Discovery and Principles
Perry C. Douglas
October 1 2024
The applied intelligence | ai strategy process is based on insight generation for strategy development — very straightforward and deliberate, constructed on four values of ai.
I — Structure
The first step in knowledge extraction for strategy formulation is to identify all of the entities and structural information within a set of documents or observable facts: people, places, things, concepts, numbers, sentiments, quotes, etc. Create a series of custom classifiers to extract, resolve and store those entities in a knowledge base. Then, identify the relationships between pairs of entities using the prescribed ai methodologies. Every piece of data that you capture retains its provenance, giving full transparency on the decisions to be made downstream. Utilizing algorithms as necessary.
II — Ensemble
The ai strategy development system process helps you construct models of reality based on the streams of retrieved information. By de-duplicating and reconciling statements in documents, we create an ensemble version of the corpus. For any given event, there can be thousands of varying descriptions, from the people involved to the tiniest details that the human mind likely won’t think of. Powered by ai, taking a multi-document approach allows us to capture variations as signals rather than being fooled by noise. Improving the quantitative performance metrics for the problem we are seeking to solve.
III — Event
The insight engine looks for evidence of real-world events based on a set of documents and observations. Analyzing a set of structured data extracted from the documents. It is then able to cluster together entity relationships as a function of time. The result is a time-directed graph of inferred real-world events from any given corpus that can be compared to generate meaning.
IV — Context
Information is best understood in context with all the other information around it. The context engine function analyzes any claim, fact, or assertion and identifies any supporting evidence or any contradictions, returning the results to be contextualized and prioritized for better understanding. On a larger scale, the context engine augments the process and allows us to connect events based on an inferred chain of probable causality. For a better understanding of how a set of events are connected and how they evolve through time enables us to identify the origin and spread of information, specifically. To better frame information and turn insight into strategy.
Artificial intelligence’s (AI) role in the process of useful utility, a tool helping the process happen incredibly faster and more in-depth, is the prime use of advanced data analysis ecosystem tools. Analyzing vast amounts of data, identifying trends and patterns, and providing comprehensive and conclusive insights that can be taken as empirically warrantable — highly useful to people and organizations.
Accordingly, AI acts as an intelligent tool fused into ai’s human-centric strategy development system. Here, AI is not distractive and doesn’t pursue making it competitive, surpassing or replacing human intelligence. AI serves as enormously helpful to users of the ai system…in solving real-world problems. It uses Generative AI (GenAI) with amplifying function, most practically, purposefully, and responsibly, to augment human intelligence capacity, capabilities, and ingenuity. Helping to advance the human-machine collaboration optimally, in the best interest of humanity.
In the enterprise space, AI integrates necessary workflows that drive value. Not wasting time with the superfluous — science fiction narratives like AGI, which is self-serving and pushed by the usual suspects in Big Tech.
The core objective for ai users is to utilize scientific wisdom to construct the most critical thinking models to solve the most pressing human problems.
So, the necessary deployment of AI within ai brings significant competitive advantages for those who find hidden asymmetries. Building strategies to capitalize on them. It’s about being grounded in facts, analysis, and leading decisions by a process of logic.
Strategy formulation is focused on winning, however, to win, strategies must be built on the firm foundations of reality. There can be no doubt about that. On what is objectively true, not on theoretical modelling or what one believes to be true.
Effective strategy building is best approached through Einstein’s discovery & principles, and concluding. These steps are important because they help to avoid the very human instinct of bias, priori hypothesis, going out and cheery picking the data to back up your hypothesis. Highly unproductive. Principles are the driving force behind Einstein’s belief that the best ideas are discovered through the relentless pursuit of knowledge, the quantitative approach, underlined by mathematics, to tell the truth.
Nevertheless, it is important to note that Einstein does inform us that, like in physics, “there is no method capable of being learned and systematically applied…by perceiving in comprehensive complexes of empirical facts certain general features which permit of the precise formulation.” In other words, there is no magic bullet; discovery is the path. AGI is a fantasy!
Cosmologist Stephen Alexander adds, “Facts are statements about phenomena, but they don’t exist on their own; they are always conceptualized, which means that they are, if only implicitly, constructed theoretically.” So, we must be skeptical about how we take in and explain “facts” and not be too reticent to conclude hastily.
Finding opportunities out of the whitespace and identifying and determining the right problems to solve is the first step in the six steps to the applied intelligence | ai process. Building solutions based on evidence and driving strategy with scientific wisdom.
Effective strategy formulation remains a very human process; nevertheless, technology is a great collaborator and enhancer of human intelligence. Therefore, with a disciplined and controlled technology framework, AI can contribute greatly to getting things done in a practical without being a distraction. Making things happen faster, more precisely, and without the need for consultants, advisors, or specialists.
The advancing digital global economy requires innovative solutions that can be developed with speed and accuracy. The realization that the effectiveness of decisioning on factual information against intuition has become even more evident. It is imperative, therefore, to recognize technologies’ extraordinary enterprise worth and apply it to the right value-advancing tasks and processes. Optimal decisioning combines the power of the mind and the computational ability of machines to process and help the human mind outperform. While managing risk.
Leveraging intelligent ecosystems to accelerate our understanding of the universe to better compete in it is fundamental to the human condition. So it was built for that. Whether it be personal growth strategies or multi-billion dollar business strategies, the ai process is the same. Just a matter of degree range and robustness. You don’t have to give in to new technology by any means, but you must develop your playbook to succeed in an increasingly AI-driven world. It is up to you to expand and broaden your intelligence capacity horizon, tame tech, and make it work for you.
Being afraid of it doesn’t help you — ai helps by creating a series of processes to identify whitespaces for growth opportunities. It builds full-picture views of target markets, industries, and opportunities, and it starts with identifying the landscape, confirming the POV, identifying opportunities and areas of risk, and the decisioning point.
Every successful strategy must be underpinned by real, in-depth knowledge of its industry, sector, or domain. The entire process works to capture insights, turning them into strategies for winning without the need for specialized skills, technical tools, and expensive consultants.
Redefining how strategy is crafted in the age of AI.
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