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Update taxonomy.qmd #24

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7 changes: 3 additions & 4 deletions taxonomy.qmd
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Expand Up @@ -1183,8 +1183,7 @@ crucial discoveries. We will include those references throughout the
book and we will just paint here, with a few coarse strokes, the main
directions in the field.

In 1963, at MIT, Larry Roberts became the first computer vision Ph. D.
entitled @Roberts63.
In 1963, at MIT, Larry Roberts became the first computer vision Ph. D., with a thesis on @Roberts63.
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thanks!


:::{.column-margin}
Larry Roberts did his Ph.D.
Expand Down Expand Up @@ -1331,7 +1330,7 @@ It wasn't until the 1980s that interest in learning algorithms, and
neural nets in particular, began to surge again. The reason was because
researchers showed that perceptrons could be stacked to create systems
capable of complex operations, including logic. These systems were the
precursors to the **deep learning** systems that are dominate today. In
precursors to the **deep learning** systems that are dominant today. In
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thanks!

this decade, several architectures specific to vision were also
introduced, including Kunihiko Fukushima's , which was a precursor to
modern convolutional neural networks @fukushima1980neocognitron. In
Expand All @@ -1353,7 +1352,7 @@ distributed processing in artificial networks.



Unfortunately, however, at that time we did not have the compute and
Unfortunately, however, at that time we did not have the computers and
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@shensquared shensquared May 15, 2025 •
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I believe the intended word is likely 'compute', as in 'computational power' or 'compute resources' (since computers were readily available in academia by the 80s/90s.) I'll leave it to the author to weigh in.

data necessary to make these systems really work, and interest waned
during the 1990s. By the year 2000, the field of AI as a whole was
firmly in a "winter"; the promises of the 1980s had failed to
Expand Down