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3129 مقال
Internships - Tesla
Internships Tesla
Two Amazon summer reading programs inspire kids to love books - About Amazon
Two Amazon summer reading programs inspire kids to love books About Amazon
Two Amazon summer reading programs inspire kids to love books - About Amazon
Two Amazon summer reading programs inspire kids to love books About Amazon
OpenAI Scholars 2021: Final projects
We’re proud to announce that the 2021 class of OpenAI Scholars has completed our six-month mentorship program and have produced an open-source research project with stipends and support from OpenAI.
Celebrating Women’s History Month - meta.com
Celebrating Women’s History Month meta.com
Amazon to help 29 million people grow their tech skills with free cloud computing skills training - About Amazon
Amazon to help 29 million people grow their tech skills with free cloud computing skills training About Amazon
Best books of the year - About Amazon
Best books of the year About Amazon
8 free skills training programs that help Amazon employees land higher-paying roles - About Amazon
8 free skills training programs that help Amazon employees land higher-paying roles About Amazon
Amazon News - About Amazon
Amazon News About Amazon
Upskilling 2025 - About Amazon
Upskilling 2025 About Amazon
Helping 700,000 students transition to remote learning - About Amazon
Helping 700,000 students transition to remote learning About Amazon
Emergent tool use from multi-agent interaction
We’ve observed agents discovering progressively more complex tool use while playing a simple game of hide-and-seek. Through training in our new simulated hide-and-seek environment, agents build a series of six distinct strategies and counterstrategies, some of which we did not know our environment supported. The self-supervised emergent complexity in this simple environment further suggests that multi-agent co-adaptation may one day produce extremely complex and intelligent behavior.
Learning Day
At OpenAI, each Thursday is Learning Day: a day where employees have the option to self-study technical skills that will make them better at their job but which aren’t being learned from daily work.
Learning Day
At OpenAI, each Thursday is Learning Day: a day where employees have the option to self-study technical skills that will make them better at their job but which aren’t being learned from daily work.
Promoting Digital Literacy in Myanmar - meta.com
Promoting Digital Literacy in Myanmar 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.
Spinning Up in Deep RL
We’re releasing Spinning Up in Deep RL, an educational resource designed to let anyone learn to become a skilled practitioner in deep reinforcement learning. Spinning Up consists of crystal-clear examples of RL code, educational exercises, documentation, and tutorials.
Spinning Up in Deep RL
We’re releasing Spinning Up in Deep RL, an educational resource designed to let anyone learn to become a skilled practitioner in deep reinforcement learning. Spinning Up consists of crystal-clear examples of RL code, educational exercises, documentation, and tutorials.
Learning concepts with energy functions
We’ve developed an energy-based model that can quickly learn to identify and generate instances of concepts, such as near, above, between, closest, and furthest, expressed as sets of 2d points. Our model learns these concepts after only five demonstrations. We also show cross-domain transfer: we use concepts learned in a 2d particle environment to solve tasks on a 3-dimensional physics-based robot.
Learning concepts with energy functions
We’ve developed an energy-based model that can quickly learn to identify and generate instances of concepts, such as near, above, between, closest, and furthest, expressed as sets of 2d points. Our model learns these concepts after only five demonstrations. We also show cross-domain transfer: we use concepts learned in a 2d particle environment to solve tasks on a 3-dimensional physics-based robot.