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How The New York Times Uses Software to Recognize Members of Congress
Even if you’ve covered Congress for The New York Times for a decade, it can be hard to recognize which member you’ve just spoken with…
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Preparing for Malicious Uses of AI
Stay up to speed on the rapid advancement of AI technology and the benefits it offers to humanity.
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Waymo One: The next step on our self-driving journey
Over time, we hope to make Waymo One available to even more members of the public as we add vehicles and drive in more places.
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Algorithm recovers speech from a potato-chip bag filmed through glass (2014)
Algorithm recovers speech from the vibrations of a potato-chip bag filmed through soundproof glass.
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Using a Keras Long Short-Term Memory Model to Predict Stock Prices
Editor’s note: This tutorial illustrates how to get started forecasting time series with LSTM models. Stock market data is a great choice for this because it’s quite regular and widely available to everyone. Please don’t take this as financial advice… Continue reading Using a Keras Long Short-Term Memory (LSTM) Model…
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Introduction to Decision Tree Learning
From Kaggle to classrooms, one of the first lessons in machine learning involves decision trees. The reason for the focus on decision trees is that they aren’t very mathematics heavy compared to other ML approaches, and at the same time,… Continue reading Introduction to Decision Tree Learning
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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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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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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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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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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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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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