Mathematics for AI ??
This is the next continuation of our AI, ML, and DL article series. As we discussed in previous articles, now we know the core reactor of AI, ML and DL technologies are mathematical concepts. They predict future indicdents based on patterns previously happend by leveraging mathematics. So in this article we are going to explore how mathematics will give the power to these technologies to become a divine eye (divine eye means the ability to see future using 6th sense)
What is the role of mathematics?
If we examine the majority of groundbreaking inventions, theories, and discoveries throughout history, we find that their foundation is mathematics. However, mathematics itself is not just a static tool which existed since the beginning of the universe — it is a human discovery, shaped and refined through continuous contributions over centuries.
Humans are highly conscious beings, unlike other living creatures. The human mind doesn’t easily accept phenomena as they are. We want to feel them in our soul — we need to know why and how. We call this desire (the very thing that keeps us attached to the cycle of life, as Lord Buddha described — and that’s perfectly okay; after all, we’re all human) the curiosity of the human mind. We sense that something is hidden within these phenomena, but we can’t fully feel it, and more importantly, we can’t control it. This lack of control creates ambiguity, and some minds are driven to resolve that ambiguity with clarity and reason.
Humans gradually uncovered a framework called mathematics as a solution to that ambiguity, and it perfectly resonated, filling the gap between universal phenomena and how we experience them. This framework evolved step by step, each layer building on the previous one, enabling us to describe increasingly complex phenomena with precision and logic.
Take an apple falling from a tree — we see it, we know something is happening, but it doesn’t quite reach our soul. This ambiguity doesn’t let rational minds stay calm. Some humans, particularly those driven by a need for clarity and understanding, couldn’t settle for vague interpretations. Their minds craved something more precise. So they began developing a framework, layer by layer — one that could convert these universal phenomena into structured understanding, and then translate that understanding back into action to influence and control those phenomena once again, in an attempt to feel and grasp the truth more tangibly.
To truly understand and eventually manipulate these phenomena, they had to be made measurable and quantifiable. However, our thoughts, emotions, and even many of our perceptions are not inherently measurable. In order to bridge this gap between human experience and external reality, we needed a language. A language that allows us to translate phenomena into the measurable and quantifiable domain, and then back into phenomena we can understand and manipulate. That’s where mathematics comes in. It was invented as a universal, quantifiable language, one that could act as a broker between the intangible desires of the human mind and the physical laws of the universe.
Intuition in mathematics for AI.
If you observe intentionally with a rational mind, there is no such thing as black and white in the universe. All events are happening within a range. From the energy spectrum in this universe to human behavior, everything unfolds as a spectrum of possibilities. In that sense, everything is possible in this universe; it’s just a matter of probability (the likelihood of an event happening, in simple terms).
If we take an example for simplicity, consider the act of driving a vehicle. From successfully reaching your destination to getting into an accident and total destruction, every outcome is possible, just with different probabilities. If you get drunk and drive, the probability of an accident is much higher, but that doesn’t mean you’re definitely going to crash. And if you drive while obeying all the traffic laws, the probability of an accident is lower, but that doesn’t guarantee you’ll reach your destination safely either.
Since many possibilities exist, each of those possibilities leads to many effects. And every one of those effects, in turn, creates more possibilities. From this, a giant web of cause and effect emerges in the universe, where one cause leads to an event, and that event becomes the cause for another. This vast network of cause and effect, filled with infinite probabilities, forms a deeply complex and interconnected system. We call this the law of causality — the natural order of the universe. As souls traveling through this universe, we are also bound to and intertwined with this intricate web.
So, as things become more complex and interconnected, a kind of event mechanism emerges — one that operates according to patterns. Through mathematics, we can begin to grasp this pattern-like behavior. Mathematics, developed through human perception, allows us not only to understand these patterns but also to influence them by identifying and controlling the key influencing factors.
So maths for AI??
As we discussed in the previous article, what AI basically does is capture the patterns of an incident and predict an outcome based on those patterns. Our human brain cannot consciously catch and process the patterns that are part of the complex web of causality. (Though they can be sensed spiritually — but that’s a topic for another time.) And that’s where mathematics comes in to save us in this logical realm.
Using mathematics, we can implement mechanisms to detect hidden patterns and identify the different components that influence those patterns within the web of causality. Then, we can build a model that runs on computational hardware, capable of predicting how the causality web will behave when we influence different parameters in different ways. This is what we call AI (Artificial Intelligence).
Conclusion
So that is why mathematics will be the driving force behind AI, enabling it to absorb universal phenomena, make predictions, and eventually influence them. Hope you got a good understanding about why we needed maths and why we use that in AI. Maybe you have a different perception about that, so let me know your thoughts as well in the comment section.
