Unstructured Complexity: Why It Is hard for enterprises
Unstructured data makes up the majority of enterprise data. Examples include e-mail, scanned documents, PDFs, transcription of phone calls, chat logs, policy documents, and spreadsheets from various teams over time. Typically, structured databases have different formats, rules and definitions. AI systems cannot make predictions based on unstructured data from multiple different sources without context; therefore the outcome is unpredictable.
Many organizations are under the impression that smarter AI models will address these issues. While it is true that smarter AI models improve prediction capabilities, even the best AI reasoning systems will fail when fed with inconsistent, incomplete, or poorly governed data. The result will be that decisions can’t be relied upon and AI will slowly lose its credibility.
Structured reasoning is critical in addressing the issues that come from the variability of unstructured data. Structured reasoning does not mean limiting AI. Rather, it provides a helpful framework for AI to build relationships, context, and consequences like a human does when making decisions.
What Is DEE and Why It Matters
DEE stands for Deep Extraction Engine; it is Tecosys' patented technology that is designed to solve enterprise reasoning problems. It works behind the scenes, in conjunction with AI models, to control how the interaction between the data, memory, and reasoning occurs.
While DEE does not produce answers, it provides AI models with the tools to receive clean, consistent, and organized-input; track and monitor-output; and evaluate the output produced by AI models. The above results in AI making decisions that are increasingly reliable, auditable, and thus, trustworthy. With DEE as a foundation for an enterprise's reasoning engine, organizations can evolve from using AI experimentally, to transitioning to the production-ready cognitive reasoning system where AI can safely operate over extended periods.
Aggregating and Cleaning Enterprise Data
DEE's ability to aggregate enterprise data within a central perspective of the 'one' view is the most critical function of DEE. In most organizations, there is a large amount of enterprise data: enterprise sales, customer support, and compliance have been traditionally held in separate places, systems, and platforms. DEE will consolidate enterprise data and format; standardization; create one complete, one version of the truth; by eliminating discrepancies and repeat data.
Thus, Clean Data will produce better reasoning: clean data provides the basis for accurate predictive models, informed decisions, and consistent recommendations made by AI. Thus, without taking into account clean data, even the most complex AI will be unreliable.
Structured and Unstructured Data Working Together
Most of the time, AI fails when it comes to dealing with both types of data simultaneously. For example, a single policy document may read one way, while a single database record may read the opposite. Hence, AI systems have difficulty determining how to reconcile this information.
DEE will combine and logically associate the extracted meaning from Unstructured Data with the meaning of Structured Data. AI can reason on documents, numbers, history, and rules by processing them all as part of one system in this manner.
By utilizing this way to structure information, the features and functionality of DEE provide the potential for true cognitive reasoning, where AI not only understands facts but also understands how those facts relate to each other and what they imply.
Secure Reasoning Environment Creation
Security and compliance are critical considerations in industries, such as finance, health care, insurance, and legal services. All AI systems operating within these types of environments must adhere to strict guidelines concerning the protection of private data, the ability to control access to that data, and the ability for users to audit that access.
With this in mind, DEE has been designed with these requirements in mind. DEE establishes a secure reasoning environment, where sensitive data is protected, controlled access to sensitive data is provided, and every single step in the reasoning process can be traced back.
Whereas an AI system that does not explain why it made a particular decision would be considered a "black box," DEE enables organizations to understand why the decision was made, what data was used in making that decision, and how the reasoning process evolved over time. This level of transparency enhances trust in the AI solution for regulators, customers, and internal stakeholders.
DEE as the Foundation for AI Reasoning System
DEE serves as the foundational element for advanced AI reasoning systems, such as Tecosys' patented Nutaan H-RAM.
To reason like a human, an AI must have memory. To reason effectively, an AI must learn from previous experiences, while still retaining that earlier knowledge. Finally, the AI must be able to manage corrections to previous reasoning in a responsible manner and not just overwrite them.
DEE provides the means of storing and processing memory so all memory is in a hierarchy -- where important memory is always present while temporary memory ceases automatically.
The log of corrections will provide a record of the correction and create a trail of the reason behind the correction and how it happened, so there are no unknown changes.
Because of this log, AI systems can continue to learn and improve over time while retaining both reliability and consistency.
Preserving Learning Without Breaking Consistency
Another major threat to AI systems is unregulated learning. With AI, there is no way to predict behavior when learning is done without some form of control. An organization may see a dramatic change in AI recommendations or decisions based on insufficient data or inadequate information.
With DEE, an organization will not experience uncontrolled changes since learning is captured in a controlled environment. Every change made to the AI is logged. Thus, there are records and visibility of what occurred before the AI changed.
Humans learn in this manner. We do not "forget" our experiences; we learn from them. DEE supports this method of learning for AI and provides long-term reliability and confidence in AI-driven solutions.
Enabling Enterprise-Scale Performance
Large organizations have thousands of AI transactions per company per day across many departments and locations. In addition to infrastructure issues (e.g., multiple systems), this creates problems because of slow downs, conflicting data, and fragmented knowledge.
Systems need to have the capability of doing distributed and parallel processing. This capability will allow multiple teams to use AI at the same time without interfering with one another.
