GRM is a unique platform where students remotely work on challenging short/long term technical projects defined by IBM mentors.
Students get the opportunity to interact with top IBM technical expertise and learn to use tools and strategies to get skilled and comfortable with gen next technologies and doing it online makes it easier to work from any part of India.
We divide this work into three modules - (a) Training Data Validation - goal here is to gain knowledge about the graphql, and then validate training samples that we have created. (b) Leaderboard - This is new emerging area - so, can we create leade
A program that can discover images and video files in a given data storage device/filesystem and help classify the discovered content in various classification categories- PII, Sensitive, Confidential etc. Possibly use ML to improve the accuracy of
Connected assets are the assets that are together involved in performing one or more business processes. If vulnerability/threat on one of the assets is exploited, because of the connectedness - it could lead to failures or disruptions to assets it i
Populate and enrich a benchmark of tabular data tasks for evaluation of LLMs with our evaluation framework. Primary work includes tasks and datasets selection, writing data loaders, preparing task cards with input/output details and pre-processing st
The project aims to explore the impact of Dynamic In-context learning approach for Generative MultiModal LLM and develop algorithm to enhance the LLM performance through representation learning approach.
To determine the Handwriting of a user to analyze PSYCHOLOGICAL behaviour
Design a data pipeline to ingest data from REST APIs. Ensure you use a REST client and a mechanism to schedule batch data processing using cron expressions. The Data Pipeline should include, Data extraction from API’s/Db2 table. Loading data t
To develop techniques using state-of-the-art AI methods to enrich the experience around LLM usage. Skills Required: Python, ML, DL, LLMs, Hugging Face, exposure to UI development
Generalize variational QEC to larger class of error correcting code Reference : https://arxiv.org/abs/2204.03560