nikhilsimha
Joined 12 years ago
Joined 12 years ago
It is used to serve features/context to ML/AI models and rule engines, along with app views.
We are more scale and perf oriented as project given the use-cases and less decentralization oriented.
We also ship with a dataframe / prql like declarative api.
the idea is to observe with clarity the counteraction and let the sharp sensation arise and pass without the counteraction/resistance.
It could very well be that the internal mechanism of our thought has an auto-regressive reasoning component.
With the full system effectively "combining" short term memory (what just happened) and "pruned" long-term memory (what relevant things i know from the past) and pushing that into a RAW autoregressive reasoning component.
It is also possible that another specialized auto regressive reasoning component is driving the "prune" and "combine" operations. This whole system could be solely represented in the larger network.
The argument that "intelligence cannot be auto-regressive" seems to be without basis to me.
> there is strong evidence that not all thinking is linguistic or sequential.
It is possible that a system wrapping a core auto-regressive reasoner can produce non-sequential thinking - even if you don't allow for weight updates.
For example - max over {4, 5} is 5. Now I update the 5 to a 3, so the set becomes {4, 3} with a max of 4. This seems to imply that the z-sets would need to store ALL the values - again, in their internal state.
Also there needs to be some logic somewhere that says that the data structure for updating values in a max aggregation needs to be a heap. Is that all happening somewhere?
Somewhere in there is a definition of commoditization.