About Ashok Khosla


Inka khipus remain one of the world’s last undeciphered historical mediums. Are they writing? or just record-keeping? What do they mean? We admire the Arabs who brought us the concepts of 0 and base 10, and replaced Roman mathematics. The Inkas did that also. We admire the Romans who conquered a continent. The Inkas did that also. I could keep going but you get the idea. As an American immigrant, I am painfully aware, how notably blind “western civilization” is to the accomplishments of our South American neighbors.

The Inka’s unique approach to communication, using cloth as a medium, has fascinated me for much of my adult life. As a child I loved to read books about code-breakers and script decipherer’s. As a young unemployed architect, I read with fascination, and a little bit of envy, the story of British architect Michael Ventris. Ventris built on the work of Alice Kober to decipher the Mycenaean Greek script Linear B. As an adult, I have been amazed at how rapidly 2000 years of Mayan writing have became understood in a mere 50 years. It is an incredibly moving thing to hear Linda Schele recite the history of a people from a thousand years ago, in their own language.

Twenty years ago, I picked up Ascher’s Mathematics of the Incas - Code of the Quipu in a Berkeley California bookstore. And after a quick read, it sat on my bookshelf, waiting to inspire me again. For the last thirty years I have worked in the field of Natural Language Processing (NLP). We used to call it Computational Linguistics, but frankly we were never very good linguists, and Natural Language Processing is a humbler and more accurate term. We’re the idiot savants that provide the 21st century equivalent of the secretarial pool. Every once in a while, I’d think, gee - could I apply everything I’m learning in NLP to khipu decipherment? Then a few years ago I met a professor in Ecuador, and I started learning Quechua, and before I knew it … I had become a knot-head.

In the last 70 years, decipherment has become a community activity. Everyone contributes some little tiny thing, and then all of a sudden - !!!WHAM!!! a key synthesis emerges from all those little things. Any language dreamer dreams that they might be The One, who after enough hard work, gains an insight that changes directions. But the truth is, we dreamers… (yes, I’m one)…, we dreamers are content if we are able to contribute one tiny thing. This, perhaps, is my one tiny thing.

I am indebted to two scholars who have aided my education and the creation of this Field Guide.

Project Scope

This is a large project. As such it is divided into three phases:

Phase 1 - Reading and Writing (Completed)

In phase 1 a basic understanding of khipu was achieved. This involves five steps.

  1. Yak Shaving - All data science projects start by yak-shaving, the affectionate name for the process of cleaning data, checking for integrity, etc. This project was no different - Sadly, integrity checks led to a loss of one-sixth of the khipus from the database. After removing the khipus that failed integrity checks, the Harvard Khipu Database SQL tables were transformed into CSV spreadsheets capable of being viewed in a variety of applications. The current database, now the largest well-formed khipu database in the world, has taken over 3 years to build.

  2. Exploratory Data Analysis - What kinds of knots are there, how are knots, cords, cord colors and clusters distributed. What are likely spreadsheet khipus, and what are possibly something else such as a narrative khipu? What things do we want to emphasize in rendering?

  3. Class Building - Simple Python functions and the Python Pandas Dataframe library will not easily provide the type of functionality and interface we need to draw khipus and do more sophisticated data analysis. A Python class object has been built built for each Khipu component, knot, cord, cord color, cord cluster, primary cord etc. This class library then supports the rendering of Khipu and of more tailored types of data inquiry and output.

  4. Khipu Rendering - Many khipu scholars regard khipu as a “tactile medium” (think of khipu reading as a kind of braille for example). Understanding them from CSV tables, is the farthest thing from tactile. Rendering is needed. Producing the code to satisfactorily render khipu has taken four months. As the Russians say, “It’s not a miracle the bear dances well. It’s a miracle the bear dances at all.”

Phase 2 - Reproduction of Existing Studies (Ongoing)

Phase 2 of this project (now underway) is an exploration of existing work in khipu analysis. In this phase, I will attempt to identify and reproduce studies of existing khipu, such as Lockes UR166, or Urton’s Calendar Khipu UR006, the Ascher’s analyses of the Ascher khipus, Manny Medrano’s analyses of the Santa River khipus, the Pleiades star chart, etc. This journey will provide the smorgasboard of analyses types and analytical tools needed to do more decipherment.

Phase 3 - Using Data Science and Natural Language Processing (NLP) Techniques (Ongoing)

In Phase 3 modern Data Science and NLP techniques are being applied to Khipu.

The great bird educator and ornithologist, Roger Tory Peterson, produced the first bird “field-guide” of the modern age. Rather than simply showing a picture of a duck, Peterson had arrows that pointed out key features of a particular duck to look for in identification. The increased curve (the 2nd derivative in mathematical terms) of a bill of an avocet allowed you to identify it as female or male; the presence of a white rump patch allowed you to confirm that the raptor was in fact a northern harrier, etc. Now known as Fieldmarks, these key identification traits will be the outcome of Phase 3.

What types of Fieldmarks will we look for? As examples, we can examine verso/recto cord attachments, or the presence of Z vs S knots (i.e. Urton’s studies), or we could look for color and patterns (i.e. Sabine Hyland’s work), or cord distribution and summation patterns (i.e. Marcia Ascher’s detailed studies). Whenever I see something intriguing (as in it stands out), and at a higher level than a simple knot or cord characteristic, it will be noted as a potential Fieldmark. The goal of Phase 3 then, is to finish with a set of Fieldmarks that allow us to categorize khipu by “Family” - hence the name of this site - the Khipu Field Guide.

There is an old joke. Stupid scientist does an experiment with a frog.
    Jump Froggy! he says. Frog jumps. Stupid scientist cuts off one leg.
    Jump Froggy! Jump he says. Frog jumps. Another leg. Another jump.

    Finally he cuts off the last leg.
    Jump Froggy! Jump! Nothing happens. He yells louder
    JUMP FROGGY!!!! JUMP!!!! Nothing happens.

He writes in his lab notebook, “After cutting off fourth leg, frog became deaf.

So it is with khipu analysis. The decoding of unknown “languages” is fraught with stupid science. The goal is to use modern data science to tease out more information about khipus. Like Pygmalion, I want khipus to speak. I suspect, however, at the end of the day, I will be ecstatic, if I simply get them to mumble, squeak, or even make the sound of a punctured balloon.