Archives

Thanks to rapid advances in hardware and model efficiency, we’re entering a future where personal AI models tailored to you, run locally on your phone, PC, or wearable.

A Data-Driven Analysis of Its Downfall and Possible Rescue

Building AI agents today feels a bit like web development before the advent of modern frameworks - we're discovering fundamental patterns that will likely become standard.

How can we avoid these pitfalls and build robust AI agents? Through hard-won experience, practitioners have distilled a couple of core principles for context engineering.

Why providing the right context to large language models and AI agents is critical for reliable, advanced AI systems.

Who is this for? Curious engineers and product folks who want to _understand_ how an Eclipse Ditto digital twin talks to a physical/virtual device over MQTT (HiveMQ), without needing the full source code. We'll unpack the concepts and show the exact shapes of the messages Ditto expects.

Ditto is an open-source framework for building and managing digital twins of IoT devices. It acts as IoT middleware and integration platform that abstracts device access via standardized APIs

Exploring sums of random variables, covariance, correlation, and limit theorems (LLN & CLT). Key tools in probability and statistics to understand aggregate behavior, co-movement, and long-run patterns of random variables.

Exploring random vectors, joint distributions, conditional distributions, and independence — the foundations of multivariate probability with real-world applications.

Comprehensive exploration of probability mass, distribution, and density functions, their properties, and real-world applications.

A quick introduction to hypothesis testing and p-values, covering their meaning, importance, and common misinterpretations in data science.

A concise, practical primer on Bayes’ Theorem: statement, formula, derivation, and real-world uses in testing, spam filtering, A/B tests, recommenders, and ML.

Exploring the principles, challenges, and strategies of data science ethics—covering privacy, bias, transparency, regulations, and best practices for responsible innovation.

A journey through pursuing a Master's degree in Data Science at IIT India while balancing work and personal life, exploring the transformative power of data science in today's world.