Founded in 2015 by Nandan Nilekani, Rohini Nilekani, and Shankar Maruwada, EkStep Foundation focuses on building digital public goods and delivering large-scale impact for billions of people. 

Working towards increasing access to learning opportunities for millions of Indian children, the non-profit organisation has developed Sunbird, a digital public good which powers DIKSHA, a national platform for school education led by the Ministry of Education in India.

However, now the foundation wants to leverage AI for the betterment of Indian citizens.

In June last year, the People+AI initiative was born out of the EkStep Foundation. It’s a community-driven effort that aims to harness AI capabilities to help a billion people. It brings together a diverse group of individuals, innovators, doers and tinkerers to find, test, and scale AI capabilities to address societal problems at scale.

Building AI use case repository 

Tanuj Bhojwani, who heads the People+AI initiative, told AIM that the foundation had been exploring the benefits of AI for quite some time. However, it was only in the past year that they decided to establish a specialised unit focused on extensively exploring AI use cases.

He believes that in a decade, India is going to be the AI use case capital of the world because of its huge population, diversity, languages and the need for specialised AI tools, be it in healthcare, education or any other field. 

“However, the biggest stumbling block right now is the lack of understanding regarding the potential use cases of AI. While building chatbots is undoubtedly crucial, there is a significant amount of work that still needs to be undertaken, especially in the context of India,” Bhojwani said.

Hence, People+AI is building a use case repository, which is an ongoing project focused on creating a structured library for AI use cases. This initiative involves defining a contribution model and designing a user experience to actively encourage and assist contributors.

“Our goal is to document and catalogue AI use cases that are particularly relevant and unique to India. Emphasis will be placed on identifying cases that are distinctive and specifically applicable to the Indian context,” Bhojwani added.

Building AI language tools

India is known for its linguistic diversity with over a thousand different languages and dialects spoken across the continent. EkStep Foundation has funded AI4 Bharat, an initiative led by the Indian Institute of Technology (IIT) Madras, focused on building open-source language AI solutions for Indian languages.

AI4Bharat is actively creating datasets for various Indic languages to train AI models. In many cases, the data collection process often requires visiting remote locations to record local dialects. To facilitate this, there is a requirement for various tools and resources.

People+AI is involved with stakeholders to determine if better tools and resources can be developed. “For this, we are collaborating and talking to different organisations, some in Africa, because they are also facing similar problems,” Bhojwani said.

A leaderboard for IndicLLMs

Moreover, People+AI is actively involved in developing a benchmarking leaderboard for Indic large language models (LLMs).

Several Indic LLMs and SLMs have emerged in the past few months, such as Tech Mahindra’s HindiLLM with 539 million parameters and Sarvam AI’s OpenHathi, a 7 billion parameters model trained on Hindi, English, and Hinglish.

However, there is no means to determine which of the two models mentioned above works better for certain use cases, say healthcare, for example.  

“A Malayalam-speaking nurse is going to speak in English when referring to medical terms, because such terms may not be commonly expressed in Malayalam. In such scenarios, a Malayalam language model (LLM) might not be effective. Instead, a model trained on both Malayalam and English medical datasets would be more beneficial,” Bhojwani said.

The objective is to establish a leaderboard to determine the effectiveness of models for various Indian languages. The leaderboard will feature default rankings and provide an option for users to “upload their own data”.

Hence, there is a growing need for an Indian use case-focussed benchmark and for this, People+AI is talking to different stakeholders in the Indian AI ecosystem such as AI4Bharat, Indian Institute of Science (IISc) as well as folks from BharatGPT. 

However, Bhojwani notes the project is still in its very initial stage.

Democratising AI computing in India

If India is going to be the AI use case capital of the world, a substantial compute infrastructure is imperative. People+AI is actively working on developing an open compute infrastructure network to meet the rising demand for compute while promoting market competitiveness.

“One of the ideas is can we decentralise computing infrastructure and create an open network where compute providers and customers who need this infrastructure can interact and discover each other,” Tanvi Lall, director of strategy at People+AI, told AIM.

The idea here, according to Lall, is to help a small business based in Tier 2 or Tier 3 cities access computing infrastructure for training or inferencing at a lower cost compared to leveraging services from the likes of AWS, Google or Azure, which could prove to be costly. 

People+AI is already talking to Indian computing service providers like NeevCloud and Vigyan Labs and the idea is to create a network of micro-data centres with interoperable standards, allowing small businesses and startups to easily plug and play, based on their specific requirements.