[civilitty]

Agreed. Reading the GP’s comment it feels like it’s from bizzaro world. It’s the computer scientists who have been claiming that neural networks resemble the human brain - they even fucking named them neural networks for christ’s sake! That could be excused as naive hubris in the 1980s, it’s utter delusion now.

A surface review of neuroplasticity literature alone should free anyone of the illusion that “neural networks” have even a passing resemblance to biological neurons, something covered in neuroscience 101 and is widely internalized by its practitioners. The BS grant writing and PR scientists have to participate in is hardly reflect of state of the art science itself.

The irony is that machine learning methods are a perfect fit for neuroscience and biology in general which generates reams of data that is largely so multidimensional that manual analysis is intractable. What we’re seeing now is the crest of the academic hype cycle which - if the history of bioinformatics is anything to go by - means that ML will take years if not decades for the field to understand and filly utilize.

[bjourne]

Actually it was neuroscientists that developed the models nowadays used for machine learning. The McCulloch-Pitts neuron model introduced in 1943 which lead to Frank Rosenblatt's perceptron introduced in 1958. Machine learning algorithms mostly still use those models but computational neuroscience has progressed towards much more complicated neuronal models.