TL;DR: LLMs summarize email well.
Ada Lovelace wrote to Charles Babbage in 1840 [1] showing interest in discrete mathematics, Srinivasa Ramanujan to G.H. Hardy in 1913 [2] on distribution of prime numbers. Much about written communication has changed since, so much so that in 2024, with an exponential volume compared to handwritten letters, (e)mail today has an increasingly rising chance of going unnoticed. Would Ramanujan hear back from G.H. Hardy today? With Large Language Models quickly beginning to take linguistic-inclined tasks over, and in the process, generating seemingly infinite words, one starts to wonder how much of it is being generated using LLMs...but more importantly, which communication is worth paying attention to?
The broader inquiry originated while trying to find ways to optimize startup and general business operations, probing whether a “single-person-company” is possible via modern day AI-enabled automatons. As a starting point, this project focuses on optimizing email traffic for a given user using Mathematica’s MBOX and MailRecieverFunction to a) analyze one’s current inbox for activity and behavioral insights, and b) set up LLM-based simple rules to equip the user with extremely short summary functionalities for a quick glance.
Ada Lovelace wrote to Charles Babbage in 1840 [1] showing interest in discrete mathematics, Srinivasa Ramanujan to G.H. Hardy in 1913 [2] on distribution of prime numbers. Much about written communication has changed since, so much so that in 2024, with an exponential volume compared to handwritten letters, (e)mail today has an increasingly rising chance of going unnoticed. Would Ramanujan hear back from G.H. Hardy today? With Large Language Models quickly beginning to take linguistic-inclined tasks over, and in the process, generating seemingly infinite words, one starts to wonder how much of it is being generated using LLMs...but more importantly, which communication is worth paying attention to?
The broader inquiry originated while trying to find ways to optimize startup and general business operations, probing whether a “single-person-company” is possible via modern day AI-enabled automatons. As a starting point, this project focuses on optimizing email traffic for a given user using Mathematica’s MBOX and MailRecieverFunction to a) analyze one’s current inbox for activity and behavioral insights, and b) set up LLM-based simple rules to equip the user with extremely short summary functionalities for a quick glance.
