Welcome to Aavishkar.ai Expert Systems: Accelerating Scientific Discovery through AI Scientific research today faces unprecedented complexity. Traditional research methods are limited by specialization, fragmented knowledge, and accessibility barriers. Aavishkar.ai...
A Wolfram Summer School 2024 Project For this edition of the ‘AI for Science’ Newsletter, I share with you my work done under the guidance of the Wolfram Summer School, exploring how the wolfram language can be used to build semi autonomous LLM agents for...
A lot of the current advancement in applied AI is a result of work done over the last decade to collect, curate and make available the training data , that is unlocking such capabilities in the latest deep learning models. However that was largely done for...
While various AI technologies could enhance discrete stages of the scientific research workflow (as described in Edition 1), large language models (LLMs) stand apart in their potential as an integrated research co-pilot across the entire process. As LLMs scale, they...
There is a small but diverse community of professionals that work at the intersection of academic research and Campus IT. Alternatively referred to as research computing facilitators, research data experts, system administrators etc. and broadly referred to as RCD...
There have been a number of well written pieces in recent days about emerging tech-stacks for AI (specially Gen AI) and how organizations can start thinking about setting-up and testing AI models in their workflows (e.g. Sequoia, A16z). While these articles are...
