Artificial Intelligence
Advanced Heuristics &
Biomimetic Systems

Intelligent, Learning, Adaptive

3 0  Y E A R S  of  I N N O V A T I O N  that  C R E A T E S   S T A N D A R D S

Since the beginning at the National Press Club in Washington DC, Quantitative Technologies has been creating new standards in publishing and information technology.

In the 1980s we first innovated incorporating plastic records in magazines from digital technology which quickly became the standard. Soon afterwards we expanded to CDs and DVD technology in magazines which then become standards.

In the 1980s we also innovated the first digital layout and publishing system for magazines which has since become the defacto standard in publishing.

In the 1990s we innovated information security for the Internet and worked with Congress to make those standards for quickly and securely processing information over the Internet.

In the 2000s we were granted patents for information processing over the Internet which is in use today by most major banks, Amazon, Walmart, Microsoft, Apple and most every major company.

Since those early days, Quantitative Technologies has gone on to win awards in innovation from Intel, Amazon, Ford Motor Company, and Samsung among others.

Whatever we innovate, it becomes new standards to push industries forward.


A I   H E U R I S T I C S    T H A T    L E A R N    &    A D A P T

Technology & Engineering ...

Quantitative Technologies pioneered fourth generation, fully-autonomous, artificial intelligence. These AI's are capable of self-healing, self-monitoring and self-adaptation. They employ mission or objective based heuristics to make them highly adaptive in achieving their goals.

Many of our technologies and algorithmic systems have been licensed and used by banks, and other institutions, and are also incorporated into Microsoft Windows 10.

Our team is a multiple award winner in Artificial Intelligence from Ford, AT&T, Ericsson, Samsung, Amazon, Intel and also worked with Deutsche Bank, Citibank among others.

Numerous issued patents in algorithmic application which are licensed and used by every major bank.

We pioneered artificial intelligence in analyzing data using similar approaches for analyzing markets for predictive marketing analytics to learn what content drives customer interaction.


Industry-Leading Technology Innovation Awards in Artificial Intelligence...

Over the years we have been issued numerous patents for the technologies we have developed. Many have been sold to Microsoft and licensed to most major banks and are included in the current Microsoft 10. But the most rewarding has been the numerous awards we have been awarded from some of the largest Fortune 100 companies including Ford, Intel, Amazon, Samsung, Ericsson, among others.


Data & Computing Infrastructure

We maintain arrays of servers and data clusters colocated on the same trunks as the Department of Defense for resiliency and speed. In addition, we are located next to one of the few Super NAPs on the planet. The Super NAP we chose is Tier IV Gold, and is also used by the Department of Defense and other military agencies.

We maintain continuous analysis of most major markets for many of our clients, and offer those same data analysis and artificial intelligence deep analysis for lease. If you require detailed technical or fundamental market analysis, we can schedule analytics cycles for your tasks as well.

Omniscience Engine

The heart of any intelligence is the management system. Our systems use advanced algorithmic based, portfolio optimization technology that borrows from the latest academic research as well as traditional algorithmic and machine learning approaches. Our difference is that all the algorithms must compete against each other.

So each individual algorithm is constantly competing to show that they can generate more alpha from their management approach, better than their sibling algorithms. Then overseeing all the algorithms is the Omniscience Engine Artificial Intelligence. This AI sees all using advanced heuristics, and make the final determination based on which algorithms are generating the most alpha and profits. Then the Omniscience Engine AI constantly re-balances among the different algorithms using third-generation algorithmic rebalancing methodology to constantly shift the return curve towards optimal. The net result, is a smooth, consistent, and adaptive curve that optimizes for consistency, and risk control above all else. These systems are custom designed per client so as to not collide with other systems.



Cortical Arrays & Algorithmic Development

The challenge that most institutions face is the development of new algorithms, especially in rapidly shifting regime changes. Existing algorithms quickly lose their "edge", and developing new algorithms is time consuming, and cannot react quick enough with requirements of forward testing.

