Author: Shabbir Chunawalla

The Indian IT industry stands at a critical inflection point. So far Indian IT industry has utilized its talent pool by putting them on client projects domestically and offshore. It is just trading services. There is a need to shift to a product and IP-centered model out of India. This has become all the more necessary after the US launching its StarGate programme and the debut of DeepSeek from China.

India should focus on innovation by concentrating on increase in R&D expenditure, say in LLMs and SLMs, quantum computing and cyber security. It should allocate a higher percentage of revenue to fundamental research. The investment of global technology leaders to R&D is 15-20 per cent of their revenue. There should be collaboration between academia, industry and government institutions. The core research in India will act as an enabler to develop indigenous AI solutions. At present it is 0.7 per cent of GDP falling far behind the global average of 3 per cent. IP processes should be streamlined to provide protection of innovations. India should build up investor confidence.

There is a missing link to support investors through all stages of capital support. The startups here are supported by angels, venture capitalists and private equity. They require capital returns in 3-5 years. The focus should be on product development which should be incentivized. There should be a talent pool well-versed in cutting-edge technologies — it requires streamlining educational curricula as well as training within the company and massive reskilling and upskilling programmes. We lack entrepreneurs who will focus on deep tech and product thinking. Cities in China and organizations such as Alibaba have invested wider and deeper in AI than we have done as a nation. However, it is never too late.

The transformation is not going to be linear, but requires a through change in organizational culture (OC).

By an executive order, the US President has established a Strategic Bitcoin Reserve (SBR) and a stockpile of other digital assets.

As we know, Bitcoin is the original cryptocurrency and its supply is limited. Thus, having its reserve is strategically advantageous.

The initial contribution of capital is derived from the forfeiture of assets by the US Department of Treasury since these were involved in criminal or civil proceedings. The other agencies too will transfer Bitcoin owned by them to SBR.

The order also creates a US Digital Asset Stockpile consisting of assets other than Bitcoin owned by the Department of Treasury and derived from criminal or civil asset forfeiture.

There is no clear policy right now how these assets are managed. There is lack of accountability. There is insufficient exploration of options to centralize, secure and maximize their value.

The US government, according to an estimate, owns 2 lac Bitcoins, though there is never a complete audit. The E.O. directs of full accounting of all digital asset holdings of the federal government.

There will not be any selling of Bitcoins deposited in this reserve. It will be maintained as a store of reserve assets. The Secretaries of Treasury and Commerce have been authorized to develop strategies for acquiring additional Bitcoin.

It is a strategic advantage for the US to create this Reserve since there is a fixed supply of 21 million coins. There should not be any premature sales.

The stockpile will have Ethereum, XRP, Solana and Cardano, apart from Bitcoins.

The US will not acquire additional assets for the Reserve beyond those derived from forfeitures.

The full accounting will be provided of all digital assets to the Secretory of Treasury and the Presidents Working Group on Digital Asset Market.

On one February, 2025 Sunday, President Trump announced the formation of a US Crypto Strategic Reserve. He will host the first-ever White House Conference on cryptocurrency. It has shaken up the worldwide crypto enthusiasts. He himself and his family holds substantial crypto assets.

India is cautious about promoting cryptocurrency. The RBI here feels crypto’s unchecked expansion could adversely affect monetary policy, create financial risks and bypass capital flow regulations. If practised excessively, there could be diversion of resources from the real economy –it results into economic instability.

Crypto advocates vouchsafe for its decentralization and financial freedom. The reality is different. Crypto investors fall prey to influencers and stack up high risk assets.

It is to be seen whether RBI mellows down its strict stance.

Crypto currency transfers are opaque. Though official channels could be used to buy cryptos with KYC back-up, what happens to the assets once these are stored in the wallet is dicey. Tracking these transactions is like looking for a needle in the haystack.

Cryptos affect geopolitics too. The developed countries use financial innovations as a tool for diplomacy. If India opts for such a model, it is opting for short-term speculation over long-term stability.

