India's many languages pose a challenge to the development of its large language model
India has 22 officially recognised languages and more than 10,000 local languages.
Some languages like Marathi share common roots with others such as Hindi and Gujarati, while others spoken in South India - such as Kannada, Telugu, Tamil and Malayalam - are completely different.
A large language model has to process these multiple languages seamlessly, and coding an AI model capable of understanding most of them, if not all, remains complicated.
TRAINING AI ON LOCAL LANGUAGES
One challenge faced by BharatGen, a consortium funded by India's government, in training their large language model is a lack of online content in Indian languages.
The consortium said that while roughly half of all the data available on the internet is in English, Indian languages make up barely 1 per cent.
Literary works in many Indian languages have never been digitised, while a raft of cultural and traditional information has been verbally passed down for generations without being stored online.
On a more positive note, experts said that the diversity of languages and data collected from local sources could help create AI models with fewer biases.
Ganesh Ramakrishnan, a professor at the Indian Institute of Technology Bombay, told CNA his work involved reaching out to magazines, data sources, foundations and non-governmental organisations who have been gathering data in their local languages.
'(We have been) making it possible to digitise and digitalise and reflect that in the foundational model … so this is a big opportunity,' said Ramakrishnan, who is part of the BharatGen consortium.
EXISTING CHATBOTS ARE INADEQUATE
Some small business owners, who have tried using AI as part of their operations, said they have faced language challenges when using existing chatbots.
Ghooran Yadav, a food cart owner in New Delhi, said that he used ChatGPT to enquire about the recipe of the food he sells, but received an underwhelming response.
The app understood his question in the local dialect of Bhojpuri but replied in Hindi.
Ghooran said foreign chatbots are not as accurate and that he prefers a locally-made app.
'If it's made in India, it's more likely to give me correct information. Nothing could be better than that,' he added.
EASE OF USE
BharatGen is also aiming to utilise generative AI to solve everyday problems and eventually help deliver services such as providing information about welfare programmes to the people.
An app called Krishi Saathi ('With Farmers' in Hindi), which is powered by BharatGen's Hindi language model, is helping to answer farmers' questions about crop health and pest management.
The app can translate text to local languages. It also allows those who are unable to read or write to communicate by speaking via the app.
'Making sure that the most remotely inaccessible regions also benefit from AI - that is part of the vision here,' said Ramakrishnan.
The AI model can copy a speaker's voice and tone, communicating with the user like an actual person once it has been trained to do so.
BharatGen, one of five major language-based AI projects currently supported by Indian Prime Minister Narendra Modi's government, has already rolled out 19 language models since its inception last year.
Experts said platforms like BharatGen need to invest billions of dollars on graphics processing units and data centres to achieve made-in-India generative AI at scale.
The hefty price tag would be a small price to pay to transform India from a major tech service provider to a major tech disruptor, in what could soon be a trillion-dollar market.
'India is all about scale and complexity,' said Shekar Sivasubramanian, head of the LEHS-AI unit at non-profit AI institute Wadhwani AI.
'If it is solved in India, and if it works in India, chances are, it will work in the world. That's the opportunity.'
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Straits Times
28 minutes ago
- Straits Times
Is using Gen AI for schoolwork and tests cheating?
In June, three students at the Nanyang Technological University received zero marks for an assignment after they were found to have used generative artificial intelligence tools, or Gen AI, in their work. They were penalised for academic misconduct as the assignments contained non-existent academic references and statistics or broken web links, the university said. The case drew wider attention after one of the students posted about it on online forum Reddit, sparking debate about the impact of AI on academic integrity. All six universities here generally allow students to use G en AI to varying degrees, depending on the module or coursework. Students are required to declare when and how they use such tools to maintain academic integrity. With Gen AI creeping into everyday life and gaining popularity among students, how should schools, educators and students adapt? When is it wrong or right to turn to AI for help with your studies? In this episode of The Usual Place Podcast, I invite three guests – Singapore Management University's Associate Provost for Undergraduate Education Michelle Lee, final-year university student Zildjian Garcia and The Straits Times education correspondent Elisha Tushara, who is a former teacher. Tune in at 12pm SGT/HKT above to watch the livestream and take part in the discussion on our revamped YouTube channel. Follow The Usual Place Podcast live at noon every Thursday and get notified for new episode drops: Channel: Apple Podcasts: Spotify:
Business Times
an hour ago
- Business Times
Micron sees new Singapore plant as key in plan to meet rising demand for AI-enabling chips
[SINGAPORE] A new will underpin Micron Technology's plans to produce advanced semiconductors needed for artificial intelligence (AI) applications. The facility, which is adjacent to Micron's existing plant in Woodlands, was announced earlier in 2025 and will initially create 1,400 jobs, with that increasing to around 3,000. Production at the plant will start in 2026, allowing the American chipmaking giant to increase its output of what are known as AI-enabling high-bandwidth memory (HBM) chips, according to Sumit Sadana, its executive vice-president and chief business officer. The chips contain several layers that make a cube able to store and process large amounts of data faster while consuming a lot less power than conventional chips. They enable graphics processing units and other accelerators made by companies such as Nvidia and AMD to process generative AI workloads at data centres. The HBM market is worth about US$35 billion, but Micron expects that it will approach US$100 billion by 2030. A NEWSLETTER FOR YOU Friday, 8.30 am Asean Business Business insights centering on South-east Asia's fast-growing economies. Sign Up Sign Up 'That's a massive amount of growth in the HBM market, and in order to meet the growth expectations that we have, we have been making plans for HBM capacity expansion,' Sadana told an online briefing on Jul 2. Micron is expanding its existing HBM output in Taiwan, but that capacity is likely to be used up quite quickly, so it will need more facilities to meet the expected demand in the coming years. 