- All conventional data analysis methods involve uncertainty. These methods support Artificial Intelligence strategies, so the resulting uncertainty can be risky and dangerous.
- Ingobert Schmadel and his team at Inora Technologies Inc, USA, are deploying Organic Intelligence Core Technology (OICT).
- OICT analyses raw data without assumptions or approximations. It offers better clarity by providing absolute certainty, eliminating the need for inaccurate learning and ‘best guesses’.
- Importantly, this groundbreaking technological advancement assesses a true picture of reality.
Conventional data analysis methods, including least squares, best fit, Bayesian and machine learning (ML), all involve uncertainty. Every one of these methods uses assumptions, estimations, approximations, and/or alignments (either mathematical or physical) to ascertain their results. These methods underpin current Artificial Intelligence (AI) strategies, and the ensuing uncertainty can range from risky to dangerous, particularly when it comes to autonomous solutions. Science and industry are therefore constrained by numerically uncertain methods. Information regarding the quality and status of processes and their efficiency are trapped within a guessing game.
Frustrated by the uncertainty of this guessing game, Ingobert Schmadel, Founder and President of Inora Technologies Inc, and his team have commercially deployed Organic Intelligence Core Technology (OICT). OICT software is a groundbreaking technological advancement, a newfound universal metric that has multi-level applications in both software and hardware solutions. This Organic Intelligence (OI) powered absolute analysis technology can determine the quality and efficiency of any process in real time with 100% accuracy. Navigating this route out of uncertainty was a complex journey that took over 30 years of scientific research, development, and programming.
What is Organic Intelligence?
Unlike traditional data analysis, where the data is normalised or filtered and essentially altered, Organic Intelligence is a numerical software technology that uses raw data. OI doesn’t require the data to be altered prior to processing.
Organic Intelligence can assess a true picture of reality, offering better clarity while providing absolute certainty.
There are no assumptions, models, filters, or uncertainties used in the OI data analysis process. As a result, OI can assess a true picture of reality, offering better clarity while providing absolute certainty.
Numerical Balancing
OI’s Numerical Balancing applies Newton’s third law – ‘for every action there is an equal and opposite reaction’ – in a numerical way. OICT determines the exact structure of any dataset and calculates the opposite face of the input data structure, providing the perfect numerical equilibrium.
The Inora team found that every data point in any dataset has its own unique geometry and weight regardless of the number of variables and observations. OICT computes precise geometric weight values for every point in relation to the other points in the data set and establishes the unique centre of equilibrium for the entire dataset. Reversing the geometry and weight information for each point offsets the geometrical influence and defines the condition of numerical equilibrium for the dataset.
Discovering the Inner Reference
The researchers discovered that every time numerical equilibrium is reached, all the resulting balance points, which are the centre points between the input and inverse data points, form a perfect, ideal geometry. This is always the same shape – a perfect hyper-ellipsoid (a stretched or squashed sphere). The team refer to this ideal condition of a constant proportion between all variables and observations in any point cloud as the Inner Reference.
Reflecting Newton’s viewpoint: ‘There is absolute perfect geometry in everything. If we observe a perfect result, we know we have a true value in our calculation,’ the discovery of this true value, the Inner Reference, shows that an ideal condition can be determined in anything.
Numerical Certainty
Schmadel reminds us to ‘always remember, there is only uncertainty or certainty, nothing in between.’ Conventionally, uncertainty is due to the assumptions, perspectives, estimations, and mathematical alignments that underpin traditional data analysis methods. OICT is unique in accomplishing Numerical Certainty with complete numerical symmetry in equations and complex scenarios.
The scientific discovery of the Inner Reference is remarkable. The fact that a true value can be found in anything means that there is only one objective data analysis result for any given dataset. Instead of best guesses, OICT is enabling new laws of mathematics that can determine reality with certainty.
Validation
True validation uses an alternate method, known as the dual, to prove the results of a particular calculation, known as the primal. For example, we can validate the primal multiplication: 2×3=6 using addition as our dual: 2+2+2=6. Unlike other numerical data-processing methods, OICT has built-in self-checking systems. Its procedures are all carefully controlled by strict, primal-dual validation with every step validated using an alternative numerical method, so the final result is validated and reliable. This offers users the confidence that is only associated with absolute mathematical proofs.
An Antidote to AI and Machine Learning
It’s important to differentiate between OICT and existing AI/ML tools. Currently, all machine learning algorithms rely on assumptions and estimations. This always leads to uncontrolled uncertainty.
The Inora team believes that while AI/ML is marketed well, it has limitations. OICT offers a better solution without estimations and assumptions, so the raw data is not altered, and a true picture of reality is visible for assessment. Applying controlled and validated OICT methods make it possible to control AI processes. Accurate decisions can be made instantly, and no learning is required, so ML is no longer needed. OICT is also ideal for the goal of Artificial General Intelligence (AGI) applications (a theoretical form of AI aiming to create software with human-like intelligence).
The Sky is the Limit
OICT is a unique new approach that offers a universal metric. It provides a neutral numerical platform and delivers numerical certainty on any dataset. This technology accepts inputs from any numerical system, coordinate system, unit of measurement, or kind of digital processors.
Always remember, there is only uncertainty or certainty, nothing in between.
OICT offers an approach to both the physical world and meta-physical world. It is a key instrument for understanding everything with unlimited applications. It is already embedded in Inora’s products that are used in the manufacturing, automotive, and aerospace industries, shedding light on the core issue of uncertainty.
What inspired you to use Organic Intelligence to avoid the issues surrounding uncertainty?
I was always inspired by the search for Inner Peace, with no clue where to find it. Through the numerical work with Professor Kampmann, it became logically clear that truth can be found in everything. For me, it is the key to living life in clarity and towards a balanced, ideal behaviour. Truth is all that matters, it is the antidote to issues created by uncertainty.
What were the most challenging aspects you faced as researchers developing Organic Intelligence Core Technology?
We had to go all the way back to where most researchers do not want to go. The areas where problems are still deemed unsolvable and mathematics follows assumptions rather than true logic. There were a myriad of numerical problems to overcome, which is why 30+ years went into the core scientific research, development, and programming of OICT.
What has been the most satisfying aspect of this research?
The discovery and existence of the Inner Reference, which can be used as a true orientation of life in general. The fact that OICT can be applied digitally on edge devices, without the need for cloud computing, to solve problems in any field is satisfying.
Can you describe some of the real-world applications of OICT? How do you envision it can be best used?
Currently, OICT powers Inora’s products in the manufacturing industry. Some examples are numerically certain corrective feedback for real-time control of processes. This saves time and money, and delivers reliable confidence. Looking to the future, we are most excited about deploying OICT in medical applications which are dominated by averaging models and assumed references instead of accurate, individual, and holistic assessments – for example, moving away from normalised/statistical thresholds based on large groups of people and instead moving to personal holistic and numerically certain baselines derived from the Inner Reference.
What advice would you give a young researcher who’s interested in a career in Data Analytics and Software Development?
There is an exciting new time of enlightenment coming with OICT. Specifically, young researchers can go into their scientific field of choice and find new knowledge by applying this new, objective perspective.
