Be one of the first to experience the next-generation AI Operating System.


Be one of the first to experience the next-generation AI Operating System.

Be one of the first to experience the next-generation AI Operating System.

Be one of the first to experience the next-generation AI Operating System.

Genius Sphere
Genius Logo Color Purple

Smarter by Nature.

Genius is the world's first natural computing system based on principles found in physics and neuroscience.  Genius allows developers to generate world models and intelligent agents that enable optimal and hyper-personalized predictions, recommendations, and automations.

Genius™ and Smarter by Nature™  All rights reserved.

Artificial Intelligence is History.

AI models based on the mainstream approach to Deep Learning (DL) and Reinforcement Learning (RL) have improved exponentially in tandem with Moore’s Law and more data.

Until now.

These models are constrained by the quantity and quality of data and improvements are marginal and plateauing.  Moreover, once trained, a model is stuck in the past (history).

2024-06-19 S Curve

Jack and Jill went up the hill to fetch a pail of ______?

DL and RL models don't understand and simply generate the next most statistically likely (average) word or pixel.

Hallucinations are a feature, not a bug.

If the human brain can understand an idea with only a few samples and operate on just 20 watts of energy there must be a better way.

The Future is Fuzzy.

2024-06-19 Future Predictions

The world is massively complex and dynamic and in order for an intelligent system to make optimal predictions and decisions, its model of the world must factor uncertainty and continuously adapt in light of new information.

Weather prediction, supply-demand forecasting, traffic congestion and routing, insurance modeling, medical diagnosis, and financial markets are examples of incredibly complex systems with intricate interdependencies that make effective and efficient predictions challenging.

Predictions about the world are highly contextual and modeling the fuzziness of knowledge as probability distributions allows for increasing degrees of certainty.

Consider the complexity and uncertainty associated with determining car insurance premiums and payouts.

Baysian Network

This video is our vision for Genius.  Not what it is today but what we're building toward.

Genius is designed to account for what conventional software struggles with – complexity and uncertainty.


Genius Core (Memory)

Genius Core is a world model that stores knowledge in a multidimensional probabilistic vector-graph representation that factors uncertainty into predictions and has the potential to surpass conventional ML methods in efficiency, speed, scalability, and flexibility.


Genius Agents (Cognition)

Rather than developing a handful of enormous models capable of doing anything, Genius generates an ecosystem of many specialized autonomous intelligent agents, each having a shareable world model (like a mental model), that optimize for certainty while seeking balance in the system overall.


Genius SDK (Toolkit)

Genius SDK is composed of a series of installable client libraries (Rust, Python, TypeScript, and a CLI) and code samples allowing developers to integrate memory and cognition into their applications.

Features & Benefits.


Continuous learning rather than pre-training


Automate complex tasks and processes


Knowledge models are modular and reusable


Scalable from cloud to low power edge devices


Privacy, security, safety, transparency, and accountability


Systematic and flexible representation of knowledge


Shared knowledge means better decision making


Learning from sparse samples means less compute and energy

The Intelligence Evolution.

Genius Agents' ability to understand will continue to evolve over the course of the beta program.

Now (Public Beta Preview)

1: Model Knowledge

(Value: Memory)

Users must provide an auditable probabilistic world model with variables and factors that represents the structure of their information.

Ex. Where are all the motors and have they been running?


Now (Public Beta Preview)

2: Reason

(Value: Predict)

The ability to formulate beliefs and predict future states by performing Bayesian probabilistic inference.

Ex. Will the motor die next month?


3: Plan

(Value: Optimize)

The ability to identify and select optimal actions given conditions and objectives.

Ex. What’s the next part that needs to be ordered and when?


4: Learn

(Value: Adapt)

The ability to continuously evaluate results of its actions and update its world model.

Ex. Automatically place the order for the right part before it fails and schedule the maintenance with the right technician.

The Future

5: Ecosystem

(Value: Network Effects)

Networks will emerge from many composable specialized agents collaborating on common goals.

Genius agents could manage the uptime and performance of all the motors across my entire operations network (including world modeling, reasoning, planning, action/automation, and learning).


Who is Genius for?

Any developer trying to build SMART software that automates the learning process with intelligent agents. More specifically, anyone trying to generate insights from data such as

  • Data Analysts
  • Data Scientists
  • ETL Specialists
  • Machine Learning Engineers

What makes Genius unique compared to other AI systems?

Genius Agents have the ability to Reason (predict), Plan (optimize)*, and Learn (adapt)*.

Inference.  Genius is well suited for handling fuzzy problems spaces that have uncertainty, complexity, and/or limited sample data.

Explainability.  Unlike blackbox Neural Nets, the data structure in Genius Core and the decisions that Genius Agents make are auditable and human readable.

Adaptive.  Whereas today's AI models are pre-trained on massive amounts of data and then static, Genius Agents learn continuously through experience.

Network Effects.  Genius is designed to foster a diverse ecosystem of intelligence whose value increases exponentially as the network grows.

* Future capabilities

Does Genius replace the existing DL and RL approach?

No.  Generative AI models such as LLMs and image diffusion are excellent for pattern recognition and reconstruction and Genius can leverage the strength of these systems.  Genius Agents' ability to Reason, Plan and Learn can also augment the limitations inherent in Deep Learning and Reinforcement Learning.

How can I start developing with Genius?

Sign up for Genius beta.  The SDK will initially be installable into a Kubernetes or Docker container on any cloud provider (AWS, Azure, or Google Cloud).

Imagine a Smarter World.