From Predictions to Decisions
DECA is an acronym that stands for Decision Evaluation Capabilities Automated and refers to the ability of AI systems to interpret and evaluate the results of AI predictions using a structured approach using historical data, rules and context before being applied to take action in the real world.
Although many AI systems produce predictions (what is likely to happen in the future), the ultimate value of these predictions for an enterprise lies in being able to use these predictions to make an effective decision. In order to make effective decisions, organizations must be able to use their experience to evaluate the results of the predictions and utilize this information to create a reasoned basis for their decisions.
This ability makes AI safer, more reliable, and more in alignment with the organization's goals and objectives versus simply functioning as "tools."
Distinctions from Chatbots and AI Models
There are several important distinctions between DEE and other types of AI systems. DECA does not generate textual responses or responses to questions. DEE also is not intended to replace existing AI systems.
Rather, DEE provides an environment for existing AI systems so they can operate properly. In the absence of DEE, AI systems will act as isolated tools, while with DEE, they will operate within a cohesive framework for reasoning.
This distinction is critical for organizations interested in maximizing the return on their investments in AI. Therefore, understanding DECA provides clarity on the types of activities that an organization should expect from their investment in AI.
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At Tecosys, DECA is built on years of direct experience working with complex, enterprise-level systems. DECA was developed by highly skilled individuals who have experience with how large amounts of data function in real-world environments rather than being based solely on laboratory research.
DEE provides the framework to fulfil the enterprise’s need for Accountability, Compliance and Reliability as they apply to their business, as well as their customers’ trust. A company earns its customers’ trust through a commitment to transparency and consistent behaviour. DEE provides both assurances by enabling organizations to inspect, explain and help continuous improvement of this Reasoning by the using of AI technology.
The Future of Cognitive AI
As AI develops, the future of AI will consist of systems that will Reason, Remember and Adapt. Although the future will have more models with better quality, their usefulness will continue to be limited due to the lack of a structured approach to Reasoning.
The evolution of DEE represents a move from thinking of Intelligence in terms of being isolated, to the development of systems that are connected to one another via the internet or via other forms of connectivity. DEE allows cognitive AI to operate in a manner similar to that of a partner you can rely upon instead of an experiment with a level of danger.
Why Tecosys Is the Solution for Companies
Tecosys is the solution for companies because we have an emphasis on Building a Foundation and not Cutting Corners in the Development of Cognitive AI. Nutaan H-RAM and DEE are Patented Technologies of Tecosys that when combined create a cognitive AI that is both practical and scalable, as well as Trustworthy.
Tecosys does not advocate for the Replacement of Human Intelligence; instead, we advocate for the Augmentation of Human Intelligence through the use of systems that can think rationally, learn in a responsible manner and Act Consistently
As mentioned before, DEE is the foundation of this vision.
Structure is the Key to the Future of AI
Structured reasoning is the key to unlocking the potential of AI. Without structured reasoning, AI will continue to be viewed as having limited potential. DEE resolves this issue by providing a structural framework through which AI can operate; thereby allowing AI to develop Cognitive AI solutions that will ultimately revolutionise the world and mankind.
Frequently Asked Questions (FAQ):
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What is DEE (Deep Extraction Engine)?
The DEE (Deep Extraction Engine) Created by Tecosys Is a Patent Protects System for Enterprises. It represents a patented enterprise solution developed by Tecosys. It does not refer to an AI model or chatbot, but rather acts as a layer underneath AN AI system to govern how data, memory and reasoning progress throughout the AI system. As a result of having a structured layer, businesses can ensure that their AI systems deliver decisions that are consistently auditable and reliable across all production environments.
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Does the DEE refer to an AI model or chatbot?
No, it does not. The DEE is neither an AI model nor a chatbot. The DEE is not able to create responses or otherwise engage directly with end-users. Rather, DEE functions as a structural layer under AI models; it provides structure to how data is sorted, organized and stored as well as manages how reasoning occurs and produces AI outputs over time.
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Why is Structured Reasoning Prerequisite for All AI Models?
The reason structured reasoning is critical to AI systems is because structured reasoning provides structure to complex and/or disorganized datasets, allowing AI systems to make sense of complex and often erroneous data sources, and at the same time ensures that structured data is created in such a way as to allow AI to produce reliable and consistent outputs. Structured reasoning assists AI in understanding relationships between all of the different types of data and develop better decision-making processes and more predictable outcomes as a result of understanding.
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How Does the DEE Integrate Structured and Unstructured Data for AI Systems?
The DEE combines and assimilates all structured and unstructured source data into a single set of integrated data sources. The DEE takes out any and all errors introduced into the combination and correlates all data sources with one another, providing a "roadmap" for how to combine them and providing AI systems with the means to "reason" across datasets without confusion or conflict.
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How Does DEE resolve Problems for Enterprises?
DEE addresses numerous significant issues that businesses experience. These include disconnected data; erratic algorithms and biases; lack of clarity as to how an AI makes decisions; regulatory compliance risk; among others. The DEE solution provides companies with confidence that their AI applications will work effectively with reliable data inputs, consistent processing; and provide a means by which companies can track the accuracy of AI-created decisions.