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  2. List of datasets for machine-learning research - Wikipedia

    en.wikipedia.org/wiki/List_of_datasets_for...

    Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...

  3. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    The Hugging Face Hub is a platform (centralized web service) for hosting: [20] Git -based code repositories , including discussions and pull requests for projects. models, also with Git-based version control;

  4. Hugging Face cofounder Thomas Wolf says open-source AI’s ...

    www.aol.com/finance/hugging-face-cofounder...

    Hugging Face, of course, is the world’s leading repository for open-source AI models—the GitHub of AI, if you will. Founded in 2016 (in New York, as Wolf reminded me on stage when I ...

  5. Deep reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Deep_reinforcement_learning

    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]

  6. Startup Hugging Face aims to cut AI costs with open source ...

    www.aol.com/news/startup-hugging-face-aims-cut...

    Hugging Face on Wednesday said it is releasing a new open-source software offering with Amazon.com, Alphabet's Google and others aimed at lowering the costs for building chatbots and other AI systems.

  7. Google Cloud partners with Hugging Face to attract AI ... - AOL

    www.aol.com/news/google-cloud-partners-hugging...

    The cloud computing arm of Alphabet Inc said on Thursday it had formed a partnership with startup Hugging Face to ease artificial intelligence (AI) software development in the company's Google Cloud.

  8. Proximal policy optimization - Wikipedia

    en.wikipedia.org/wiki/Proximal_Policy_Optimization

    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]

  9. Model-free (reinforcement learning) - Wikipedia

    en.wikipedia.org/wiki/Model-free_(reinforcement...

    Model-free RL algorithms can start from a blank policy candidate and achieve superhuman performance in many complex tasks, including Atari games, StarCraft and Go.Deep neural networks are responsible for recent artificial intelligence breakthroughs, and they can be combined with RL to create superhuman agents such as Google DeepMind's AlphaGo.