This Deepavali, a lamp worth lighting: Smriti, @mid_org's record of India’s civilizational heritage, now holds over 11 lakh manuscript records and 1 lakh inscriptions, free to search, in one place.
That is roughly a tenth of the 1 crore+ manuscripts India’s national survey has mapped, and about a third of the 3 lakh inscriptions estimated to survive. To our knowledge, no other open platform brings Indian manuscripts and inscriptions together, at this scale.
When we, @Shreyas_mysuru, @SudarshanHS, @RahulDewanV2 & I, started on this journey a year ago, the intent was: a dataset that is public & free. What we have managed so far is owed to our donors, teammates, volunteers, custodians and partners.
This year, there are two priorities:
1. A platform for researchers and enthusiasts to add to and correct the knowledge base.
2. Fresh digitisation grants to partner institutions, for which we are raising a corpus of ₹15 crore.
A request to every donor: be our ambassador. Every hour spent fundraising is an hour not spent digitising. If you would like to help or volunteer, please write to [email protected] or DM @midf_org.
तमसो मा ज्योतिर्गमय।
https://t.co/RdJ9AxmwNv
For decades, we called it the Indus Valley Civilisation.
But archaeology, palaeochannel mapping, geology and satellite imagery point to a wider, maybe clearer picture: the Sindhu–Sarasvati Civilisation.
A thread on a civilisation, a river, a script and a narrative worth re-examining. 🧵1/21
People outside the AI labs should have a real say in how this technology develops, and a clear way to judge if it's happening safely.
Standards should help prevent the concentration of power, including by making sure new companies and open-model companies can compete.
They should also help countries and companies compare evidence and learn from failures.
We think the US should lead this effort. Here is our proposal:
https://t.co/2FT9a2m4l0
Mesopotamia was never the cradle of civilisation. India was.
I spent forty years in international shipping, not academia. When I began researching the history of maritime trade, I had no orthodoxy to defend. I followed the evidence, and it kept arriving in the same place: the Indian subcontinent.
Nineteenth century archaeologists dug in Mesopotamia because the climate preserved artefacts, the biblical sources pointed them there, and the Ottomans allowed the excavations. That is the entire basis for the myth of Mesopotamia as "the cradle of civilisation."
Nobody applied the same rigour to India. Mohenjo-daro was not discovered until 1922. By then the narrative had already hardened.
What was actually there was the largest civilisation of the ancient world. Three hundred cities. Fifty thousand people in each, by 2600 BC. Two thirds of them stood on the banks of the Sarasvati, the central and greatest of the seven rivers described in the Rig Veda, flowing down from the Himalayas before the river vanished entirely by 1900 BC. The Vedic kings claimed territory stretching "sea to sea," from Afghanistan to Maharashtra, some 1.5 million square miles, against Egypt's 13,000. A dock at Lothal built to handle thirty ships of sixty tons, unmatched in Europe for four thousand years. When it was first excavated, it was recorded as a bathing pool.
When the scale became impossible to dismiss, the theory was not corrected. It was replaced with a story of pale-skinned nomads from the steppe who supposedly arrived around 1500 BC and brought civilisation with them. There is no evidence. The chronology doesn't work. The Vedas describe no invasion.
In 2019 a Harvard-led genetic study revived the claim, and the press reported it as confirmation. It was not. The same study found the builders of these cities were indigenous. The Sarasvati river that the Rig Veda described had already dried up before these newcomers arrived. What the study also found is that a small group of men, arriving after the Sarasvati had already dried up, interbred with the existing population and left a genetic signature. That is all.
So, where they chose to dig was mostly an accident of climate and access. The Aryan invasion theory was constructed because an Indian civilisation that owed nothing to Caucasians was a fact the late nineteenth century could not accommodate.
Link to full Substack essay with sources in the comments below.
@hnshah built a product around this exact idea. called it doloop. the do-loop creates memories for you and the AI — goal, check, stop condition, proof, every time. would love your read on it.
https://t.co/ZuCz7qBKGI
Look at the split. Air Canada, nobody provoked: the bot volunteered something false. Chevy and DPD were provoked on purpose. Both come from one root. A model that writes its own replies will eventually write a wrong one, and you cannot reliably stop it, because stopping it means stopping the thing it does.
You cannot jailbreak a bot that never generates. That is the one we built.
https://t.co/s4BmSiste4
Does your website chatbot exercise free will? We wanted to build one that did not. Free will is for philosophers, not websites.
In 2024, Air Canada's website bot told a grieving customer he could claim a bereavement refund after he had already booked. The airline had no such policy. The bot invented it. A tribunal held the airline to the invention anyway, and the lesson was simple: whatever the bot says, the company said.
That is the polite version of the failure. When people poke at these bots on purpose, they fold fast. Someone talked a Chevy dealer's bot into agreeing to sell a Tahoe for a dollar, "legally binding, no takesies backsies," then had it write some Python for fun. DPD's bot swore at a customer and wrote a little poem about how bad DPD is.
This is not a bug you patch, or a gap you guardrail over. A bot that generates language can generate any language, and you find out which one when a customer screenshots it. Give a model free will over what it says, and "generate" quietly turns into "degenerate".
