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New
The latest blog posts to take off on Hacker News. 3,242 posts.
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Reverse Engineering Google Colab
Take a peek into the internals of Google Colab, and discover how we can bend the rules of Colab a little in order to adapt it to our MLOps workflow
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How Imagen Works
Given a brief description of a scene, Imagen can generate photorealistic, high-resolution images of the scene. Learn everything you need to know about Imagen and how it works in this easy-to-follow guide.
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Next-generation AI models
We've put together an index of testing terms and articles, covering many of the basics of testing and definitions for common searches.
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GitHub Copilot is generally available
We’re making GitHub Copilot, an AI pair programmer that suggests code in your editor, generally available to all developers for $10 USD/month or $100 USD/year. It will also be free to use for verified students and maintainers of popular open source projects.
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Techniques for Training Large Neural Networks
Large neural networks are at the core of many recent advances in AI, but training them is a difficult engineering and research challenge which requires orchestrating a cluster of GPUs to perform a single synchronized calculation.
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Deploying Transformers on the Apple Neural Engine
An increasing number of the machine learning (ML) models we build at Apple each year are either partly or fully adopting the Transformer…
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Mozilla releases local machine translation tools as part of Project Bergamot
In January of 2019, Mozilla joined the University of Edinburgh, Charles University, University of Sheffield and University of Tartu as part of a project fu
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WebGPT: Improving the factual accuracy of language models through web browsing
We’ve fine-tuned GPT-3 to more accurately answer open-ended questions using a text-based web browser.
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Accelerated PyTorch Training on M1 Mac
In collaboration with the Metal engineering team at Apple, we are excited to announce support for GPU-accelerated PyTorch training on Mac. Until now, PyTorch training on Mac only leveraged the...
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NaturalSpeech: End-to-end text to speech synthesis with human-level quality
Text to speech (TTS) has made rapid progress in both academia and industry in recent years. Some questions naturally arise that whether a TTS system can achieve human-level quality, how to define/judge that quality and how to achieve it. In this paper, we answer these questions by first defining the human-level…
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We asked 100 humans to draw the DALL·E prompts
Where do human artists fit in a world of rich, creative AI? We asked 100 Surgers to draw the DALL-E prompts.
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DeepMind: A Generalist Agent
Explore a selection of our recent research on some of the most complex and interesting challenges in AI.
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BERTopic: The Future of Topic Modeling
BERTopic takes advantage of the superior language capabilities of (not yet sentient) transformer models and uses some other ML magic like UMAP and HDBSCAN to produce what is one of the most advanced techniques in language topic modeling today.
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Cloud TPU VMs are generally available
Cloud TPU VMs with Ranking & Recommendation acceleration are generally available on Google Cloud. Customers will have direct access to TPU host machines.
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Recognize Digits Using ML in Elixir
Machine learning allows you to solve once unimaginable problem. Elixir's support for machine learning through Nx and Axon let us do impressive thing while staying in our favorite language.
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Learning to think critically about machine learning
Graduate students are helping to infuse ethical computing content into MIT’s largest machine learning course, as part of the Social and Ethical Responsibilities of Computing initiative.
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Tackling multiple tasks with a single visual language model
We introduce Flamingo, a single visual language model (VLM) that sets a new state of the art in few-shot learning on a wide range of open-ended multimodal tasks.
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Amazon releases 51-language dataset for language understanding
MASSIVE dataset and Massively Multilingual NLU (MMNLU-22) competition and workshop will help researchers scale natural-language-understanding technology to every language on Earth.
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How DALL-E 2 Works
How does OpenAI's groundbreaking DALL-E 2 model actually work? Check out this detailed guide to learn the ins and outs of DALL-E 2.
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Doing small network scientific machine learning in Julia faster than PyTorch
Doing small network scientific machine learning in Julia 5x faster than PyTorch ...
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K-Nearest Neighbors
One Machine Learning algorithm that relies on the concepts of proximity and similarity is K-Nearest Neighbor (KNN). KNN is a supervised learning algorithm capable of performing both classification and regression tasks.
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Differentiable Programming – A Simple Introduction
What is Differentiable Programming, and how is it different from Deep Learning? Check out this introduction to learn everything you need to know!
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Pathways Language Model (PaLM): Scaling to 540B parameters
Posted by Sharan Narang and Aakanksha Chowdhery, Software Engineers, Google Research In recent years, large neural networks trained for language un...