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Taskmaster-1 and Taskmaster-2: conversation id, utterances, Instruction id Taskmaster-3: conversation id, utterances, vertical, scenario, instructions. For further details check the project's GitHub repository or the Hugging Face dataset cards ( taskmaster-1 , taskmaster-2 , taskmaster-3 ).
Deep reinforcement learning has also been applied to many domains beyond games. In robotics, it has been used to let robots perform simple household tasks [18] and solve a Rubik's cube with a robot hand. [19] [20] Deep RL has also found sustainability applications, used to reduce energy consumption at data centers. [21]
The company was named after the U+1F917 珞 HUGGING FACE emoji. [2] After open sourcing the model behind the chatbot, the company pivoted to focus on being a platform for machine learning. In March 2021, Hugging Face raised US$40 million in a Series B funding round.
The self-reinforcement algorithm updates a memory matrix W =||w(a,s)|| such that in each iteration executes the following machine learning routine: 1. in situation s perform action a 2. receive a consequence situation s' 3. compute state evaluation v(s') of how good is to be in the consequence situation s' 4. update crossbar memory w'(a,s) = w ...
Spoilers ahead! We've warned you. We mean it. Read no further until you really want some clues or you've completely given up and want the answers ASAP. Get ready for all of today's NYT ...
Maximum meteor activity is expected to peak between 10 a.m. ET to 1 p.m. ET (15 to 18 Coordinated Universal Time) on January 3, which favors Alaska, Hawaii and far eastern Asia, said Bob Lunsford ...
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Proximal policy optimization (PPO) is a reinforcement learning (RL) algorithm for training an intelligent agent's decision function to accomplish difficult tasks. PPO was developed by John Schulman in 2017, [ 1 ] and had become the default RL algorithm at the US artificial intelligence company OpenAI . [ 2 ]