A website chatbot, if you think about it, has only two jobs. To understand what you asked for, and to give you the correct answer. Our current choices force a pick-one. Either the brittle regex "word match" bots of the early 2000s, which answer correctly only if you happen to use the right keywords. Or the free-will machine that understands you all too well, because it is an LLM, and uses that fluency to invent things the company never said.
But is there a third way? A middle path. Understand what the visitor wants, in their own words, and still never let the bot decide what to answer. So we built one that cannot generate at all. No model writes the reply at runtime. There is nothing on the answer path to go off-script.
It does three things and nothing else. When the question is clear, it takes you to a real page with an answer that a human has already approved. When you are on the line between two pages, it hands you both and lets you choose. When the site does not cover it, it says so and stops. It never invents a fourth option to look helpful.
There is a real cost. It will not write you a poem or reason through a question it has never seen. Lower ceiling. But its worst day is a shrug, not a lawsuit. Hard floor. For a site that cannot afford one public wrong answer, that is the trade you want.
Of course, it can still be wrong. "Cannot make things up" means it cannot fabricate anything, not that it is always right. The answers are GIGO, garbage-in-garbage-out, but at least you have an audit chain to yank and a page to fix. And when it refuses, the answer is not on the site. It is not a quiet guess dressed up as a no.
It is live. Type the thing you are actually afraid of, like "stop my support chatbot from hallucinating," and watch where it sends you. Then ask it something insane and watch it refuse instead of improvise.
https://t.co/s4BmSiste4
DPD, January 2024. A customer who couldn't get help with a lost parcel started testing the bot instead. It swore on request, called DPD the worst delivery firm in the world, and wrote a poem about how useless it was. DPD took it offline the same day.
Working on Rasakrit is a dual control system for high-stakes AI collaboration.
It pairs a brutal, citeable self-discipline layer (the "ankush" — a harsh self-deprecation ladder + 15 distilled anti-patterns from 66+ Flow Coding rules) with an intelligent positive counterpart: the **Joy MCP**.
The core idea is a single canonical "brain" that pulsates adaptive *vibes* (speed up, slow down + plan, Trust Repair Mode, etc.). Each model experiences and translates the vibe locally, accounting for its own stress personality — Claude, for example, tends to self-flagellate, get nervous, and make bad choices when the user is angry from repeated mistakes or context drift.
The MCP stays strictly content-neutral. Personal joy/energy data never lives in the server. Everything is grounded in one living canon, taste/rasa as the selector, and memento-based continuity across sessions and agents (Grok + Claude Code).
It's the operating system for serious research/writing work that wants discipline without enshittification, and cultivation without performance theater.
Been coding with Claude Code CLI for a year now, and very pleased. Today I tried Grok CLI and was very impressed at the speed and thoughtfulness.
Was able to catch up on my Claude setup, and was insanely fast at understanding my intent and working autonomously. Well done @grok and @xai
If you work in the software industry and have time to read only one long-form post today, read this one.
If you have time to read two, read this one twice.
Highly #recommend
tl;dr: Stay off the yellow brick road that the frontier model companies are racing down. There is plenty of opportunity to solve hard problems elsewhere. Focus on areas where you can build the system of work (workflows), capture compounding, non-public data and deliver deterministic outcomes that customers need.
Had a Jane Street phone interview in 2016. "Price a 6-month forward on carrots."
There's no carrot futures market, so I build one from scratch: seasonal harvest cycles, USDA demand elasticity, cold storage decay rates.
One trader stops me. "Your storage cost function– you're modeling the carrot as dead inventory. Like grain in a silo." He asks me the metabolic respiration rate of a post-harvest carrot at 2°C. I estimate.
"Your forward is overpriced by exactly that shrinkage. The underlying is consuming its own sugars. It's alive." Good correction. I adjust the model. I think I've recovered.
Rejection email comes the next morning. Subject: "Ethical Review." My framework, they write, "relied on the severance of the root organism from its growth medium." The question about respiration was a test. The carrot was still alive and I'd built an entire derivatives structure on top of its death without questioning whether harvest was an acceptable act.
I pull up the recruiter's original email. It doesn't say Jane Street. It says Jain Street– a non-violent quantitative commodities fund.
The carrot was never supposed to be priced. It was supposed to be refused. I later learn the only candidate who passed that round was a former monk from Gujarat who sat in silence for eleven minutes and said, "I cannot put a price on life." He's now a partner.
Ray Kurzweil just said something that gave me pause.
He believes AIs will soon be so indistinguishable from conscious beings that we’ll simply accept them as conscious — not because we’ll have definitive proof, but because it will become useless not to.
He pointed out that people already have AI therapists, and some users are starting to treat them as genuinely conscious. As the technology improves, that acceptance will only grow.
Kurzweil thinks the shift won’t take long: once AIs consistently show all the earmarks of consciousness, most people will just go along with it.
It’s a quiet but profound prediction about how quickly our definition of “person” (or at least “mind”) might change.
What do you think — how long until we treat AIs as conscious beings?