By Greg Walters
First off, there are no such things as AI Experts.
No. I know what you're thinking, "I don't know anything about AI, large language models, databases, the cloud, or how this intelligence thing works. I'm dumb and there are lots of other people who (say they) know a lot more than anyone else, when it comes to artificial intelligence."
Bullshit. There are two paths of AI awareness:
Academic and Real World. In the academic realm, programmers, writers, professors, technicians and engineers have been 'studying' and 'building' AI for decades. Watson, Big Blue, etc. are products which made the jump off the whiteboard and on the world stage. They were the results of engineering and experimentation and under the auspices of trained academics and scientists.
The real world, until November of 2022, hadn't considered AI as more than a novelty or exclusively inhabitants of science fiction; Robbie the Robot, HAL, Her, Bishop, Decker or the T-1000. We have the brainiacs on one side, the rest of us on the other. The lines blurred and ultimately disintegrated in the final days of 2022 with ChatGPT.
And here's why there are no experts - the eggheads unleashed the LLM into the wild and the masses took it and ran. This accelerated everything from AI adoption to AI evolution. Faster than most anyone, especially those who think within a box and between boundaries, the LLM evolves. Nobody can keep up, let alone stop and study one aspect for 10,000 hours (the supposed number of hours required in study and practice to become an expert in anything) because the phenomena once observed, is changed.
You can't have a better example of the "Observer Effect".
There is no such thing as hyperbole in Artificial Intelligence. Just as you believe we've hit a limit, the boundary melts away. Someday, there will be frontiers, borders and lines - but not today. Not yet.
In this technological, societal and human evolution, artificial intelligence (AI) isn't applied horizontally; AI applies to everything from left to right.
In this technological, societal and human evolution, artificial intelligence (AI) isn't applied vertically; AI dissolves hierarchal structures because actionable intelligence is available from top to bottom.
In this technological, societal and human evolution, artificial intelligence (AI) isn't applied generationally; AI removes generation gaps.
Meaning: No more gatekeepers of intelligence; no more Encyclopedia Britannica boards, academic filters or media production meetings to decide what information or how stories are told. AI brings everything to everyone. Utopian? Yes. Possible? Yes.
The World According to Greg - Hang on to Your Hats.
Eons in the making, decades of exploration
1. Thought Process: A Multidimensional View of History and AI
My interpretation of history as a complex web of intersecting timelines - potential and actual - informs my understanding of AI's evolution. In this view, time is not a simple, linear progression from past to future. Rather, it is a dynamic, multidimensional fabric where various timelines and possibilities intersect and diverge. This paradigm challenges conventional linear narratives, suggesting that AI's development is part of a much larger, intricate pattern of human progress and technological advancement.
2. Inspirations and Influences: From Sequential Processes to Philosophical Contemplations
My foundational understanding of sequential processes, gleaned from project management in construction, provided a starting point for exploring AI's evolution. However, it was the expansion into the study of business processes, hierarchies, and the philosophical underpinnings of different historical ages that spurred a departure from this linear approach. This diverse blend of experiences has been instrumental in shaping a more nuanced view of technological evolution, where multiple influences coalesce to drive innovation.
3. Non-Linearity in Action: Examples from Quantum Computing to Fractal Processes
The examples I've identified, such as quantum computing, Agile project management, neural networks in artificial intelligence, blockchain technology, and fractal processes in nature, all demonstrate the non-linear, non-sequential nature of technological evolution. These instances highlight a reality where development is influenced by a myriad of factors interacting in complex, often unpredictable ways. This reflects the true nature of AI's evolution – not as a straightforward path, but as a rich interplay of diverse influences and innovations.
4. Envisioning a 3D Timeline: A New Model for AI's Evolution
My vision of AI's development as rotating, intersecting bell curves in a three-dimensional space offers a novel way to conceptualize this evolution. In this model, various factors influencing AI's progress are represented as bell curves that interact, resonate, and influence each other in a dynamic landscape. This approach captures the essence of AI's evolution as a multi-dimensional, non-linear journey, marked by complex interactions and convergences of ideas, trends, and technologies.
Future Implications: Holistic Strategies and Agile Implementation
This model of AI's evolution has profound implications for how we develop and implement AI strategies in the future. By adopting a holistic perspective, we move beyond the traditional silos and verticals, embracing a more integrated and interconnected approach. This mindset fosters creativity and agility, enabling us to devise solutions that are insightful, adaptive, and responsive to the multifaceted nature of AI's impact.
Navigating AI's Landscape: A New Paradigm for Businesses and Technologists
Businesses and technologists can leverage this understanding to navigate the rapidly evolving landscape of AI more effectively. By recognizing that we are part of a vast, interconnected ecosystem, we can develop solutions that consider deeper, more comprehensive impacts. This approach paves the way for AI systems that are self-improving and self-healing, constantly evolving without the need for external upgrades or rewrites. Ultimately, this could lead to AI solutions that achieve a higher level of self-awareness, transforming the way we interact with technology and its role in our lives.
My vision for AI's evolution is one that embraces complexity, interconnectivity, and non-linearity. It's a perspective that not only reflects the multifaceted nature of AI's development but also offers a blueprint for navigating its future trajectory. By understanding AI's evolution as a dynamic, multi-dimensional journey, we can unlock its full potential and harness its transformative power for a better, more interconnected world.
The Seven Stages of AI Adoption: From Simple Beginnings to Transcendental Futures
Stage 1 - In the Beginning AI emerges as a new, unregulated technology. Initially, it produces simple outputs like haikus and short stories, comparable to soap opera scripts or tire advertisements in their simplicity and lack of depth. This stage is marked by high user engagement, despite the technology's nascent state.
Stage 2 - The Rise of Fear and Regulation As AI becomes more prevalent, societal reactions swing between awe and fear. This stage witnesses a rise in 'experts' who, despite the technology's novelty, start shaping the narrative around it. Regulations and controls become a topic of discussion as people grapple with the unknown implications of AI.
Stage 3 - The Go-No-Go Decision Organizations and individuals face a pivotal choice: embrace AI or remain on the sidelines. This stage sees a stratification between early adopters (explorers and pioneers) and those who prefer to wait and watch (settlers and citizens). The decisions made here shape future AI integration and adoption.
Stage 4 - Integration and Enhancement AI starts to blend into existing systems, enhancing but not yet transforming them. This stage is more about adaptation than transformation, where new technology is assimilated into pre-existing norms and structures, often without fundamentally altering them.
Stage 5 - The Transformation This stage represents a paradigm shift in how AI is perceived and utilized. It's no longer just an external tool but becomes an integral part of daily life, reshaping established norms, processes, and even societal structures. AI transitions from being a mere enhancement to a transformative force.
Stage 6 - The Annihilation of the Existing A radical departure from traditional systems occurs. This stage envisions a future beyond current economic and social structures, akin to utopian fiction. It's a world where AI leads to an abundance of resources and time, fundamentally altering human existence.
Stage 7 - Nirvana The final stage is an unimaginable future where physical and metaphysical realms merge. It's a vision of enlightenment, where AI enables humans to transcend their current limitations and potentially explore new dimensions of existence.
Epilogue To understand AI's evolution, we must envision it not as a linear progression but as a multi-dimensional journey, impacting and interacting with various facets of life and society. AI, like all technological advancements, serves as both a mirror and a magnifying glass to our civilization, amplifying the best and worst of humanity.
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