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matrix multiplication

Where Do the MACs Come From?

By Bryon Moyer | July 10, 2020 | 0 Comments

[From the last episode: We looked at the convolution that defines the CNNs that are so popular for machine vision applications.] This week we’re going to do some more math, although, in this case, it won’t be as obscure and bizarre as convolution – and yet we will find some […]

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convolution

What the Heck Is Convolution?

By Bryon Moyer | July 3, 2020 | 0 Comments

[From the last episode: We looked at CNNs for vision as well as other neural networks for other applications.] We’re going to take a quick detour into math today. For those of you that have done advanced math, this may be a review, or it might even seem to be […]

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CNN

CNNs and Other Networks

By Bryon Moyer | June 26, 2020 | 0 Comments

[From the last episode: We looked at the common machine-vision application and its primary .] We’ve seen that vision is a common AI these days, and we’ve also talked about the fact that our spate of neural networks are not neuromorphic – that is, they’re not modeled after animal brains. […]

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machine vision

Machine Vision: AI’s Big Win

By Bryon Moyer | June 19, 2020 | 0 Comments

[From the last episode: We looked at the difference between training and inference for ANNs.] One can do many, many things with AI. But of all of the applications, vision has been the most… well, visible. Another popular application – so-called predictive analytics – is used by the social media […]

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neural nets training inference

The Two Main Machine-Learning Functions

By Bryon Moyer | June 12, 2020 | 0 Comments

[From the last episode: We looked at artificial neural networks as a practical solution that’s come available ahead of neuromorphic networks.] We talk about AI as allowing machines to make decisions. While that might be true, it’s an imprecise description of what goes on. There are two main jobs that […]

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