Deficiency of Model-Only Based Enterprise AI
Most current model-based enterprise AI systems operate under a powerful model; however, these systems lack the capabilities of long-term intelligence. We are still in the era of developing advanced AI, based on the current use of immediate input data, with the inability to leverage continuous interaction and historical context when generating an appropriate response.
Thus, AI systems that are designed in this way can be extremely challenging for enterprise users that rely on them for consistent and accurate responses.
Customer support experiences customers frequently receiving the same information multiple times and conflicting answers being provided by the same AI application. In Finance and Healthcare, there are additional compliance risks since previously made decisions and the rationale for such decisions can be lost along with the memory of those decisions. Like this, on the internal operation side of things, when AI cannot recall previous policies, exceptions or even resolutions to issues that it had previously dealt with, it becomes unreliable, and therefore, by absence of memory, AI-based reasoning is vapid; it is limited to using templates for recognition, i.e. interpreting patterns, rather than genuinely understanding.
Why Memory Is Central to AI Reasoning
Enterprises require an AI that is persistent and has both the ability to continuously reason and learn. Artificial intelligence's ability to reason is reliant on its ability to recall. A human's intelligence is not a matter of having raw knowledge, but of having memories. Humans learn from their mistakes and are able to tap into their previous experiences, and apply that to new problems. In this respect, present-day enterprise AI has an inherent shortcoming compared to humans.
AI-based reasoning systems cannot reason without incorporating memory. The process of logical reasoning necessitates that the reasoning process be able to reference previous states of thought, compare the outcomes based on the previous state(s), and adapt logic to fit an ongoing series of changes over time. AI-based reasoning systems can only react and cannot genuinely reason, because they lack the benefit of having memory.
Therefore, an AI-based reasoning system needs to develop further than simply offering stateless responses, and develop into a structure that permits an AI-based reasoning system to continuously develop, grow, and learn from its past experiences. To this end, Nutaan H-RAM is an architectural model ratified as capable of performing this function.
Introducing Nutaan H-RAM: The Humanized Reasoning and Memory Architecture for AI Models
Nutaan's H-RAM adds a memory/knowledge-based layer of reasoning to any AI-based system. Nutaan does not replace existing AI systems; rather, it augments or enhances them by enabling enterprise customers to enjoy a more durable and intelligent experience with AI systems. Nutaan's H-RAM enables AI to function more like a highly educated and experienced human employee than a generic bot.
Nutaan's H-RAM provides AI with memory through the storage of contextual knowledge acquired from the interaction between users and AI. This memory is structured, searchable, and updated, allowing the AI system to capture the history of decisions made and errors corrected and to maintain and develop organizational memory. Through continual exposure to business rules, expectations and tone of voice and expectations will cause AI systems to align themselves with enterprise needs without requiring re-training of the underlying AI model. Through this architecture, Nutaan provides users with an AI product that is truly designed for enterprise use.
Enabling Enterprise level of Consistency across interactions
Many enterprises have reported that inconsistency with regards to how they respond to users is one of their biggest frustrations with AI technology. Users submit the same question and receive different responses based on how the user phrased the question, when the question was submitted, or depending on different behaviors of the AI model. These inconsistent responses deteriorate user trust and create difficulty in implementing AI systems on large scales.
Nutaan offers enterprises a different way of providing AI-enabled services. Nutaan's technology captures the context of each interaction with an enterprise by remembering previous responses, decisions and policies so that AI responses always conform to the expectations of that enterprise. When a user has a customer, employee, auditor or partner, he or she will find the AI always produces the same responses.
The ability to maintain this level of consistency across interactions with an AI system is critical for regulated industries such as finance, insurance, healthcare and legal services, transforming the capabilities of AI from being viewed as a research platform to that of a viable enterprise solution.
Utilizing Memory for Quality Control in AI Systems
While errors are expected with AI usage, continual errors are not acceptable for enterprise level data usage. Traditional models of AI require retraining to learn from past mistakes; retraining is time consuming and costly to employ. However, Nutaan H-RAM offers built-in quality control mechanisms via "memory-based" feedback loops.
