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Story Of This Mumbai-based Entrepreneur Who Is Enabling People To Read More AI Research Papers With Ease

Story Of This Mumbai-based Entrepreneur Who Is Enabling People To Read More AI Research Papers With Ease

Srishti Deoras

Are you an AI enthusiast who wants to keep abreast of the latest developments in space but do not know where to begin? This Mumbai-based computer science engineer may have an answer for you. 

With the number of papers and publications that are published each week growing exponentially, one of the biggest challenges for the AI and machine learning enthusiasts is to pick the papers that are trending in the space. There are very few dedicated platforms that host the archives of the technical papers and even fewer websites that surface and suggest top trending papers in AI, ML, computer vision and related domains. 

In fact, 42papers is one of a kind initiative that lets tech enthusiasts pick from the top trending papers. Founded by Vikram Rangnekar, there is nothing similar that exists today. It not only curates the best papers in the field on one platform but also lets the users immerse into a social and collaborative experience to discuss and read papers together. 

We got in touch with Rangnekar to dive into understanding more about his venture and how it has been benefitting the tech community so far. 



Idea To Reality

A computer science graduate from the University of Delaware and a tech enthusiast himself, the project started as a way for him to find a couple of good papers to read on each weekend. Rangnekar wrote a bot that slurped in discussions about papers from several sources and ranked them on various features including who the folks in the discussion were. 

“I shared it with friends who really liked the quality of papers the bot was discovering,” said Rangnekar, who is also the founder of MOV North, the largest community platform connecting global software engineers with Canada.

He further believes that reading papers is essentially a collaborative experience and is the way to surface great ideas. Considering the growing volume and depth of papers today, it makes sense to read them together. “Looking to grow my circle of folks interested in reading papers I built 42papers.com to be a collaborative community to discover and read great papers together on the web,” he shared. 

Why the name 42papers? Rangnekar is quick to share that the number 42 is a joke from a Douglas Adams book (sci-fi) that is popular among techies in the valley. “If you Google for “Answer to the Ultimate Question of Life, the Universe, and Everything” google will answer with 42,” he quipped. 

Bringing the AI & Tech Community Together

Rangnekar believes that academic papers are the building blocks of all technological progress. They are how research is communicated out into the world, and new research is built upon the foundation of existing papers on the topic. The big problem, however, is that in the field of AI and computer science, the number of papers published is growing exponentially and no one is able to keep up with the overload. 


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This tweet pins the problem in research outpouring:

“42Papers is working on solving this problem using crowdsourcing. Our bots scan the web for discussions around papers and using our ranking and scoring algorithms, surfaces the top trending papers. We bring to people papers they should be reading each week since everyone else seems interested in those papers,” he explained. Their collection of bots can go to places where people share and discuss papers, AI research, distributed systems, etc. Moreover, the ranking and scoring models consider what people are discussing, who are the people discussing the paper with, and more. 

As Rangnekar shares, they currently use more traditional machine learning models like logistic regression and LDA for ranking, scoring, etc. However, they are currently working on building deep learning models for named entity recognition which will help site search and paper recommendations much better. “At the moment, our focus is on building the deep learning models that will help us make more sense of the papers at scale. These are not easy to build and require a lot of paper reading and research on our end,” he said.

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Rangnekar takes pride in the fact that they have a fast-growing community of technologists on their platform bookmarking, sharing, making notes and liking papers which is all creating value for the whole community.

“I’m surprised by how many people are interested in the site, including folks from academia, corporate research, students and engineers. We are getting great feedback from people who are leaders in AI and startups in the valley,” shared an elated Rangnekar. 

For instance, Pete Skomoroch who led ML teams at LinkedIn and since then has sold his AI startup SkipFlag to Workday, uses 42Papers to find his reading list for the week which he also shares with various VC firms he’s involved with.

Wrapping Up

42papers.com contains papers from several categories such as machine learning, computer vision, natural language, AI, computer science, distributed systems, databases and more. While it has numerous papers on the site, “Hardware Lottery”, an AI paper by Google is the most read so far and is also one of his favourites. Another paper that is being read the most is on Auditing the EVM machines that run the Indian election. 

Users can visit the site to read the papers and sign up is only needed for bookmarking, making notes etc. 

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