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Joined 9 months ago
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Cake day: March 4th, 2024

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  • The linear algebraic computations performed on their GPU’s tensor cores (since the Turing era) combined with their CUDA and cuDNN software stack have the fastest performance in training deep neural network algorithms.

    That may not last forever, but it’s the best in terms of dollars per FLOPS an average DNN developer like myself has access to currently.







  • I make DNNs (deep neural networks), the current trend in artificial intelligence modeling, for a living.

    Much of my ancillary work consists of deflating/tempering the C-suite’s hype and expectations of what “AI” solutions can solve or completely automate.

    DNN algorithms can be powerful tools and muses in scientific endeavors, engineering, creativity and innovation. They aren’t full replacements for the power of the human mind.

    I can safely say that many, if not most, of my peers in DNN programming and data science are humble in our approach to developing these systems for deployment.

    If anything, studying this field has given me an even more profound respect for the billions of years of evolution required to display the power and subtleties of intelligence as we narrowly understand it in an anthropological, neuro-scientific, and/or historical framework(s).