Cryptos thrive in a weak regulatory environment. It shifts to most lenient jurisdictions. These are high-risk traps. The US could trigger a wave of capital flight. Investors think they have entered a stable market. Crypto crashes leave investors in financial ruin.

India has built a robust finance eco-systems — UPI, Aadhar-enabled payments and the digital rupee. These should be expanded and strengthened. India should not encourage unregulated digital assets. It is not an issue of managing the risks today, but the issue is to have financial future against chaotic speculation.

No doubt, the RBI is doing a thankless job, but it is crucial. It has to protect us from financial shocks.

The White House can have a crypto party. We are better off while exercising sobriety.

Will AI affect my job? It is an issue that is echoed all over by the white-collar workers — in fact it is the fear of being obsolete (FDBO). The concern has some basis.

All knowledge workers will be affected. The omnibus term knowledge workers include administrative and managerial jobs, financial analysts, software developers, legal personnel and creative people. It is a massive upheaval and needs a back-up plan.

Knowledge workers constitute around 50 percent of the UK’s job market, and 70 jobs out of these 50 per cent could be affected or replaced by generative AI. Employees in the US making more than $2.5 lac a year constitute 50 per cent of the US consumption. You can imagine what happens when these high-net-worth individuals are affected.

Software engineering agent will be able to perform what a software engineer with several years of experience performs, that too without human supervision. Coding could be done by virtual co-workers. They could have problem-solving abilities of a mid-level engineer very soon.

AI agents can be deployed on a large scale. It means though there will be new jobs and augmentation of existing jobs on account of AI, it still would result into job losses. Already, there are signs of recession in MBA level jobs, stagnation in consultancy jobs, no jobs for the translators and lay-offs in the IT sector.

In finance, a prospectus before an IPO can be drafted by generative AI in minutes, which otherwise takes a six-member team two weeks to produce. Contract and temporary staff in banking could be curtailed while AI takes over their roles.

In the back-up plan, one must familiarize with AI tools to protect oneself. One must keep networking on LinkedIn in case one is not offered a lifeboat for another career. It is also necessary to be alive to entrepreneurial opportunities.

There is no guarantee that one will retain one’s job, but a back-up can keep FOBO at length.

In the US, there is a demand to set up Manhattan-style project to push the development of superhuman AI intelligence, also called AGI.

To counter this demand, three prominent AI scientists Eric Schmidt (former Google CEO), Dan Hendrycks Director, Centre for AI safety) and Alexander Wang (CEO of Scale AI) has written a paper titled Superintelligence Strategy. They have cautioned that exclusive control of superintelligent AI systems by the US may provoke retaliation from China in the form of a cyberattack. The response to Mahattan-style project could provoke hostile reactions.

The suggestion of Manhattan-style project assumes the setting up of AGI project on the lines of atomic bomb programme in the 1940s.

The joint paper challenges this suggestion and could provoke a pre-emptive strike from an adversary. Though comparing nuclear weapons and AI is extreme, world leaders consider AI to be a top military advantage.

Schmidt et al suggest that adversaries will not wait till AGI is weaponised. They can disable threatening AI projects by using Mutual Assured AI Malfunction (MAIM).

Instead, the US should develop methods that deter other countries from creating superintelligent AI.

Some doomers treat AI as catastrophic. They want to slow down its development. Some ostriches want to accelerate the development of AI. A third way is to prioritize the strategies. It is at times wiser to take a defensive approach.

AM Turing Award is the tech world’s equivalent of the Nobel prize. It has been awarded this year to two pioneers in the field of reinforcement (RL), Andrew Barto and Richard Sulton. Barto (76) and Sulton (67) did their research on RL since 1970s and paved the way of the past decades AI breaking thoughts.

They channelized the so-called hedonistic machines which could continuously adapt their behaviour in response to positive signals.

