Alt Text: an image of Agent Smith from The Matrix with the following text superimposed, “1999 was described as being the peak of human civilization in ‘The Matrix’ and I laughed because that obviously wouldn’t age well and then the next 25 years happened and I realized that yeah maybe the machines had a point.”
Assuming that the path to AGI involves something akin to all the intelligence we see in nature (i.e. brains and neurons), then modern AI algorithms’ ability to simulate neurons using silicon and math is inarguably and objectively a precursor.
Machine learning, renamed “AI” with the LLM boom, does not simulate intelligence. It integrates feedback loops, which is kind of like learning and it uses a network of nodes which kind of look like neurons if you squint from a distance. These networks have been around for many decades, I’ve built a bunch myself in college, and they’re at their core just polynomial functions with a lot of parameters. Current technology allows very large networks and networks of networks, but it’s still not in any way similar to brains.
There is separate research into simulating neurons and brains, but that is separate from machine learning.
Also we don’t actually understand how our brains work at the level where we could copy them. We understand some things and have some educated guesses on others, but overall it’s pretty much a mistery still.