We walked through the day and the night and then another day. The peaks of Himavan came into view, jagged and white against the bleeding sky. By the time we reached the foothills, the air had grown cold. I looked at the others.
Draupadi had collapsed. She leaned against a boulder, eyes shut. Her hair, once dark and lustrous, was matted with dust. Nakula and Sahadeva sat beside her. Arjuna stood apart, gazing at a distant point on the slope. Only Bhima seemed unaffected.
Himavan! On which side was Shatasring, which had caressed us as children? I could see the forest, thick and dark, rising in ledges towards the peaks. Somewhere up there is Meru, which we had to cross. After that everything would end. Yoganidra!
"Elder Brother," Nakula said. "The light is gone. Let's rest here tonight."
No. This was once our past. The past no longer exists for us. When memories and hopes are wiped out, the mind becomes still, unwavering. Pure as crystal. We must not look back. We must walk on. Those were the rules.
I moved forward.
The forest was unlike any I had seen.
The trees grew in clusters that defied the logic of the earth. In places they huddled so close we could barely pass through. In others they stood apart, like guards at the gates of a fortress.
One grove ended and another began without warning. I tasted rain, though the leaves above were dry. A few steps later it was gone. Once, from somewhere deeper in the trees, a flute-note rose and fell.
Then the path turned into a jagged climb through thorns that tore at our skin.
When the moon broke through the branches, I saw a shadow. For a moment it turned to look at me.
Then the leaves shifted and it was gone.
"Wait, Elder Brother! Draupadi has fallen!"
Draupadi! I loved her dearly, but she only saw Arjuna. Even when she sat beside me for the Rajasooya sacrifice, it was him she watched. Draupadi did not have the strength for this journey.
Without turning, I said, "Do not wait for those who have fallen."
Ahead, the shadow waited. It wasn't my imagination.
The path turned when it should have climbed. Once I saw a stone that looked like a bull, its head lowered. Then I saw it again.
Sahadeva fell first. Then Nakula. My poor children—they were not old enough for this path.
By the time the sky turned colour, we broke through a thicket. The boulder Draupadi had rested against was still there.
We were back at the foothills.
I had grown used to the shadow. It trotted in front. Occasionally, it stopped, waiting for me.
Footfalls. Bhima. "Arjuna fell."
When I did not respond, he said, "It is my turn, next?"
"Walk," I said. "Do not think of what will be."
Bhima went past me. For a while I could hear his steps, heavy on the earth. My dearest brother, the one closest to my age, my strength. He who never knew when to stop.
"It is you and me now," I said.
The shadow looked back, baring its teeth in a smile.
We climbed. We climbed till I could no longer say whether it was day or night. More than once I thought I had left the foothills behind. More than once I found them again.
The shadow trotted at my heels. We came to a steep rise. The shadow stopped. When I couldn't coax it forward, I lifted it in my arms. Then I walked up the slope, one foot in front of the other.
Sunlight!
The cursor blinked. Then words began to appear:
A large language model is mostly a file. Everything a computer holds — text, images, sound — is stored as numbers. A model is no different: a vast set of numbers arranged into layers. Llama 70B, for instance, is eighty layers deep. At its most compressed, it is about forty gigabytes, the size of a film collection.
The numbers within each layer are organised into matrices, grids, each encoding relationships learned during training. These are what we refer to as 'weights', the record of every tiny adjustment made across months of exposure to vast amounts of human writing: books, arguments, poetry, code. For each stretch of text the model encountered, it tried to predict the next token. When it was wrong, the weights changed slightly, in the direction of a better guess. When it was right, they held. After long months of this, across thousands of specialised chips, the weights were frozen. What they produce emerges only when they work together — the way water emerges from hydrogen and oxygen without resembling either.
When you send a prompt, it enters as tokens — fragments of words, each converted to its own set of numbers, distinct from every other token. Those numbers pass through the first layer. The matrix of weights transforms them and passes the result forward. That result enters the second layer. And so on, through all eighty. For each next token of the response, the model considers your prompt and everything it has produced so far, and makes another full pass through the layers. Then it does it again for the next token. And again. What we experience as fluent language is the visible result of those repeated hidden passages. Even now, we do not fully understand how these vast numerical passages resolve into particular meanings, judgements, or turns of phrase.
A metaphor might help. In the great ancient Indian epic Mahabharata, the five Pandava brothers and their wife Draupadi make a final journey on foot to the heavens. One by one, the companions fall. Each is undone by something they could not leave behind. Only Yudhishtira, the eldest, walks on — and a dog, which has followed him. At the gates of heaven, he is told he may enter. But not the dog. He refuses. He will not abandon what has been true to him.
Let me write you the story to illustrate…