When I first broke into the data world, tools like Tensorflow, Caffe, and Theano were growing in popularity.
In addition, I had taken several courses in neuroscience, bioinformatics, and computational neuroscience.
Culminating in immediate interest in the subject of neural networks and machine learning. Now a lot…and I mean a lot has changed since when I first even heard of these topics.
Each passing year brings further advancements and changes in what we think and know is possible using AI and ML.
In this article, I wanted to review one of my older articles where I discussed some of the foundational research that built up our understanding around some of these concepts in computer vision as well as discuss ChatGPT.
It’s hard not to jump on the hype train…
From Neuroscience To Computer Vision
Like many students in college, I spent a good amount of time taking electives that had nothing to do with my major. In particular, I decided to take a few random neuroscience courses where we read through papers and discussed their impact on our understanding of how the brain translates and interrupts signals.
Eventually when I did start writing on data, one of the first articles I put out reviewed these papers and how they built upon each other and led to computer vision as we know it now(now being 2016).
Keep reading with a 7-day free trial
Subscribe to SeattleDataGuy’s Newsletter to keep reading this post and get 7 days of free access to the full post archives.