To my JVM friends looking to explore Machine Learning techniques - you don’t necessarily have to learn Python to do that. There are libraries you can use from the comfort of your JVM environment. 🧵👇

IT WAS RISHI KANADA WHO GAVE THE ATOMIC THEORY & TALKED ABOUT THE GRAVITY OF EARTH, 2600 YEARS BEFORE AN APPLE FELL IN FRONT OF NEWTON'S EYES:

Scientists of the modern world credit an English scientist John Dalton (1766 CE -1844 CE) for the Atomic Theory.

And this is because, most of us are not even aware of an ancient Indian Sage named Kanada, who was the first to formulate the theory of atoms, almost 2600 yrs before Dalton and talk about earth's gravity.

Rishi Kanada was born around 600 BCE in Dwarka, Gujarat and he was the son of a philosopher named Ulka. He was fascinated with the minute detailing of the things right from his childhood. Once, when he was very young, he accompanied his father on a journey to Prayaga.

He saw plentiful grains scattered along the path leading to the shore of river Ganga. It's a tradition in Hindu families to scatter the grains for the ants and birds to feed on them. Suddenly, an ant caught his attention, who was feeding on a rice grain.

He was mesmerised by this very fact that how a small grain of rice becomes food for the ant but to satisfy the hunger of a person so many grains are needed together. This incidence made him realize the importance of a single grain of rice.

A thread on HN about bad code in legacy projects both makes me think how little we've learned as a discipline over the years and, honestly, how little credit we give ourselves for some pretty major

Fun going down this list and thinking: "Hmm, plausible at a well-run modern software shop", "Hmm, possible, but requires implausible tradeoffs", "Literally disallowed by languages", and "If you were to attempt doing that our test suite wouldn't let you merge."

I think we as an industry celebrate (not quite the right word) failure too much and don't celebrate success nearly enough. There is no DailyWTF for competent execution, word of which generally stays pretty local to the source while incompetence passes into legend.

Alrighty let me try to thread the needle on being the change I want to see in the world while not giving away anything that will get me in trouble:

Ruby has wonderful developer ergonomics. Typed languages are easier for machines to guarantee the correctness of. We built a type checker for Ruby (and I believe it is slated for OSS release sometime).

c.f.

💬 I often get Q’s like these:

How did you get your first customers for WIP? How did you grow BetaList’s traffic? Etc.

Makers are looking to reverse-engineer success. I see it everywhere.

I don’t think it works that way and the answers to those questions are mostly useless. 💥

I have built dozens of different products over the last couple of years. The vast majority failed. 😭

Surely if I know the answers to these questions, but still fail over and over again, these answers aren’t that useful. 🤷‍♀️

So what’s a better question to ask? 🤔

99.9% of the questions I receive are about the products that did well. In a way that makes sense, because we quickly forget about those that didn’t succeed.

🧠 This is known as survivorship bias.

Focusing on what survived, while ignoring what made it survive in the first place.

The real question, what you really want to know, is this:

What makes @WIP, @BetaList, and to some extent @AllStartupJobs succeed where my countless other attempts failed?

What separates a failed product 👎 from a successful product 👍?

Honestly, I don’t know. I wish I did.

It’s like Steve Jobs said “I’ll know it when I see it.” 👀

Same is true when we make products. We don’t know upfront what will work. But once we see an inkling of a product that does have potential, it’s not that hard to spot.