The Invictus9 Cortical Array is an array of hundreds of artificial intelligences working in unison, with each AI focusing on a particular objective, and a particular aspect of that market. Each AI utilizes machine-learning-heuristics to search for inefficiencies that can be harvested. All these AI's do so in real-time.

In addition, each AI spawns children. Each child splinters the aspect view of the market, further fine tuning, and at the same time searching for non-correlating inefficiencies for harvest. This leads to literally thousands of algorithms exploring hundreds of markets, and thousands of equities for inefficiencies.

The net result is real-time, and very rapid adaptive discovery of opportunistic AI based algorithms capable of producing solid results, and quickly adapting to whatever situation conditions change, in a matter of seconds.

This approach works very well on concert with the Omniscience Artificial Intelligence Engine to serve as a management algorithm to all the other AI's and their offspring.

Swarm Optimized Liquidity Solutions

The problem with many artificial intelligence approaches is the constant trade-off between scale, and liquidity.

To solve this problem, here at Invictus9, we approached the problem from a different perspective, using the biomimetic approach of swarm optimization. In essence, splintering a single trade in to hundreds, and thousands of execution components. The result is a collection of "approaches" or executions that are now in essence a swarm of executions.

This was originally done to solve the problem of limited liquidity. By splitting a single objective into a swarm of smaller objectives, you could then execute at much higher liquidity with minimal impact on performance.

Now you have a collection of executions that are each given their own intelligence (AI). So each AI becomes a member of the swarm, with the intention of executing in the market at the most optimal price. In the same way that millions of birds cannot fly through a tunnel at the same time, thousands of executions cannot happen at the same time without colliding with liquidity issues.

With swarm optimization, each execution thinks and behaves independently. Imagine tens of thousands of bats, flying out of a single hole in a cave. Each bat arranges it's location, and exit based on the bats around it, and the exit. In addition, each bat is communicating it position, location, trajectory to all the other bats. These AI's behave the same way, communicating with each other, and finding the most optimal time and size to enter, or exit the market.

The net result is the ability to execute in limited liquidity with higher orders of magnitude.


Advanced Swarm Optimized Alpha Systems

One of the most powerful techniques that we have discovered, and has provided a strong, consistent results in all markets  has been an advanced form of swarm optimization. By combining swarm optimization and hive intelligence, has allowed hundreds, and thousands of individual algorithms to use seek and hunt patterns to search out different markets, different approaches among different time horizons, each in search inefficiencies that can be harvested.

The use of Hive Intelligence has made the swarm incredibly effective and efficient. By enabling all the individual drone algorithms to communicate with each other, they are able to coordinate themselves. So when one set of algorithms finds opportunity, it notifies other algorithms to join them in their search patterns.

The net result is a system, or hive, that can quickly adapt to changing conditions, and more so, can actually profit through close coordination, and actually generate more results than would normally be harvest-able.

Hive Intelligence Biomimetic System Design

Everything we do involved, massively scaled artificial intelligences. To solve the problem of inordinate computing power requirements, doubled with the highly dynamic requirements, of sometimes being mostly idle, to sudden condition changes moves requiring exponential computing requirements, we combined biomimetic hive intelligence with a queen intelligence. It proved to be shockingly adaptable, and able to efficiently allocate computing resources beyond our wildest hopes.

In essence, each computing unit, or server is considered a drone. As a drone, it is capable of doing any task requested of it by the queen. Therefore, each server is adaptable, at a moments notice. The queen computing unit is capable of spawning (spinning up additional servers) at will.

So the queen, being aware of all of her drones, can allocate computing resources as needed. Under times of duress (or learned times of expected duress), she can request that additional drones be spawned in anticipation, and then released when no longer needed.

The system is highly adaptable, and incredibly resilient. Failures of single servers have no meaning, since other drones are always available to accomplish tasks. Finally, drones are capable of mutating into "daughter" servers, which can become queens if the queen becomes overtaxed, or damaged.

This highly adaptable, and nearly impervious approach is incorporated into all our engineering and infrastructure designs.