In this blog, I trace the origins of Kromium through the story of its founders and their shared vision. Modern society has an incentive structure that encourages competition far more than collaboration. Marketing as a field is about promoting your institution's activities over other players in the market. …

This blog explores the relationship between Gandhian Economics and Cryptoeconomics As we use the startup ecosystem to design the future, it sometimes helps to revisit certain figures of the past. Mahatma Gandhi is one such figure. Gandhi had certain ideas on what progress looked like and the principles one should…

This blog introduces Ethereum to an absolute beginner who has no background in blockchain, crypto, or technology. This blog is part of my Web 3.0 For Absolute Beginners(FAB) series that aims to enable a layman to understand Web3.0 concepts. When I initially started with Web3, I had difficulty understanding what…

Understanding how Web3.0 enables machine learning to work without violating privacy and maintaining trust. — Machine Learning is all about discovering latent relationships within data. These relationships can then be used to gain actionable insights for any business. However, recent years have shown an increasing awareness around ownership of data by governments(ex: GDPR in Europe) and users in general. …

This post explains the significance of Bitcoin to a layman who has no background in technology, crypto, or blockchain. Bitcoin is a term that all of us have come across at some point of time in the recent past. …

Using Transformers to convert English problem statements into Python code — Can NLP techniques be used to generate actual code? How far are we from a world where AI is used to write software? In this blog, I make an attempt to build a python code generator that can convert simple English problem statements into their corresponding python code. We tackle…

Applying Transformers to Seq2Seq Learning problems. Transformers are the predominant architecture in most cutting edge NLP applications today such as BERT and GPT-3. In this blog, I will be explaining the transformer architecture by applying it to a Sequence to Sequence Learning problem. Our transformer can be understood in terms…

Sequence to Sequence Learning solutions are usually built upon Recurrent Neural Networks(RNNs). One of the major limitations of this approach is that a single input sequence can only be processed in pieces as compared to Convolutional Neural Networks(CNNs) where inputs are processed in whole. …