BRN 0.00% 15.5¢ brainchip holdings ltd

Thank you Fact FinderSo to piece it...

  1. LJD
    609 Posts.
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    Thank you Fact Finder

    So to piece it altogether.

    Glossary

    Convolutional Neural Networks (CNNs) excel at processing spatial information in images but struggle with effectively utilizing temporal information. Large training data needed, doesn’t encode the position and orientation of object.

    Recurrent Neural Networks (RNNs) provide an internal state with temporal dynamics, allowing them to capture sequential dependencies. However, RNNs have their own challenges, such as vanishing gradients and difficulty in parallelization. Temporal Convolution involves computing a temporal convolution of a kernel over past inputs. While it can capture temporal correlations, it often requires extensive memory resources and can be power hungry at inference time for the Edge.

    Temporal Event-based Neural Networks (TENNs) developed by BrainChip, which efficiently combines spatial (CNNs) and temporal (RNNs) convolutions to process sequential data like never before.

    Vision Transformers, or (ViT)s, are a type of deep learning model that uses self-attention mechanisms to process visual data.

    There are three AKIDA 2.0 configurations you can license E. S. & P. The one you license will be determined by your power and latency requirements.


    About 5 March, 2023 Brainchip released the AKIDA 2.0 E.S.P. TENNS & ViT IP to select customers.

    AKIDA 2.0 P. was released with a performance rating of 50 TOPS (Tera Operations per Second)

    Products from the 2nd generation platform were available for general release in Q3 2023.


    I can't draw the conclusion, from this data, that time is running out; quite the opposite, time has barely begun.


 
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