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PyTorch 1.5
Today, we’re announcing the availability of PyTorch 1.5, along with new and updated libraries. This release includes several major new API additions and improvements. PyTorch now includes a significant update...
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The latest blog posts to take off on Hacker News. 212 posts.
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Building an end-to-end Speech Recognition model in PyTorch
The complete guide on how to build an end-to-end Speech Recognition model in PyTorch. Train your own CTC Deep Speech model using this tutorial.
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Enemy AI: chasing a player without Navigation2D or A* pathfinding
Making a game where your enemies need to chase the player? This starts out easy, make the enemy run towards the player! But what happen...
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CuPy Accelerates NumPy on the GPU? Hold My Cider, Here's Clojure
Everyone knows that Java is slow and Clojure is not a great choice for number crunching, but as soon as I dig anywhere with my software, I discover that the ...
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All models are wrong, but some are completely wrong
At this critical time in the modern history of the human race, mathematical models have been pushed into the foreground. Epidemic forecasting informs policy and even individual decision-making. Sad…
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Illustrated FixMatch for semi-supervised learning
Learn how to leverage unlabeled data using FixMatch for semi-supervised learning
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Slack's core flaws require topic modeling to fix
Chatops is a ladder
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ACM Prize in Computing Awarded to AlphaGo Developer
Silver, a professor at University College London and Principal Research Scientist at DeepMind, is recognized as a central figure in the growing and impactful area of deep reinforcement learning, leading the team that developed AlphaGo.
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An Overview of Bayesian Inference (2019)
A few weeks ago I wrote about Kuhn’s theory of paradigm shifts and how it relates to Bayesian inference. In this post I want to back up a little bit and explain what Bayesian inference is, and eventually rediscover the idea of a paradigm shift just from understanding how Bayesian inference works.
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Unsupervised learning of probably symmetric deformable 3D objects from images
We propose a method to learn weakly symmetric deformable 3D object categories from raw single-view images, without ground-truth 3D, multiple views, 2D/3D keypoints, prior shape models or any other supervision.
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Signal processing is key to embedded machine learning
When we hear about ML - whether it’s about machines learning to play Go or computers generating plausible human language - we often think about deep learning.
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Using JAX, numpy, and optimization techniques to improve separable image filters
By the end of this blog post, we aim to improve the results of my previous blog post of approximating circular bokeh with a sum of 4 separable filters and reducing its artifacts (left) through an o…
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Cloud AI Platform Pipelines
AI Platform Pipelines provides enterprise-ready infrastructure for deploying and running structured ML workflows, and pipeline tools for building, debugging, and sharing pipelines and components.
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Lagrangian Neural Networks
A blog by Sam Greydanus
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Transformers Are Graph Neural Networks
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…
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Computational predictions of protein structures associated with COVID-19
The scientific community has galvanised in response to the recent COVID-19 outbreak, building on decades of basic research characterising this virus family. Labs at the forefront of the outbreak response shared genomes of the virus in open access databases, which enabled researchers to rapidly develop tests for this…
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Deep Learning Algorithms: The Complete Guide
All the essential Deep Learning Algorithms you need to know including models used in Computer Vision and Natural Language Processing
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Visual Introduction to Self Supervised Learning
A visual introduction to self-supervised learning methods for visual representations.
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Machine Learning, Kolmogorov Complexity, and Squishy Bunnies (2019)
Computer Science, Machine Learning, Programming, Art, Mathematics, Philosophy, and Short Fiction
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T5: The Text-to-Text Transfer Transformer
Posted by Adam Roberts, Staff Software Engineer and Colin Raffel, Senior Research Scientist, Google Research Over the past few years, transfer le...
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Andreessen-Horowitz craps on “AI” startups from a great height
Andreessen-Horowitz has always been the most levelheaded of the major current year VC firms. While other firms were levering up on “cleantech” and nonsensical biotech startups that viol…
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The Next Leap in Self-Driving: Prediction
Why prediction has overtaken perception as the biggest challenge in the field.
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JPEG Committee releases a call for evidence for image compression based on AI
The 86th JPEG meeting was held in Sydney, Australia. Among the different activities that took place, the JPEG Committee issued a Call for Evidence on learning-based image coding solutions. In addition, a First Call for Evidence on Point Cloud Coding was issued in the framework of JPEG Pleno Point Cloud Coding…