Frequentist or Bayesian, Who am I?

I am a Software Architect and an Independent Researcher who has designed and developed data products from Ideation to Go To Market at enterprise scale through my career. I am a perpetual learner who learn new things and make them work. My passion is Programming and Mathematics for Deep Learning and Artificial Intelligence. My focus area is Computer Vision and Temporal Sequences for Prediction and Forecasting.

Selected Reads Selected Watch More About Me

Selected Writes - AI, ML, Math

Evaluating Large Language Models Generated Contents with TruEra’s TruLens

Posted Mar 17, 2024 ‐ 41 min read

It's been an eternity since I last endured Dr. Andrew Ng's sermon on evaluation strategies and metrics for scrutinizing the AI-generated content. Particularly, the cacophony about Large Language Models (LLMs), with special mentions of the illustrious OpenAI and Llama models scattered across the globe. How enlightening! It's quite a revelation, considering my acquaintances have relentlessly preached that Human Evaluation is the holy grail for GAI content. Of course, I've always been a skeptic, pondering the statistical insignificance lurking beneath the facade of human judgment. Naturally, I'm plagued with concerns about the looming specter of bias, the elusive trustworthiness of models, the Herculean task of constructing scalable GAI solutions, and the perpetual uncertainty regarding whether we're actually delivering anything of consequence. It's quite amusing how the luminaries and puppeteers orchestrating the GAI spectacle remain blissfully ignorant of the metrics that could potentially illuminate the quality of their creations. But let's not be too harsh; after all, we're merely at the nascent stages of transforming GAI content into a lucrative venture. The metrics and evaluation strategies are often relegated to the murky depths of technical debt, receiving the customary neglect from the business overlords.

The 40 rules of love

Posted December 23, 2023 ‐ 41 min read

At the age of forty, Ella Rubenstein, stuck in an unhappy marriage, decides to work as a reader for a literary agent. Her first task is to read and review **Sweet Blasphemy**, a novel penned by Aziz Zahara. Ella is captivated by the story of Shams's quest for 'Rumi' and the transformative impact the dervish has on the cleric, turning him into a devoted mystic, passionate poet, and love advocate. She is intrigued by Shams's teachings, which reveal an ancient philosophy centered on the unity of people and religions, as well as the presence of love within each individual. As Ella delves into the narrative, she discovers parallels between Rumi's journey and her own life, realizing that Zahara, like Shams, has arrived to liberate her.

Airflow Trigger Rules for Building Complex Data Pipelines Explained, and My Initial Days of Airflow Selection and Experience

Posted May 1, 2022 ‐ 9 min read

Dell acquiring Boomi(circa 2010) was a big topic of discussion among my peers then, I was just start shifting my career from developing system software, device driver development to building distributed IT products at enterprise scale. I was so ignorant and questioned, 'why would someone pay so much for a piece of code that connects systems and schedules events'. I argued that those data pipeline processes can easily built in-house rather than depending on an external product. To understand the value of an integration platform or a workflow management system - one should strive for excellence in maintaining and serving reliable data at large scale. Building in-house data-pipelines, using Pentaho Kettle at enterprise scale to enjoying the flexibility of Apache Airflow is one of the most significant parts of my data journey.

Temperature is Nothing but Measure of Speed of the Particles at Molecular Scale - Intro 2 Maxwell Boltzmann Distribution

Posted January 23, 2022 ‐ 8 min read

The definition for temperature is it is the average kinetic energy of the molecules in the space. If you find the cup of coffee your girlfriend graciously gave you this morning is not hot enough, then you can confidently conclude the molecules in the coffee pot are as lazy as you are. When the particles in the space are active, bumping into each other and have a commotion to prove their existence, we can call they are hot. What makes one hot is directly proportional to the number of particles in their space of influence traipse from a steady-state to a hyperactive one. Often these particles move aimlessly that we witness while boiling water or cooking food. This phenomenon can be understood quite clearly via Maxwell-Boltzmann distribution which is a concept from Statistical Physics/Mechanics having significant importance in machine learning and cognitive science.

