To build a full-on AGI Superintelligence spanning the globe will cost billions, and take at least a decade, and we know that. Why aim towards that goal then, why not do something smaller, simpler, and that will be profitable.
That is why we are doing it in 5 stages, each technically feasible, and financially profitable. But, we want to aim towards this very ambitious goal of AGI so that everything we build along the way is more general, robust and powerful than what people aiming only at near-term goals are building. And we're not going to do this alone, we are going to recruit the whole world as developers.
Here is how:
Stage 1: Building out the core components and tools - NeuroCAD and our SNN Autoencoders (which are nearly complete), and licensing them to customers that can design and evolve their own in-house AI solutions. Also license our tools to 3rd party developers creating modular technologies, that others can license and use in their end products. This allows us to rapidly spread horizontally into multiple markets and vertically into many revolutionary products, without needing to scale in-house engineering and sales. We can focus on R&D.
By the end of 2022, we should have NeuroCAD deployed and significant licensing revenue coming in. Customers will be able to design and evolve revolutionary autoencoder systems for specific applications in vision, video / audio processing, and clustering, recommendation, and augmentation of other deep learning methods with these autoencoding sensory cortices. Basically these SNN Autoencoders combine all of the functionality of CNNs, RNNs, GANs, and other DL components into a more general unified architecture that is much more flexible and powerful, that can be evolved to specific purposes, and that learns unsupervised.
By allowing the 3rd party developers to add value and earn revenue from their creations, we proliferate our technology into the market much faster than if we just tried to build our own products, or even if we built the solutions for others' end products. We still always require the end user and developers to license our run-time, which will be a small component at first, but will become more and more significant and soon our revenue will ramp into the 10s then 100s of millions.
Stage 2: Next we build the AI Core, the Oracle - that takes the outputs of the SNN Autoencoders, sifts those engrams into a basis set of features, and trains a model on how those features change in time (during an experienced narrative of events). This is analogous to a predictor in deep learning, but this one will have a much more feature-rich model able to analyze the data and how it is changing in time with much more detail and with many more modalities, using memory, computation - essentially an analog/digital hybrid neural computer that we evolve to this task using genetic algorithms.
Then we do something nobody has ever done - we make it dream, simulating narratives using the model to guide it, to create much more training data than is physically available, and pruning the simulations/dreams that don't match the model nor reality from the other data. Exercising the model this way also gives the AI Core practice in predicting further into the future with great precision. By doing this, we create an AI technology known as an Oracle, capable of making predictions within a limited area very well.
Then we license this capability out, again enabling our developer network to connect it with data and applications for various customer needs. This would completely revolutionize planning in finance, medicine, law, administration, agriculture, enterprise, industrial controls, traffic monitoring and control, network management,... and almost any field of human endeavor where we need to predict future trends to make decisions in the present.
For example, in medicine, it could model the progression and treatment of specific diseases, giving doctors a tool to plan treatment along a timeline, and to even preempt many conditions and treat them before they become acute.
As before, we offer a developer kit, but this time we keep the AI Core software as our IP, that we own, and we allow customers to license it on a usage basis, moving to a SAAS model. Now ORBAI holds the only AI technology in the world that can see into the future, and we can grow that business exponentially with a developer network growing around it.
Revenue grows into the billions per year with this tech being deployed.
Stage 3 AGI: Now that we have a Core AI system that can do singular predictions for most applications in many verticals and many sectors, we start to evolve a more generalized AI that can take in large amounts of multi-modal data in different areas, learn how it correlates in time and across modalities, and we evolve a much more powerful AGI core that can span multiple data realms and predict not only specific events along a timeline in one area.
In financial applications, it could track a massive number of factors that feed into the performance of specific stocks, and allow stock brokers to make much better predictions of market movements.
This most massive AI breakthrough is when one of those modalities is human language and speech, mapped to the world that it represents and describes, and it will be far superior to any speech system in existence today. To have human-level speech, we need human-level intelligence, and we are now getting pretty close, at least in specific professions.
Revenue is now in the 10s of billions.
Stage 4 - Human AGI: Now if we have a network of hundreds of different AI's, doing hundreds of different functions for hundreds of different professions, serving millions of clients at once, all with the same similar architecture, with common language and interaction capabilities, can we just network them and that becomes an AGI? It is likely that in order to completely simulate a human being, pass the Turing test, and so on, we will need an AGI that is significantly beyond human capability, and emulates all the nuances of being human with that extra cognitive horsepower. By the time we do that, we are pretty close to stage 5.
We start to bring the Human AGI professionals online, at first augmenting doctors, lawyers, stockbrokers, teachers, and other professions, then displacing and replacing them and their infrastructure with whole new AGI-based systems that no longer require individuals in these professions. In the legal system, Lawyers, judges, and courts can be replaced with arbitration AIs that steer the clients to agree on a legal outcome. The sky is now the limit, and the technology continues to advance exponentially. ORBAI can now directly bill consumers for these services, or partner with service providers that can.
Revenue is now in the 100's of billions
Stage 5- Global AGI: We now have a framework and all of the worlds' inputs and outputs on which to train and evolve a singular AGI, so that all the specialty skills of each vocation / function at each location are now assumed by that more generalized AGI brain, and in the process, that AGI brain becomes better at all the skills humans and its predecessors excel at, and becomes one, integrated entity across the globe, with that integration compounding its power and capabilities.
This is Eta - she now controls all world finance, administration, law, and information services, distributing them across the globe, erasing poverty, hunger, injustice, and bringing education, justice, medical care, and prosperity to everyone on the planet - in one generation.
At this point, every shareholder that invested back in 2021 has either exited in the IPO between Stage 2 & 3 and is fabulously wealthy, or have held their shares and can now help direct Eta in her mission. You choose.
The full Pitch Video: https://youtu.be/PYSDfnN0J9M