Centre Considering Local Storage Of AI Models To Prevent Data Outflow

Centre Considering Local Storage Of AI Models To Prevent Data Outflow

SUMMARY

The Centre is reportedly considering local storage of AI models to minimise risks associated with them and prevent flow of sensitive data outside India

With the Centre reportedly planning to finalise the Digital Personal Data Protection (DPDP) Act rules by April, MeitY secretary S Krishnan said that once implemented it will play an effective role in preventing the personal data leaks

The MeitY secretary also highlighted the rise of cybersecurity incidents in India, signaling improved public awareness and enhanced surveillance capabilities

The Centre is reportedly considering local storage of AI models to minimise risks associated with them and prevent flow of sensitive data outside India.

This aligns with the government’s broader efforts to strengthen cybersecurity infrastructure and safeguard data of citizens.

With the Centre reportedly planning to finalise the Digital Personal Data Protection (DPDP) Act rules by April, Ministry of Electronics and Information Technology (MeitY) secretary S Krishnan said that once implemented it will play an effective role in preventing the personal data leaks.

Notably, the act empowers the government to restrict cross-border data transfers and mandates robust security measures for handling personal data.

As per news agency PTI, Krishnan also pointed out that the government is closely monitoring Chinese LLM models due to potential risks related to data misuse.

“The true problem lies when data gets shared on a portal or on a mobile app because then the data may go out of the country and may sort of feed the way that a particular model is trained and a lot of the data may go out. On the private side, if the model itself is hosted in India, then the risks of data going out are far more mitigated considerably,” he said.

The MeitY secretary also highlighted the rise of cybersecurity incidents in India, signaling improved public awareness and enhanced surveillance capabilities.

This comes a few days after Krishnan reiterated the need to develop more foundation models in India, focused on issues relevant to the country and languages spoken here.

It is pertinent to note that India’s focus on localising AI models and enforcing stringent data protection laws is intended towards establishing itself as a global leader in AI, but with national security. 

In line with this, India has also introduced initiatives like the IndiaAI Mission, aiming to foster AI development through public-private partnerships, GPU procurement and support for startups. 

Moreover, the data localisation under the DPDP Act also aligns with global trends where nations are imposing stricter controls over cross-border data flows.

Driven by this data localisation requirement, global AI companies like OpenAI, Microsoft, Google, and Amazon are either looking to set up or expand their local data storage in India. 

India’s homegrown AI industry has made significant progress in the past few years, led by the support from the government as well as investors. As a result, more than 200 GenAI startups have raised more than $1.2 Bn since 2020.

While the likes of SarvamAI and Krutrim are building Indic LLMs, others like ObserveAI are leveraging AI to offer customised offerings to businesses.

Besides, we are also witnessing across sectors AI usage to streamline user experience and operations, projecting the homegrown GenAI market to cross the $17 Bn mark by 2030.

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