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A journey into Kindle AI slop hell
A journey into Kindle A.I. slop hell with Leah Beckmann
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 673 posts.
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AI-powered conversion from Enzyme to React Testing Library
Update (October 2024): In response to numerous requests from external developers, we have open-sourced a version of our Enzyme to React Testing Library (RTL) conversion tool. You can now find it on npm, along with detailed instructions on how to integrate and use it in your projects. In the world of frontend…
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Trillium TPU Is GA
Trillium, Google’s sixth-generation Tensor Processing Unit (TPU) is now GA, delivering enhanced performance and cost-effectiveness for AI workloads.
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A decoder-only foundation model for time-series forecasting
Posted by Rajat Sen and Yichen Zhou, Google Research Time-series forecasting is ubiquitous in various domains, such as retail, finance, manufacturi...
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Systematically Improving Your RAG
Discover systematic strategies to enhance your Retrieval-Augmented Generation (RAG) systems for better performance and user experience.
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iTerm2 and AI Hype Overload
Xe Iaso's personal website.
398
Zen, CUDA, and Tensor Cores, Part I: The Silicon
Given the complexity of today's computing hardware, it’s easy to get confused about what is meant by the word “core”.
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Using Large Language Models to Catch Vulnerabilities
Posted by the Big Sleep team Introduction In our previous post, Project Naptime: Evaluating Offe...
400
Cerebras Inference: AI at Instant Speed
We are excited to announce the release of Cerebras DocChat, our first iteration of models designed for document-based conversational question answering. This series includes two models: Cerebras Llama3-DocChat, a large language model (LLM), and Cerebras Dragon-DocChat, a multi-turn retriever model.
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Moonshine, the new state of the art for speech to text
Can you imagine using a keyboard where it took a key press two seconds to show up on screen? That’s the typical latency for most voice interfaces, so it’s no wonder they’ve failed…
402
Compressing Images with Neural Networks
An introduction to learned image compression using neural networks.
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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!
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Georgia Tech, Meta create open dataset to advance solutions for carbon capture
To avoid catastrophic climate impacts, excessive carbon emissions must be addressed. At this point, cutting emissions isn’t enough. Direct air capture, a technology that pulls carbon dioxide out of ambient air, has great potential to help solve the problem.
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Answering Legal Questions with LLMs
Blog post: Answering Legal Questions with LLMs
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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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Every Way to Get Structured Output from LLMs
A survey of every framework for extracting structured output from LLMs, and how they compare.
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Golden Gate Claude
When we amplify the "Golden Gate Bridge" feature, Claude's responses focus on the bridge. For a short time, anyone can interact with this model.
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PyTorch Native Architecture Optimization: Torchao
We’re happy to officially launch torchao, a PyTorch native library that makes models faster and smaller by leveraging low bit dtypes, quantization and sparsity. torchao is an accessible toolkit of techniques written...
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What I've Learned in the Past Year Spent Building an AI Video Editor
Lessons from An Unexpected Year in AI
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Qwen2.5: A Party of Foundation Models
GITHUB HUGGING FACE MODELSCOPE DEMO DISCORD Introduction In the past three months since Qwen2’s release, numerous developers have built new models on the Qwen2 language models, providing us with valuable feedback. During this period, we have focused on creating smarter and more knowledgeable language models. Today, we…
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New algorithm discovers language just by watching videos
Mark Hamilton, an MIT PhD student in electrical engineering and computer science and affiliate of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), wants to use machines to understand how animals communicate. To do that, he set out first to create a system that can learn human language “from…
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Publishing AI Slop Is a Choice
Link to: https://www.nytimes.com/2024/05/24/technology/google-ai-overview-search.html
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AI for Data Journalism: demonstrating what we can do with this stuff
I gave a talk last month at the Story Discovery at Scale data journalism conference hosted at Stanford by Big Local News. My brief was to go deep into the …
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ZombAIs: From Prompt Injection to C2 with Claude Computer Use
A few days ago, Anthropic released Claude Computer Use, which is a model + code that allows Claude to control a computer. It takes screenshots to make …
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Fixing Gemma Bugs
Unsloth fixing Google's open-source language model Gemma.
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Exploring LoRA – Part 1: The Idea Behind Parameter Efficient Fine-Tuning
“The What and Why of Adapter based Parameter Efficient Fine Tuning: Understanding Its Purpose and Significance”