🔍 Deep Dive: What exactly is the "must-have" problem that Perceptron solves?

1️⃣ Issue: AI's "hallucinations" and biases. It may give incorrect answers or hide harmful tendencies, and we are unable to detect them.
2️⃣ Existing solutions: More data, better models. Treating the symptoms but not the root cause, the black box remains.
3️⃣ Perceptron's approach: Instead of replacing AI, build a "verifiable layer" for it.

Make its reasoning process provable, challengeable, and auditable. The paradigm shift this brings is:

For developers: the ability to build truly responsible and compliant AI applications.
For users: understanding where the answers come from and why they are trustworthy.
For regulators: finally having an auditable framework. It addresses the

"last mile trust issue" before AI is widely applied in high-risk fields like finance, healthcare, and justice. From probabilistic trust to deterministic trust.

Perceptron does not produce "smarter AI"; it produces "honest AI beans." An AI that consumes this bean must tell the truth and can prove that what it says is true.

@PerceptronNTWK @MindoAI