Hi guys,

What do you think of a system that can interact with AIs in many different ways, depending on the type of inference method used and specificity of application.

In a paper - technology overview,  we read:

“We can name three main modes:

Training data acquisition and processing

In this mode Bitlattice performs an initial gathering and processing of data that is later fed to an AI solution. Primarily in the ones based on neural networks several steps must be accomplished before the actual training can begin. Simplifying, those steps can contain normalization (making data homogenous), feature extraction (gathering prominent patterns) and classification (assigning meanings to patterns). Bitlattice can perform them in one pass while processing incoming data. The added values of using Bitlattice, apart from preparation, are potentially large data gathering network and possibility to decouple actual data from symbolic description passed to AI. Globally accessible training dataset is one of interesting potential applications.

Output storage and processing.

This is a rather obvious consequence of Bitlattice being a distributed ledger. Actually distributed ledgers at the moment do a similar job, but using mostly natural (human) intelligence as input. Bitlattice in this mode could accept input from multiple AIs and offer an aggregated and/or processed output. At that point the latter can further deterministically classify, the data provided by AIs and produce a conclusion. Given a large scale and a large number of AIs that could minimize risk of residual poisoning of training data and other forms of manipulation. That mode could also serve to combine different observations using strict criteria.

Active component

The compartments that Bitlattice stands on, expose a set of metrics that facilitate operations. Those metrics can also be used as an input for AIs. As they are uniform, there is no need to normalize them. They carry a general picture of the data stored in a compartment and therefore can be used by AIs to infer about the data structure and dynamics.

Artificial intelligence itself.

This is probably the most interesting mode. While Bitlattice’s middle layer works like a decision tree, other strategies can be implemented as well. Simplifying again, distributed ledgers are networks of peers, but to become neural networks they would need several additional properties, like layered organization, persistent neurons, defined excitation levels, etc.

Bitlattice has or can have implemented instrumentation needed to act as a neural network. That idea is wild, but ultimately possible and potentially beneficial. While the global wide network in this mode won’t be fast (due to physical limitations of signals speed and delays of network) the fact that the middle layer contains far less nodes than actual number of participating devices makes that idea at least possible to implement. The practical aspect here could be, for instance, making a “feeling planet” like project.

The above modes can also be mixed and extended, as the domain of AI is very wide and provides plenty of different tools to experiment with.”

What is your opinion?