
LLMs can now make use of the right tools to resolve complex queries and tasks
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More Data Is Not Better and Machine Learning Is a Grind
I had an opportunity to sit in on a lecture today by two experts on Machine Learning from Amazon, during a lecture at UNC. Ed Banti is Director of Software Development, Core AI Amazon, and Pat Bajari, was VP and Chief Economist, Core AI, at Amazon as well. Both gentlemen shared their insights on working with AI…
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A Mechanistic Interpretability Analysis of Grokking
Neel Nanda reverse engineers neural networks that have "grokked" modular addition, showing that they operate using Discrete Fourier Transforms and tr…
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Beyond Diffusion: Inductive Moment Matching
Inductive Moment Matching surpasses diffusion models in speed and sample quality.
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Learning to write programs that generate images
Through a human’s eyes, the world is much more than just the images reflected in our corneas. For example, when we look at a building and admire the intricacies of its design, we can appreciate the craftsmanship it requires. This ability to interpret objects through the tools that created them gives us a richer…
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Mozilla Is Crowdsourcing Research into YouTube Recommendations
Mozilla has built a browser add-on that transforms YouTube users into YouTube watchdogs YouTube recommendations can be delightful, but they can also be…
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Protecting our FLOSS commons from LLMs
In Brief: Two motions regarding
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Intellect-2 Release: The First 32B Model Trained Through Globally Distributed RL
We're excited to release INTELLECT-2, the first 32B parameter model trained via globally distributed reinforcement learning. Unlike traditional centralized training efforts, INTELLECT-2 trains a reasoning language model using fully asynchronous RL across a dynamic, heterogeneous swarm of compute contributors.
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Machine learning saves us $1.7M a year on document previews
Recently, we translated the predictive power of machine learning (ML) into $1.7 million a year in infrastructure cost savings by optimizing how Dropbox generates and caches document previews. Machine learning at Dropbox already powers commonly-used features such as search , file and folder suggestions , and OCR in…
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Emu Video and Emu Edit, our latest generative AI research milestones
Today, we’re announcing new research into controlled image editing based solely on text instructions and a method for text-to-video generation based on diffusion models.
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The hippocampus as a 'predictive map'
Think about how you choose a route to work, where to move house, or even which move to make in a game like Go. All of these scenarios require you to estimate the likely future reward of your decision. This is tricky because the number of possible scenarios explodes as one peers farther and farther into the future…
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ChatGPT – The Revolutionary Bullshit Parrot
ChatGPT seems convincing and wise but is neither wise nor hallucinatory—just bullshit. Here’s biased take on AI’s socalled revolution.
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Learning from Tay’s introduction
As many of you know by now, on Wednesday we launched a chatbot called Tay. We are deeply sorry for the unintended offensive and hurtful tweets from Tay, which do not represent who we are or what we stand for, nor how we designed Tay. Tay is now offline and we’ll look to bring Tay...
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We're Joining OpenAI
Alex is the ultimate tool for iOS and Swift app development, empowering developers with AI for Xcode to streamline workflows, tackle complex coding challenges, and boost productivity. Discover what makes it an essential asset for modern app creation.
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Patterns and problems in emerging multi-agent systems
We ran experiments on swarms of Claude agents and found coordination failures, collusion, and sabotage. Here, we share what they mean for AI safety.
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Dynamic Workflows in Claude Code
Dynamic workflows in Claude Code let Claude tackle the most challenging tasks by executing across 10s to 100s of parallel subagents, and checking its work before anything reaches you.
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Announcing GPT-NeoX-20B
Announcing GPT-NeoX-20B, a 20 billion parameter model trained in collaboration with CoreWeave.
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What Is a Knowledge Graph?
What is a knowledge graph? Learn about nodes, relationships, organizing principles, and ontologies, which comprise a knowledge graph.
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Natural Language Processing: The Age of Transformers
This article is the first installment of a two-post series on Building a machine reading comprehension system using the latest advances in deep learning for NLP.
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