Who is Prathosh AP? Why IISc Bengaluru Professor's Remarks on IIT Students Studying Shastra in AI Go Viral

An assistant professor at the Indian Institute of Science (IISc), Bengaluru sparked a conversation after he spoke about the importance of traditional Indian knowledge systems in an age increasingly shaped by artificial intelligence (AI), computer science and modern technology.

Prathosh AP’s remarks about IIT students, including those who scored well in the Joint Entrance Examination (JEE), drew attention and approached him to study Sanskrit and Shastras.

In a video shared on his X account, Prathosh challenged the conventional definition of success among students of top engineering institutions, arguing that education should not go beyond securing a high-paying job and accumulating material wealth.

“I’ll tell you, some of my IIT students are studying shastra with me today,” he said.

His comments also drew attention to the connections he made between ancient Indian philosophical texts, intellectual reasoning, and the ethical challenges posed by artificial intelligence.

Why are Prathosh AP’s comments going viral?

The main reason for the debate is Prathosh’s argument that the study of the shastras could complement modern scientific and technological education.

According to a report in India Today, he said some IIT students approached him to understand why they should study Sanskrit and traditional Indian texts despite taking demanding technical courses.

According to the professor, studying these texts could help students develop intellectual skills and challenge conventional notions of success.

He argued that the purpose of education should not be limited to entering a prestigious institution, securing a lucrative job and acquiring material possessions.

Prathosh also linked the study of traditional texts to the development of artificial intelligence, arguing that technological progress must be accompanied by a deeper understanding of human values and responsibilities.

He drew an analogy with the Mahabharata and reportedly suggested that algorithms should be designed to improve human life. He also questioned the implications of placing powerful technologies in the hands of people without an understanding of dharma.

At the same time, he warned against approaching ancient Indian texts only to look for references to modern scientific discoveries.

Using an agricultural analogy, he said, “You don’t grow a crop for the sake of the weeds, you grow a crop for the sake of the crop.”

What did he say about Nyaya Shastra, logic and intellectual development?

Prathosh outlined three dimensions of the study of the shastras: intellectual, social and metaphysical.

On an intellectual level, he argued that traditional Indian philosophical systems can help students develop structured reasoning, analytical thinking, and the ability to examine arguments.

Citing Nyaya Shastra, an Indian philosophical tradition focused on logic, reasoning, and methods of acquiring knowledge, he argued that someone who studied the subject for 12 years could be trained in quantum physics and mathematics within a year. He said he had conducted experiments to support this suggestion.

On a social level, he linked the study of dharma with questions of responsibility, especially in relation to new technologies.

On a metaphysical level, he referred to the Upanishads and their discussions of wealth, happiness and liberation. He quoted a conversation between Yajnavalkya and Maitreya in the Brihadaranyaka Upanishad, which examines whether material wealth can lead to immortality.

Who is Prathosh AP?

Academic profile:

-Faculty Member, Department of Electrical Communication Engineering, IISc Bengaluru

-Research areas: machine learning, deep representation learning, artificial intelligence and digital health

-Co-founder of Cogniable and LatentForce.ai

Prathosh AP is an academic and artificial intelligence researcher at the Indian Institute of Science (IISc), Bengaluru. His research focuses on machine learning, deep representation learning, data-efficient learning, and AI applications in healthcare.

According to his academic profile, he received his PhD from IISc Bengaluru in 2015, specializing in temporal data analysis. He completed his bachelor’s engineering studies in 2011, three years before submitting his doctoral thesis.

After completing his PhD, he worked in corporate research labs including Xerox Research India and Philips Research, as well as a startup in California, USA.

His industrial research, particularly in healthcare analytics, has resulted in several contributions to intellectual property. His profile lists 15 US patents, of which 10 have been granted and six have been commercialized.

He joined the Indian Institute of Technology (IIT) Delhi in 2017 as an assistant professor in the computing group of the Department of Electrical Engineering. He worked there for four years before joining IISc Bengaluru in September 2021.

He also co-founded Cogniable, a startup focused on developing learning algorithms for behavioral healthcare. According to his earlier IISc profile, the venture won first place in the Indian AI Startup Challenge.

His current professional website also identifies him as co-founder and head of AI at LatentForce.ai, an AI venture incubated at IISc.

What is his research focus at IISc Bengaluru?

Prathosh’s academic work is primarily focused on artificial intelligence and machine learning.

His research interests include:

– Deep representation learning: Developing artificial intelligence systems that can learn useful representations from complex data.

– Machine learning with limited data: Building models that can perform effectively when training data is scarce.

– Deep generative models: Development of artificial intelligence systems capable of generating new data and representations.

– Healthcare applications: Using machine learning and artificial intelligence to solve challenges in digital healthcare.

– Signal processing: Application of computing techniques for analysis and interpretation of signals.

His academic work combines theoretical research with practical applications, particularly in healthcare analytics and machine learning.

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