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One model to learn them all
One model to learn them all Kaiser et al., arXiv 2017 You almost certainly have an abstract conception of a banana in your head. Suppose you ask me if I’d like anything to eat. I can say the word ‘…
Top posts
Every blog post that took off on Hacker News, ranked by the votes of its best submission. 292 posts.
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OpenAI Five Benchmark: Results
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Face recognition in images and video with Python
Learn how to perform face recognition using OpenCV, Python, and dlib by applying deep learning for highly accurate facial recognition.
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A Global Optimization Algorithm Worth Using
Here is a common problem: you have some machine learning algorithm you want to use but it has these damn hyperparameters . These are number...
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Neuron, a new VS Code extension for data science
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Real-Time Noise Suppression Using Deep Learning
Imagine waiting for your flight at the airport. Suddenly, an important business call with a high profile customer lights up your phone. Tons of background noise clutters up the soundscape around you…
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Autopsy of a deep learning paper
Introduction I read a lot of deep learning papers, typically a few/week. I've read probably several thousands of papers. My general problem with papers in machine learning or deep learning is that often they sit
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Self-Crashing Cars
This article is geared towards people with a STEM background. For something shorter try this article in The Weekly Standard. Também disponível em português aqui . 💃🏽
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Cloud TPUs in Beta
Starting today, Cloud TPUs are available in beta on Google Cloud to help machine learning (ML) experts train and run their ML models more quickly.
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Why Love Generative Art?
Over the last 50 years, our world has turned digital at breakneck speed. No art form has captured this transitional time period - our time period - better than generative art. Generative art takes full advantage of everything that computing has to offer, producing elegant and compelling artworks tha
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How Alexa knows “peanut butter” is one shopping-list item, not two
Get the latest news and features about smart home, Alexa Built-in, and Alexa Gadgets.
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Tensorflow 2.0: models migration and new design
Tensorflow 2.0 will be a major milestone for the most popular machine learning framework: lots of changes are coming, and all with the aim of making ML accessible to everyone. These changes, however, require for the old users to completely re-learn how to use the framework: this article describes all the (known)…
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Deep reinforcement learning doesn't work yet
June 24, 2018 note: If you want to cite an example from the post, please cite the paper which that example came from. If you want to cite the post as a whole, you can use the following BibTeX:
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Facebook launches PyTorch 1.0
Earlier this year, we shared a vision for making AI development faster and more interoperable. Today, during our first-ever PyTorch Developer Conference, we are announcing updates about the growing…
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Building a Language and Compiler for Machine Learning
Since we originally proposed the need for a first-class language, compiler and ecosystem for machine learning (ML), there have been plenty of interesting developments in the field. Not only have the tradeoffs in existing systems, such as TensorFlow and PyTo...
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Prefrontal cortex as a meta-reinforcement learning system
Recently, AI systems have mastered a range of video-games such as Atari classics Breakout and Pong. But as impressive as this performance is, AI still relies on the equivalent of thousands of hours of gameplay to reach and surpass the performance of human video game players. In contrast, we can usually grasp the…
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Evolving Floorplans
Evolving Floorplans - 2017.
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Introducing Preemptible GPUs
In May 2015, Google Cloud introduced Preemptible VM instances to dramatically change how you think about (and pay for) computational resources for high-throughput batch computing, machine learning, scientific and technical workloads. Then last year, we introduced lower pricing for Local SSDs attached to Preemptible…
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OpenAI Charter
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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A Google Brain engineer’s guide to entering AI
Technical AI safety is a multifaceted area of research, with many sub-questions in areas such as reward learning, robustness, and interpretability. These will all need to be answered in order to make sure AI development will go well for humanity as systems become more and more powerful. Not all of these questions are…
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Artificial intelligence accelerates discovery of metallic glass
Machine learning algorithms pinpoint new materials 200 times faster than previously possible
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Predicting Stock Performance with Natural Language Deep Learning
We developed an NLP deep learning model using a one-dimensional convolutional neural network to predict future stock market performance of companies using Azure ML Workbench and Keras with open source for you to replicate.
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Lessons Learned Reproducing a Deep Reinforcement Learning Paper
There are a lot of neat things going on in deep reinforcement learning. One of the coolest things from last year was OpenAI and DeepMind’s work on training an agent using feedback from a human rather than a classical reward signal. There’s a great blog post about it at Learning from Human Preferences , and the…
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Making a racist AI without really trying (2017)
A cautionary tutorial. Let's make a sentiment classifier!¶Sentiment analysis is a very frequently-implemented task in NLP, and it's no surprise. Recognizing whether people are expressing positi