Extracting Profits From Crypto-Currencies | Running Alpha Opens New Ground in Data-Driven Decision-Making: Introducing AI-Powered Quantum Machines
by efrem on Tuesday December 12, 2017 at 10:41 pm EST | Tags: AI, Algorithms, Alternative Data, big data, Bitcoin, Cryptocurrency, machine intelligence, Running Alpha, trading
Running Alpha is the first AI-Powered Algorithmic Machine Intelligence Framework that was designed from the ground up to:
organically simulate how nature uses quantum computing principles for circumventing the constraints of processing exponentially big chunks of classical data ( visible information ) in real-time.
In-house proprietary technology is used for transforming data into an encrypted superposition of quantum entangled states — each representing the observed event from a unique viewing perspective; independent of human or machine observation.
Adapted from the founder’s U.S. patents on Autonomous Hierarchical Assemblies of Artificial Neural Networks — for giving early warning of tornado outbreaks from 3D atmospheric radar imagery — the parameters underlying the conversion process were discovered.
Up until now, conventional machine intelligence can only learn by example in sequence; and because they require a very large number of past examples to recognize variation and identify change, many of today’s newer data sets of finite length impose a roadblock to innovating data-driven applications.
Even in those situations where the data history is not limited, legacy classical algorithms are unable to leverage the capabilities offered by Running Alpha’s massively-parallel one-shot training process (self-generated), which takes into account gauge symmetries — the unchanging geometric relationships among the viewing perspectives (quantum states) that lead to emergent structure in the real-world; and as such, traditional AI platforms are ill-designed for detecting anomalies in data we have never seen before.
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