New Delhi:

Union Minister Ashwini Vaishnaw on Friday praised the Narendra Modi-led government for focusing on new and emerging technologies, and allocating Rs 500 crore in the Union Budget 2025-26 to set up a Centre of Excellence in Artificial Intelligence (AI).

Speaking to NDTV, Mr Vaishnaw, who is the IT minister, said: “It was very important to get the complete facility so that researchers, academicians, start-ups get an opportunity to use those GPUs (graphics processing units), which are state-of-the-art… As part of the India AI Mission, we focussed on getting the complete facility and I am very happy to share that we have already empanelled 18,000 GPUs and these are really high-end ones. So with this, we have started the work on the foundational panel.” Follow Union Budget 2025-26 LIVE UPDATES here

GPUs are used to power data centres needed to train AI models. The number of GPUs needed for an AI model depends on how advanced the GPU is, how much data is being used to train the model, the size of the model itself and the time the developer wants to spend training it.

In March last year, the Centre announced a $1.25 billion AI investment, dubbed IndiaAI mission, which includes funding for AI startups and developing its own AI infrastructure.

Mr Vaishnaw said the budgetary allocation is “part of India AI missions, along with creating new Centres of Excellence because research is going to be a very important part of technology.” 

While presenting the Union Budget 2025-26 in the Lok Sabha earlier in the day, Union Finance Minister Nirmala Sitharaman said: “I had announced three Centres of Excellence in Artificial Intelligence for agriculture, health, and sustainable cities in 2023. Now a Centre of Excellence in Artificial Intelligence for education will be set up with a total outlay of Rs 500 crore.”  

Mr Vaishnaw also said the government has seen the algorithm efficiency of DeepSeek, a Chinese AI-powered chatbot. “Many more such innovations are going to come. I can say that our talent is really good and our people and researchers will bring out such innovations in the coming days,” he said.

DeepSeek has triggered a dramatic rethink on AI spending around the world, claiming it took just two months and cost under $6 million to build an AI model using Nvidia’s less-advanced H800 chips. 

Downloads of its app recently surpassed OpenAI’s ChatGPT on Apple’s App Store, while the cost and performance of its tools upended industry beliefs that China was years behind US rivals in the AI race.

Recently, Mr Vaishnaw had praised DeepSeek for shaking up the sector with its low-cost AI assistant, likening its frugal approach to his government’s efforts to build a localised AI model.

Mumbai:

Researchers at the Indian Institute of Technology Bombay (IIT Bombay) have uncovered how animals find their way back home without getting lost or being late by using a robot that mimics their movements.

This robot is designed to move on its own, much like an animal finding food and then to use light as a guide to return home (homing), the IIT Bombay said in a statement on Tuesday.

In a new study, researchers from the department of physics have used this robot to study the underlying principles of homing by animals.

“The primary goal of our research group was to understand the physics of active and living systems. We achieve this by performing experiments on centimetres-sized self-propelled programmable robots. In simple words, we model these robots to mimic the dynamics of living organisms, both at the individual and collective levels,” Dr Nitin Kumar, an assistant professor at the department of physics, IIT Bombay, said.

For their study, the researchers wanted to determine the time it took for the robot to return home, with increasing amounts of deviations from its homing path.

It was observed that the reorientation rate, the frequency at which the robot (or an animal) should adjust its direction for successful homing, originated from the degree of randomness in its path.

The researchers discovered an ‘optimal reorientation rate’ for a particular value of randomness beyond which the adverse effects of increased randomness are negated by more frequent reorientations, ultimately ensuring successful homing.

This suggested animals might have evolved to reorient themselves at an optimal rate to efficiently find their way home, regardless of the noise or unpredictability in their environment.

“The observation of a finite upper limit on return times indicates that the homing motion is inherently efficient. Our results demonstrated that if animals are always aware of the direction of their home and always correct their course whenever they deviate from the intended direction, they will surely get home within a finite time,” Kumar added.

Apart from physical experiments, the researchers also ran computer simulations where the robot’s movement mimicked animals.

This virtual robot combines active Brownian motion (the random motion of particles in a liquid or gas, caused by collisions with fast-moving atoms or molecules in the fluid) with occasional resets to its orientation to correct its course back towards home.

These simulations matched the experimental results, reinforcing the idea that randomness and reorientation work hand-in-hand to optimise homing.

“When we applied this model to the trajectories of a real biological system of a flock of homing pigeons, it showed a good agreement with our theory, validating our hypothesis of enhanced efficiency due to frequent course corrections,” Mr Kumar said.

He said in real and more complex systems, the homing cues might be more complicated than a simple uniform gradient towards home, as modelled in this experiment.

“In our future research, we aim to model these scenarios in our experiment by using a combination of spatiotemporal variations in light intensity and physical obstacles,” the assistant professor added.

(Except for the headline, this story has not been edited by NDTV staff and is published from a syndicated feed.)