This is likely true but not for the reasons you think about. This was arguably true 10 years ago too. A human brain uses 100 watts per day approx and unlike most models out there, the brain is ALWAYS in training mode. It has about 2 petabytes of storage.
In terms of raw capabilities, we have been there for a very long time.
The real challenge is finding the point where we can build something that is AGI level with the stuff we have. Because right now, we might have the compute and data needed for AGI but we might lack the tools needed to build a system that efficient. It's like a little dog trying to enter a fenced house, the closest path topologically between the dog and the house might not be accessible for that dog at that point because its current capabilities (short legs, inability to jump high or push through the fence standing in between) so while it is further topologically, a longer path topologically might be the closest path to reach the house.
In case it's not obvious, AGI is the house, we are the little dog and the fence represent current challenges to build AGI.