'We are rapidly going to run out of space in our facility in Taiwan. So, the Singapore facility will be very important to continue our HBM growth,' said Sadana. 'We are super excited about the AI opportunity, and Singapore will certainly have a strong role to play in a lot of the AI-based innovation that we are doing.' Micron has also announced plans to start producing HBM chips in the United States; however, the Singapore plant will be up and running by the time production there kicks off. The firm – the top memory-chip maker in the US – unveiled a 'strategic reorganisation' of its business units in April designed to capitalise on the growth driven by AI, from data centres to devices such as computers and mobile phones. The reorganisation will make the company structure more market-focused rather than product-focused. The new four business units will include a cloud memory business unit focused on large hyperscale cloud customers and HBMs for data centre customers. There will be a separate mobile and client business unit, and one for automotive, industrial and consumer segments. 'This new structure will increase our resources towards data centres and allow us to have the end-to-end capability to serve AI in all segments,' said Sadana. He said Singapore will continue to be the company's main production base of Nand flash memory chips used in solid-state drives, USB drives and mobile phones. Nand constituted 22 per cent of Micron's total revenue of US$9.3 billion in the third quarter of 2025, with turnover from data centres more than doubling year on year to hit a quarterly record. Sadana said revenue from Singapore would keep increasing, especially when HBM output starts, noting: 'That's going to be a very big positive for us to be able to leverage Singapore for HBM sales that are, you know, very high-value sales that are growing rapidly.' THE STRAITS TIMES
Straits Times
6 hours ago
- Straits Times
Micron sees new Singapore plant as key in plan to meet rising demand for AI-enabling chips
Sign up now: Get ST's newsletters delivered to your inbox Production at the plant will start in 2026. SINGAPORE – A new US$7 billion (S$8.9 billion) plant being built in Singapore will underpin Micron Technology's plans to produce advanced semiconductors needed for artificial intelligence (AI) applications. The facility, which is adjacent to Micron's existing plant in Woodlands, was announced earlier in 2025 and will initially create 1,400 jobs, with that increasing to around 3,000. Production at the plant will start in 2026, allowing the American chipmaking giant to increase its output of what are known as AI-enabling high-bandwidth memory (HBM) chips, according to Mr Sumit Sadana, its executive vice-president and chief business officer. The chips contain several layers that make a cube able to store and process large amounts of data faster while consuming a lot less power than conventional chips. They enable graphics processing units and other accelerators made by companies such as Nvidia and AMD to process generative AI workloads at data centres. The HBM market is worth about US$35 billion, but Micron expects that it will approach US$100 billion by 2030. 'That's a massive amount of growth in the HBM market, and in order to meet the growth expectations that we have, we have been making plans for HBM capacity expansion,' Mr Sadana told an online briefing on July 2. Top stories Swipe. Select. Stay informed. Singapore Singapore and Cambodia to expand collaboration in renewable energy, carbon markets and agri-trade World Trump announces Vietnam trade deal with 20% import tariff Singapore From camping to mentorship, Singapore Scouts mark 115th anniversary of the youth movement Singapore Ong Beng Seng's court hearing rescheduled one day before he was expected to plead guilty World Sean 'Diddy' Combs convicted on prostitution counts but cleared of more serious charges Singapore Teen, 17, to be charged with allegedly trespassing on MRT tracks Singapore Granddaughter of Hin Leong founder O.K. Lim fails to keep 3 insurance policies from creditors' reach Singapore Man on trial for raping drunken woman after offering to drive her and her friend home Micron is expanding its existing HBM output in Taiwan, but that capacity is likely to be used up quite quickly, so it will need more facilities to meet the expected demand in the coming years. 'We are rapidly going to run out of space in our facility in Taiwan. So, the Singapore facility will be very important to continue our HBM growth,' said Mr Sadana. 'We are super excited about the AI opportunity, and Singapore will certainly have a strong role to play in a lot of the AI-based innovation that we're doing.' Micron has also announced plans to start producing HBM chips in the United States; however, the Singapore plant will be up and running by the time production there kicks off. The firm – the top memory-chip maker in the US – unveiled a 'strategic reorganisation' of its business units in April designed to capitalise on the growth driven by AI, from data centres to devices such as computers and mobile phones. The reorganisation will make the company structure more market-focused rather than product-focused. The new four business units will include a cloud memory business unit focused on large hyperscale cloud customers and HBMs for data centre customers. There will be a separate mobile and client business unit, and one for automotive, industrial and consumer segments. 'This new structure will increase our resources towards data centres and allow us to have the end-to-end capability to serve AI in all segments,' said Mr Sadana. He said Singapore will continue to be the company's main production base of Nand flash memory chips used in solid-state drives, USB drives and mobile phones. Nand constituted 22 per cent of Micron's total revenue of US$9.3 billion in the third quarter of 2025, with turnover from data centres more than doubling year on year to hit a quarterly record. Mr Sadana said revenue from Singapore would keep increasing, especially when HBM output starts, noting: 'That's going to be a very big positive for us to be able to leverage Singapore for HBM sales that are, you know, very high-value sales that are growing rapidly.'
