Men, Machines and Generational Intelligence

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“Whatever the mind can conceive and believe, it can achieve.”

SwissCognitive Guest Blogger: Senthil M Kumar – “Men, Machines and Generational Intelligence”


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Once every 20 years, there is a generational Cycle that has a deep impact on the present and future generations. This cycle powers societal transformations and encompasses the experiences, values, and aspirations that define each generation’s unique character. In a sense, it is this fascinating rhythm that shapes the ebb and flow of generations. It is a constant reminder that change is inevitable, and with it comes a chance for growth and renewal.
In this cycle and in a span of two decades, we’ve witnessed the birth of new technologies that reshape the way we live and interact. From the ubiquitous rise of the internet to the proliferation of AI, each generation experiences technological shifts that shape their worldview and communication styles. The year was 1982, Times Magazine, for the first time, instead of a Person of the Year cover, named the Computer, the PCs as the Machine of the Year. A machine displaces a human to get on the cover of a coveted magazine. Since then, and since we all saw IBM Watson in action, we have come afar.

A Realist View of the World

As we aspire to the future, the present is an interesting place to live. We are experiencing an inflexion point in the field of computational science. The work over the years has led us to a moment in time, where commoners get to experience the impact of machined intelligence and have a say in shaping its future.
The recent advancements in A. I foster a harmonious interplay between men and machines. While the computational machines have made their mark, they are not replacing human ingenuity, at least not yet. They are now complementary and enhance human potential. Intelligence is now ripe for redefinition. It can no longer be the unitary human intellect. We are now cohabitating with machines and the collective intellect is what makes up intelligence. As human intellect focuses on creativity, critical thinking, and emotional quotient, machines can handle complexity in analysis, relate and correlate patterns, identify scenarios that may have been missed, and anticipate and formulate solutions for the future. This partnership has given birth to a new form of intelligence, one that combines human intuition with the computational processing power of the machines.

Generational Intelligence

Generational intelligence is a result of this harmonious interplay. It represents the collective wisdom of both human and machined insights, a symbiotic foray that transcends the limitations of individual capabilities. As each generation of machines becomes smarter, faster, and more adaptive, the potential for solving complex challenges grows exponentially. As humans make available and feed machines with information and refine algorithms, these tools reciprocate by providing actionable insights that drive innovation and progress. In a mere stroke of an LLM (Large Language Model) that was pre-trained and generative, the world undeniably woke up to a new world order. Suddenly democratizing A. I was no longer an imaginary dream. The subsequent generative iterations of AI evolution will lead to capabilities for the machines to reason more. Act faster, imbibe more information based on their own reasoning, formulate solutions, and explain the recommended actions. Take proactive actions and work side by side getting a proverbial seat at the table of a human interactor in decision making.

The Big Blue and Elementary Dr. Watson

If the machines are getting smarter, it was not long ago that the scientific community heralded that a new era in computational science has arrived with the arrival of IBM Watson. Imagine the feeling when the Big Blue’s multi-billion-dollar investment in shaping Watson was demonstrated to the world when it took on human competitors in the game of Jeopardy and won. So why has Watson not succeeded and why do we think that Generative AI will? Well, a number of Eulogies have been written about the demise of Watson. An exorbitant question and answering system. What happened to all that fanfare and why is the present world a much more bankable one? At times in a battle of the giants, along comes a player who can unravel the Gordian knot. Though the technological implementations are quite different between Watson and Generative AI, the foundational difference lies with the usage of a Large Language Model that was pre-trained for Generative AI purposes. That has made a big difference. It didn’t come easy or cheap and neither is the work done. This, in all possibilities, is the first generation of such a solution that will evolve and mature as the years progress.

The Road Ahead

The trajectory of men, machines, and generational intelligence presents a multitude of interesting possibilities. As we harness the capabilities of machines to broaden our horizons, this isn’t the rise of machines; it’s the rise of human capacity through machines. The key lies in our ability to adapt, collaborate, and lead this partnership toward a brighter, more intelligent future. Within the next few years, we are going to see the algorithms will do better than humans on a number of fronts. Take the case of Healthcare and Medicine, from analyzing radiological images to retinal scans to oncological treatment formulations to eventually helping us find a cure for cancer, the machines will become a critical aspect of our solution. They will not only partner with us but in a number of instances, will do better than their human counterparts in analyzing, introspecting, reasoning, and formulating, all without the emotional quotient. Which will both be a blessing and a curse. In the case of Architecture, Engineering, and Construction space, Machines will become adept at creating designs of their own that will have practical applicability and a high degree of efficiency. In the field of education, these advancements present a new way of generational learning.

Challenges and Ethical Considerations

The march of generational intelligence is not without its challenges. As machines become smarter and integrated more into our lives, considerations about privacy, biases, security, and unsupervised controls ought to come to the fore. These cannot be an afterthought and have to be built into the foundational concepts. Striking a balance between utilizing AI for progress and ensuring ethical usage requires careful thought, planning, and regulatory enforcement.

Epilogue

As older generations pass on their wisdom, younger ones bring fresh perspectives and technological advancements. Isn’t it fascinating to note that unlike humans, AI is growing younger and younger, birthing of new ideas, newer concepts, and democratization of something that was only available to the higher echelons of computational scientists and to companies that can afford. From that stance to one where the commoners have now begun to get involved and embrace the technologies is a monumental leap. The future beckons with its promises and challenges. The generations that emerge will be shaped by the lessons of the past and the innovations of the present.

In the mere moment of a millennium, the achievements of the human mind have been spectacular to the point of being able to conceive machines that can be smarter and more intelligent than their human counterparts. The synergy between men and machines fosters generational intelligence, an intelligent fusion that empowers us to conquer new frontiers. This phenomenon is not just about technological advancement; it’s about expanding human potential and improving overall productivity and efficacy. As the generational digital age clocks on, our ability to embrace change and leverage the human-machine convergence and partnership will chart our success in the journey ahead.


About the Author:

Senthil M KumarWith pioneering contributions in AI, Edge Computing, Blockchain, Cloud Computing, Metaverse, IIoT, Swarm Robotics, and System Autonomy, among others, Senthil M Kumar has been instrumental in shaping the technological landscape. As a technology executive, his work has spanned various industries globally, including AEC, Fintech, CRM, Autonomous Vehicles, Smart Buildings, Geospatial Engineering, Insurance, Healthcare, and Medicine. He currently serves as the CTO of a Silicon Valley startup, Slate Technologies, and is an advisor to academia and to other companies on sophisticated technologies and futurism. His work has been acknowledged as a Pioneer in A. I by the W.E.F.

Der Beitrag Men, Machines and Generational Intelligence erschien zuerst auf SwissCognitive, World-Leading AI Network.

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Jason M

Kudos, well thought out and written article