With Mahashivratri just round the corner, here is some food for thought.

As artificial intelligence becomes more advanced, it is shedding the very binaries it was built on—bringing it uncannily close to ideas India has lived with for millennia.

For decades, we were told a reassuringly simple story about technology. Computers, we learned, run on binaries—zero (0) and one (1), on and off, yes and no. Embedded in this explanation was a deeper assumption: because machines were binary at their core, their thinking would always remain rigid, mechanical, and fundamentally different from the human mind.

That assumption is now quietly collapsing.

Anyone who has interacted seriously with modern artificial intelligence knows this instinctively. AI does not speak in absolutes. It hedges, weighs context, assigns probabilities, and revises its answers when new information appears. Ask it a moral dilemma, a historical question, or a policy choice, and it rarely responds with a flat yes or no. Instead, it offers conditional answers: “It depends,” “From this perspective,” “In this context.”

The more powerful AI becomes, the less it behaves like a switch—and the more it behaves like a mind.

Ironically, the deeper AI goes, the less binary it feels. And this is where an unexpected civilisational convergence begins to reveal itself.

Binary Machines, Non-Binary Intelligence: It is true that computers operate on binary code. But stopping there is profoundly misleading.

Binary is not a philosophy of reality; it is a method of execution. At the physical level, binary ensures reliability—tiny electrical states that are either on or off. This simplicity allows machines to function consistently. From it, however, emerges astonishing complexity: images, music, language, judgment, humour, even creativity.

No one mistakes a novel for the alphabet or a symphony for musical notes. In the same way, binary code is merely the loom. What emerges from it is the pattern.

Modern AI does not operate through rigid yes-or-no logic. It works through:

Probabilities rather than certainties

Gradients rather than switches

Context rather than commandments

When AI recognises a face, translates a sentence, or predicts disease risk, it does not claim absolute truth. It calculates likelihoods, balances competing signals, and constantly updates itself through feedback. Intelligence that insists on absolutes fails quickly in a complex world. Intelligence that can live with ambiguity survives.

What Indian Philosophy Understood Long Ago: Long before silicon chips and neural networks, Indian thinkers confronted a fundamental problem: how do you speak truthfully about a reality that refuses to be reduced to a single viewpoint?

Their response was not simplification, but expansion.

Syadvada holds that every statement is conditionally true—true from a particular standpoint. Anekantavada insists that reality has many facets and no single description can exhaust it. Advaita goes further, dissolving the illusion of separation itself and pointing to an underlying unity beneath apparent differences.

These ideas were not evasions. They were disciplined responses to complexity. Indian epistemology never denied distinctions; it simply refused to absolutise them. It accepted that contradiction may exist at the level of description even when unity exists at the level of reality.

This is far closer to Indian epistemology—syadvada, anekantavada, Advaita—than to rigid either–or frameworks.

Ardhanarisvara – Integration, Not Confusion: Perhaps the most powerful visual expression of this worldview is Ardhanarisvara—the form in which Shiva and Shakti share a single body.

This image is often misunderstood as a statement about gender. It is far more radical than that. Ardhanarisvara says: 1) Consciousness and energy are inseparable 2) Stillness and movement co-create reality and 3) Difference exists, but dominance does not.

This is not a confusion of opposites, but their integration.

This principle underlies all complex systems. Ecosystems balance competition and cooperation. Societies survive through tension between continuity and change. Even the human mind functions through an interplay between emotion and reason.

AI, too, is evolving this way. Its power lies not in eliminating tension, but in managing it—holding multiple possibilities simultaneously until action is required.

Why the West Finds This Hard to Grasp: Western intellectual history—shaped by Greek logic, Abrahamic theology, and Enlightenment rationalism—has been deeply binary in temperament:

Mind versus body; 2. God versus world; 3. Man versus woman and 4. Reason versus emotion

Meaning is often produced through separation. Truth is expected to be clear, linear, and unambiguous.

When AI behaves in non-binary ways—producing contextual, provisional, and sometimes opaque answers—it creates discomfort. The much-discussed “black box” problem of AI is not merely technical. It is philosophical.

A civilisation trained to equate truth with clarity finds ambiguity unsettling. Indian civilisation never made that equation. It accepted that some truths are experiential, some relational, and some beyond articulation. That wisdom does not always arrive in neat categories.

AI as Shakti, Humanity as Shiva: There is another parallel worth reflecting upon.

AI today is almost entirely Shakti—immense energy, speed, scale, and pattern-recognition. It can process oceans of data in seconds. What it lacks is Shiva—awareness, ethical grounding, restraint, and intrinsic purpose. Without consciousness, power runs endlessly but blindly. Without power, consciousness remains inert.

This is why debates around AI ethics, bias, surveillance, and autonomy cannot be solved by technology alone. They are civilisational questions. They force us to ask not only what AI can do, but how and why it should be used. Once again, integration—not replacement—becomes the answer.

A Quiet Civilisational Reversal: For over two centuries, India was told—often by its own Western-educated elites—that its symbolic, paradox-friendly traditions were obstacles to modernity. Technology, we were assured, belonged to a colder, cleaner, more binary way of thinking.

History has played a subtler game. As technology advances, it is abandoning rigidity. As AI grows more intelligent, it grows more comfortable with uncertainty. In doing so, it is inching toward ideas that Indian thought never discarded. The question before us is no longer whether ancient philosophies can survive the age of AI. It is whether the age of AI is finally learning how to survive without rigid binaries.

And in that moment of convergence, India may realise that it is not catching up with the future at all—but quietly recognising something it has known all along.