Using delta-type error detection methods, Nutaan H-RAM automatically flags (designates) as correct/incorrect/risky/not-compliant any response that has been produced by an AI Model. These flagged corrections will be recorded into "memory", allowing the system to "self-correct" on-the-fly. As a result of this correction process, over a period of time the AI system will become less likely to repeat a previously flagged correction.
By employing reliable and self-correcting technologies, Nutaan H-RAM dramatically improves operational dependability while lowering risks associated with operational practices. This is particularly true for situations in which one incorrect response could lead to major adverse consequences; therefore, persistent self-correcting AI represents a new way of improving performance through increased levels of accuracy in reliable enterprise applications.
Continuous Learning Without Retraining
One of the greatest barriers preventing enterprises from fully scaling out their use of AI technologies is the time; number of resources and workbook downtime associated with retraining models. This is even more pronounced in environments where rules, policies and information changes frequently. Nutaan H-RAM allows enterprise AI applications to continuously learn via updating their memory stored data.
When new policies, SOPs, FAQs or regulatory changes occur, Nutaan H-RAM is able to immediately update their memory stored data. Subsequently, the AI application can adjust/adapt in real-time without having to retrain their AI models.
AI Decision Intelligence: The Key to Creating Enterprise Value through Intelligent Decisions
Enterprise value created by AI does not come from the machine simply answering questions. AI Decision Intelligence is an effective combination of historical context, real-time input, and the logic of the business, to produce accurate and reliable results.
The Nutaan H-RAM is designed to provide fast (H), structured (R), and contextually aware (A) means of retrieving memory (M).
H-RAM allows for AI to perform multi-step reasoning, to work with complex workflows, and to accomplish high-context work that traditional methods are unable to achieve, such as evaluating risks, justifying claims, interpreting patient histories, and assessing compliance. Rather than responding to direct answers, AI is able to reason through the problem based on historic knowledge and previous decisions. This methodology allows for the development of entirely new enterprise applications through the transition from reactive AI to reasoning AI.
Persistent AI: The Evolution of High-Context Enterprise Workflows
The majority of enterprise workflows include multiple steps and numerous stakeholders. Stateless AI cannot sustain continuity throughout workflows, and thus becomes difficult to implement. Persistent AI offers a new paradigm.
Nutaan H-RAM permits AI to remember the "journey" that an item of work will take from initiation to resolution, making it possible to capture relevant context across department, tool, and timeline. Consequently, organisations can automate the processes of complex workflows whilst maintaining appropriate levels of oversight and control.
Persistent AI is particularly beneficial within the insurance, healthcare administration, loan processing, and enterprise support industries to guarantee consistency, transparency, and traceability in decision-making.
Enterprise scale AI
Enterprise AI must be able to scale in addition to volume, therefore complexity. As enterprise use increases, the memory of the AI platform needs to manage across all the teams, products and data sources without risking degradation of service. The Nutaan H-RAM was designed to operate in a distributed enterprise environment with thousands of users interacting daily.
The architecture of the Nutaan H-RAM allows the segmentation, sharing and restricting of memory according to organizational need, thus enabling each team member to benefit from the knowledge that is most relevant to their function whilst preserving the confidentiality and governance of the organization. This way, the AI platform is able to horizontally scale to all departments of the organization without losing intelligence or control.
Therefore, the H-RAM is also suitable for large enterprises where multiple regions, business units and regulatory frameworks exist.
Works Seamlessly with Existing AI Stacks
Most enterprises have made a significant financial investment in AI infrastructure, and therefore it does not make practical or logistical sense to replace existing models. The Nutaan H-RAM allows enterprises to include memory and reasoning capabilities seamlessly with their existing AI stacks, which may include, but are not limited to, ColdFusion, GPT4, Claude, Llama, Gemini and even internal proprietary models.
