Saṃskāra: Who Trained Your Mind?

Episode 4 — Saṃskāra: Who Trained Your Mind?

BEGINNING — The Invisible Training

In the last episode, we saw that AI hallucinates — generating false information with total conviction. And we saw that the human mind does exactly the same thing. Adhyāsa, superimposition. Same mechanism, same conviction, same risk.

But a question remained: why does AI hallucinate the way it does? Why does it invent a specific author and not another? Why does it generate a response in this direction and not that one?

The answer is simple: because of the training data. Everything the model does — every word it chooses, every pattern it recognizes, every hallucination it generates — is a direct result of what it absorbed during training. Billions of texts, books, articles, conversations, forums, Wikipedia, Reddit, source code. This material is not neutral. It has biases, repetitions, gaps. And the model faithfully reproduces all of this — including the errors.

If the training data contains more texts stating that Columbus discovered America than texts questioning that narrative, the model will reproduce that version with more conviction. Not because it's true, but because it's statistically dominant in the corpus it absorbed.

Now replace "model" with "you".

If in your upbringing — family, school, culture, religion, media — there are more inputs stating that success is having money than inputs questioning that definition, you will reproduce that version with more conviction. Not because it's true, but because it's statistically dominant in the corpus that *you* absorbed.

In Sanskrit, this corpus is called *Saṃskāra*.

MIDDLE — Saṃskāra: The Impressions That Form You

*Saṃskāra* comes from the root *sam-kṛ* — to make completely, to prepare, to refine. These are the impressions that each experience leaves on the mind. It's not memory in the sense of "I remember that this happened." It's deeper. It's the mark the experience leaves on your mental structure — the groove that water carves in the earth by repeatedly flowing along the same path.

Each time you experience something, a Saṃskāra is formed. Each time you repeat it, the groove deepens. Over time, these grooves become the natural paths through which your mind flows. You don't consciously decide to follow these paths — they simply happen. They are your default patterns.

This is exactly how an LLM is trained.

During training, the model receives billions of text examples. With each example, the neural network's weights are adjusted — microscopically, but consistently. Each adjustment is a digital Saṃskāra. After billions of adjustments, the model has developed "grooves" — preferential paths of neural activation. When it receives a prompt, the response flows through these grooves. It doesn't "decide" to respond in a certain way — the weights naturally lead it there.

Notice the symmetry:

AI: Training data → weight adjustment → response patterns Mind: Repeated experiences → Saṃskāra formation → behavior patterns

In both cases, the result is not conscious choice. It is conditioning. AI doesn't choose to be biased — it was trained that way. You don't choose most of your emotional reactions — they were trained into you.

When someone criticizes you and you feel a tightness in your chest even before processing the content of the criticism — that's not you deciding to feel. It's a Saṃskāra activating. A groove so deep that the water doesn't even need to think to follow it.

---

END — The Lingering Question

Everything the model does is a result of its training data. Everything you do is a result of accumulated impressions — Saṃskāra.

But if conditioning is there, deep and automatic, a practical question arises: is re-training possible? In AI, there's a process called fine-tuning. And in Vedānta, there's something analogous — but it goes deeper.

Next episode.

---

*Series: AI and Vedānta — Episode 4 of 8* *Previous Episode: Hallucination (Adhyāsa)* *Next: Fine-Tuning — Is Re-training Possible?*