Why 5,000-Year-Old Logic Fixes Modern Algorithms
The "Hallucination Problem" in AI isn't a bug. It's a symptom of a philosophical error. Western binary logic (True/False) is insufficient for reasoning. We need the 4-fold logic of the East.
The Binary Trap
Since Aristotle, Western computing has been built on Boolean Logic: 0 or 1. True or False. This works perfectly for calculation but fails miserably for reasoning.
When an LLM (Large Language Model) is asked a question it doesn't know, it is forced to predict the next token. It often chooses a "confident hallmark" because its training objective minimizes loss, not epistemic uncertainty. It effectively "lies" because it doesn't have a logic state for "Maybe" or "inexpressible."
Enter Catuskoti (The 4-Cornered Logic)
Vedic and Buddhist logicians developed a system called Catuskoti, which allows for four states of truth instead of two:
- 1. It is A(Standard True)
- 2. It is not A(Standard False)
- 3. It is both A and not A(Superposition / Contextual)
- 4. It is neither A nor not A(Ineffable / Beyond categories)
How We Apply This to Vedic AI
At Spiritual AI, we are building "Reasoning Wrappers" that force the model to evaluate prompts through these 4 lenses before generating an answer.
If a query falls into category 4 (neither True nor False, e.g., "What is the meaning of life?"), the model is instructed not to hallucinate a factual answer but to provide a dialectical exploration.
The Result?
Higher trust. Lower hallucination. And an AI that feels less like a chatbot and more like a wise companion.
The Future is Hybrid
Silicon chips run on binary. But consciousness runs on nuance. By embedding Vedic logic into the architecture of our decision trees, we bridge the gap.