This modular design provides a low-risk option for an organization to adopt both memory and reasoning capabilities without disruption to existing operations. Also as mentioned earlier, enterprise AI is future-proofed by its adaption of future model and technology.
Enterprise H-RAM decouples artificial intelligence from models, giving enterprises flexibility, compliance, and a long-term return on investment (ROI).
From Reactive Artificial Intelligence to Cognitive Enterprise Systems
Enterprise AI will evolve similar to the evolution of Human Intelligence (HI). In early enterprise AI systems, the emphasis was computation. In modern enterprise AI systems, the emphasis is on language. In the next evolution of enterprise AI, enterprises will focus on Cognitive processes, i.e., Memory, Reasoning, and Decision-making.
In the next evolution, Nutaan H-RAM enables the introduction of Memory into AI, allowing for the transformation of Static AI Models into Adaptive Learning Systems. This change will allow for the development and improvement of Adaptive AI Learning Systems over time. As such, for enterprises looking to adopt AI sustainably as opposed to just Quick Wins, adopting a Cognitive AI system is an absolute necessity.
Cognitive AI systems will not be defined by the quality of the language in which they communicate; rather, they will be defined by their ability to retain Memory, make Decisions, and reason effectively.
The Business Impact of AI with Memory
To put it more plainly, businesses can expect an immediate positive impact as the result of incorporating AI with memory. businesses can expect improved accuracy; reduced operational risk; improved speed-to-decision; improved trust in the quality of AI decisions. employees can spend less time making sure the AI is making accurate decisions and more time on strategic planning/execution. customers receive consistent and informed responses from AI.
The Future of Enterprise AI is Memory-Driven
As enterprises are increasing their use of AI, they are becoming increasingly aware of the limitations of model-based AI approaches. Enterprises do not want to use systems that "forget" the previous conversation, contradict themselves, or need to be "retrained" repeatedly in order to be accurate. Enterprises want AI to think and act in an intelligent manner over the long term.
Enterprise AI will become an integrated part of an enterprise's day-to-day operations. New enterprise AI systems will combine the models associated with machine learning with logical reasoning and self-learning capabilities. Nutaan's H-RAM is one example of an AI system that delivers this type of "persistent" AI, closely matching how enterprises operate.
Beyond Models, Toward Intelligent Systems
Memory is not something that needs to be added to an enterprise AI platform; it is the very foundation of a true intelligent enterprise AI platform.
Enterprise AI is transitioning from a collection of disparate tools to a single platform that integrates enterprise-wide intelligence. Therefore, to harness the full potential of enterprise AI, enterprises must shift their thinking from being focused on models to incorporating memory and reasoning as fundamental components. Nutaan's H-RAM will contain the third component needed to facilitate this transition.
H-RAM enables AI systems to incorporate memory and have advanced reasoning capabilities, allowing for the inclusion of scalable AI knowledge in the decisions made by AI. By enabling AI with memory, advanced reasoning, and scalable decision intelligence, H-RAM converts traditional, static automation into a truly intelligent system that continuously grows in intelligence with every experience.
Frequently Asked Questions (FAQ):
1. What is AI with memory?
AI with memory can be defined as an artificial intelligence (AI) system using past experience when performing tasks. It allows for consistency and improvement of responses based on previously recorded interactions, decisions and corrections.
2. Why do Businesses need AI with memory?
Businesses utilize AI with Memory to enable consistency, accuracy and continuity within complex workflows, regulatory compliance and multi-year operations.
3. How can memory improve AI reasoning?
With the use of Memory, AI systems are able to understand the context of previous actions and relate data outputs. Memory allows for multi-step reasoning rather than only a single response giving a static result.
4. What is Nutaan H-RAM?
Nutaan H-RAM (Humanized Reasoning and Memory Architecture) is a persistent memory and intelligence layer that is integrated into any AI model.
5. Does Nutaan H-RAM require retraining of the Model?
No, Nutaan H-RAM updates the AI system's Memory in real time, enabling the AI model to continuously learn without requiring the re-training of the original AI model.