The Best Way to Minimize Uncertainty is NOT Being Informed, Surprised? Let us Measure Surprise

Posted January 14, 2022 ‐ 6 min read

Ignorance is bliss. We all know there is a deeper meaning to this phrase from a philosophical context that points towards lethargic attitude. I would like to define the word ignorance as a lack of knowledge or information. Often we believe the more information we have, the more we are certain about the past, present, and future events associated with that information. Information theory differs significantly on that belief, Thanks to Claude Shannon. i.e. the more the information we have, the more we fill the uncertainty bucket that we detest. Is there any fun in knowing that an event is absolutely certain to happen? for example, Proteas won the series(Cricket) against India. The improbable state of events brings more information which is the cause for all surprises to keep us sitting on the edge of the seat. Test cricket - Game of glorious uncertainties after all..! Hence, we shall learn more about surprises especially measuring surprises.


Selected Reads - Papers, Articles, Books

Density Estimation using Real NVP - GOOGLE RESEARCH/ICLR

This paper is going to change your perspective on AI research tangentially, if you stepping into Probabilistic DNNs. Start from here for unsupervised learning of probabilistic model using real-valued non-volume preserving transformations. Model natural images through sampling, log-likelihood and latent variable manipulations read...

The Neural Code between Neocortical Pyramidal Neurons Depends on Neurotransmitter Release Probability - PNAS

This 1997 paper brings bio-physics, electro-physiology, neuroscience, differential equations etc in one place. A good starting point to understand neural plasticity, synpases, neurotransmitters, ordinary differential equations read...

Using AI to read Chest X-Rays for Tuberculosis Detection and evaluation of multiple DL systems - NATURE

Deep learning (DL) is used to interpret chest xrays (CXR) to screen and triage people for pulmonary tuberculosis (TB). This study have compared multiple DL systems and populations with a retrospective evaluation of 3 DL systems. read...

Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization - IEEE/ICCV

How to approach compute complexities, ie time and space complexity problems while designing a software system to avoid obvious bottlenecks in an abstract fashion. read...

Evolve Your Brain: The Science of Changing Your Mind by Joe Dispenza - BOOK

Ever wonder why you repeat the same negative thoughts in your head? Why you keep coming back for more from hurtful family members, friends, or significant others? read...

Selected Watch - Social Media/OTT Content

Eureka : Dr V. Srinivasa Chakravarthy, Prof, CNS Lab,IITM

Interaction with Prof. Chakra, Head of the Computational Neuroscience Lab. Computational neuroscience serves to advance theory in basic brain research as well as psychiatry, and bridge from brains to machines. watch...

Quantum, Manifolds & Symmetries in ML

Conversation with Prof. Max Welling on Deep Learning with non-Euclidean geometric data like graphs/topology or allowing networks to recognize new symmetries watch...

The Lottery Ticket Hypothesis

Yannic's review of The Lottery Ticket Hypothesis - A paper on network optimization through sub-networks. This paper is from MIT team watch...

Backpropagation through time - RNNs, Attention etc

MIT S191 Introduction to Deep Learning by Alexandar Amini and Ava Soleimany. Covers intuition to Recurrent LSTM, Attention, Gradient Issues, Sequential Modelling etc watch...

What is KL-Divergence?

A cool explanation of Kulbuck Liebler Divergence by Kapil Sachdeva. It declutters many issues like asymmetry, loglikelihood, cross-entropy and forward/reverse KLDs. watch...

Overfitting and Underfitting in Machine Learning

In this video, 2 PhD students are talking about overfitting and underfitting, super important concepts to understand about ML models in an intuitive way. watch...

Attitude ? Explains Chariji - Pearls of Wisdom - @Heartfulness Meditation

Chariji was the third in the line of Raja Yoga Masters in the Sahaj Marg System of Spiritual Practice of Shri Ram Chandra Mission (SRCM). Shri Kamlesh Patel also known as Daaji, is the current Guide of Sahaj Marg System (known today as HEARTFULNESS ) and is the President of Shri Ram Chandra Mission. watch...