Some of the most powerful theories in existence have come from paradoxes and thought experiments. One that continues to fascinate me is the St. Petersburg Paradox, probably because of its simplicity.At its core, the St. Petersburg Paradox is a deceptively simple coin-flipping game. The rules are: flip a fair coin until it lands heads. The payout … Continue reading From Paradox to Theory: An example from St. Petersburg
Tag: artificial intelligence
An optimistic, yet opinionated take on Vibe Coding
I've been exploring different dimensions of Vibe Coding over the past couple of months. It’s a nuanced topic, yet it often gets framed in extremes. The discussion surrounding it are hyperbolic to say the least. At one end of the spectrum, we hear about PMs spinning up full-stack products over a weekend and landing YC … Continue reading An optimistic, yet opinionated take on Vibe Coding
Rearrangement Correlation: First Principle Thinking to capture Non-linear Relationships?
Couple of weeks ago, I was hunting for a non-linear association measure for a use case I was working on. That’s when I came across this paper that introduces "Rearrangement Correlation." It provides a fresh take on the tried-and-tested Pearson's r. I couldn't use the result for my specific problem. Nonetheless, the paper is a pretty … Continue reading Rearrangement Correlation: First Principle Thinking to capture Non-linear Relationships?
Vapnik’s Principle: What was actually said?
If you google Vapnik's Principle, this is the first search result: When solving a problem of interest, do not solve a more general problem as an intermediate step We will come back to this "principle" later. Allow me to take a rather elaborate detour for now. Over the years, I've delved into several self-help books. … Continue reading Vapnik’s Principle: What was actually said?
Finally a good start for the foundational models for timeseries?
Plot twist: It is Chronos by AWS Supply Chain Optimization Technology (SCOT). NeurIPS 2023 saw a proliferation of papers on the applicability of LLMs in time series forecasting. Some of the papers were so bad that I seriously have started (and continue to do so) questioning the review process of NeurIPS. Seeing that particular trend, … Continue reading Finally a good start for the foundational models for timeseries?
Shah Mahdi Hasan 