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Why We Disagree With the Bundeskartellamt - meta.com
Why We Disagree With the Bundeskartellamt meta.com
Banning More Dangerous Organizations from Facebook in Myanmar - meta.com
Banning More Dangerous Organizations from Facebook in Myanmar meta.com
Removing Coordinated Inauthentic Behavior From Iran - meta.com
Removing Coordinated Inauthentic Behavior From Iran meta.com
Customer Support - Tesla
Customer Support Tesla
Designing Security for Billions - meta.com
Designing Security for Billions meta.com
Meet Scout - About Amazon
Meet Scout About Amazon
Making Pages More Transparent and Accountable - meta.com
Making Pages More Transparent and Accountable meta.com
Facebook and the Technical University of Munich Announce New Independent TUM Institute for Ethics in Artificial Intelligence - meta.com
Facebook and the Technical University of Munich Announce New Independent TUM Institute for Ethics in Artificial Intelligence meta.com
Removing Coordinated Inauthentic Behavior from Russia - meta.com
Removing Coordinated Inauthentic Behavior from Russia meta.com
Banning Twinmark Media Enterprises in the Philippines from Facebook - meta.com
Banning Twinmark Media Enterprises in the Philippines from Facebook meta.com
Schedule and Manage Tesla Service Appointments - Tesla
Schedule and Manage Tesla Service Appointments Tesla
Preparing for a Mobile Service Appointment - Tesla
Preparing for a Mobile Service Appointment Tesla
How AI training scales
We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks. Since complex tasks tend to have noisier gradients, increasingly large batch sizes are likely to become useful in the future, removing one potential limit to further growth of AI systems. More broadly, these results show that neural network training need not be considered a mysterious art, but can be rigorized and systematized.
How AI training scales
We’ve discovered that the gradient noise scale, a simple statistical metric, predicts the parallelizability of neural network training on a wide range of tasks. Since complex tasks tend to have noisier gradients, increasingly large batch sizes are likely to become useful in the future, removing one potential limit to further growth of AI systems. More broadly, these results show that neural network training need not be considered a mysterious art, but can be rigorized and systematized.
Facebook Watch: What We’ve Built and What’s Ahead - meta.com
Facebook Watch: What We’ve Built and What’s Ahead meta.com
Quantifying generalization in reinforcement learning
We’re releasing CoinRun, a training environment which provides a metric for an agent’s ability to transfer its experience to novel situations and has already helped clarify a longstanding puzzle in reinforcement learning. CoinRun strikes a desirable balance in complexity: the environment is simpler than traditional platformer games like Sonic the Hedgehog but still poses a worthy generalization challenge for state of the art algorithms.
Coordinated Inauthentic Behavior Explained - meta.com
Coordinated Inauthentic Behavior Explained meta.com
Response to Six4Three Documents - meta.com
Response to Six4Three Documents meta.com
Tesla Account Support - Tesla
Tesla Account Support Tesla
Winter Driving Tips - Tesla
Winter Driving Tips Tesla