It is reinforcement learning (RL) that led a Google computer programme to beat the best human players of the game GO in 2016 and 2017. It is also a key technique to enhance the capability of ChatGPT, optimize the financial trading and helping a robotic hand solve a Rubik’s Cube.

Animal trainers mould the behaviour of dogs and horses. Similarly, RL too moulds the behaviors of machines. They develop AI through RL. This has been recognised formally by declaring a top award to RL scientists.

In February 2025, the UK and Apple tension reached its peak over encryption. The government wanted Apple to provide a backdoor to customer data. Apple rather than submitting to this demand removed end-to-end encryptions for all British customers.

As we know, end-to-end encryption makes data inaccessible. It can be accessed only by the holder of encryption keys — the i cloud customer. The government wanted to penetrate the security layer. Apple resisted the efforts of even the US government to break into the encrypted system.

The British government has got more than what it has demanded. However, along with government, the bad actors too will have easier access to personal data of the British citizens. The British users are the losers.

In the world, we observe a privacy paradox. Even those customers who care for data privacy, they do not act on this concern by activating privacy settings on products. We do not know how many Apple customers have turned on end-to-end encryption. If the number is low, it is an example of privacy paradox.

Instead, privacy has become a product differentiation strategy for Apple. The UK retreat may reveal whether privacy features are worth the regulatory battles, especially if the consumers do not care.

India is after developing indigenous LLMs. The critical issue is whether India has the computing infrastructure to support the AI workloads. Even training the LLMs require massive processing capabilities. Both the US and China have an edge here — they have an advanced supercomputing infrastructure.

India generates huge volume of data but it is unstructured and requires lot of cleaning before being used for training. There is a need for better industry-academic collaboration. There should be sustained investment.

India requires AI infrastructure including data centers with high performance computing (HPC), specialised GPU clusters and efficient cooling technologies. This will support large scale AI training and inferencing.

Data centers and cloud infrastructure should support storage and high performance computing.

As AI adoption expands, there will be greater need for AI-ready infrastructure. There should be service providers to take on the risks and invest in high-performance GPUs. These services should be available on a cloud model. It ensures scalability and operational efficiency.

Indian data centers are not optimised for AI workloads which require specialised hardware such as Nvidia A100 GPUs or TPUs.

AI hardware should be both compute-intensive and energy-intensive.

AI optimized hardware includes GPUs, FPGAs (field programable gate array) and other accelerators to speed up model training and inference. These data centers must be power efficient, should have cooling facilities and bandwidth. They should have robust framework to protect sensitive data and proprietary AI models. They should take cyber security measures.

India should provide education to prepare talent pool of people. Future ready data centers must integrate AI-specific accelerators. There should be adoption of renewable energy sources.

India has the potential to emerge as global AI powerhouse if there is investment in the right infrastructure, policy support and talent development.

Since the government here decided to develop Indian LLMs, they will focus on voice-based models, rather than the text-based models elsewhere. It will provide access to a wider audience in local languages. Global models do have voice-capability in their AI assistants. However, their models are optimized for English text and a handful of other languages.

Population here is more comfortable in speaking to the model than typing its prompt. The model will use voice-based internet. The services will be accessed through voice commands. The concept will be a game changer. Voice will become a significant enabler.

Our internet using population is 500 million. Still India has 900 million people who remain offline. Many of these are from agricultural community, and non-tech savvy individuals. Voice-based models will serve them better. They will cater to the country’s linguistic diversity.

Some international models support multiple languages. Still, they use limited Indian datasets while training them. Indian AI models will use Indian datasets in training and will take care of linguistic and cultural nuances.

India has received 67 proposals for developing AI models — 22 proposals for LLMs and 45 for SLMs. The committee is examining these proposals.

The Ministry of Information and Broadcasting has announced plans to roll out digital FM radio broadcasting in 13 major cities. This is both a challenge and an opportunity in audio space.

Traditional FM radio has a massive listener base. Digital radio has the potential to expand the reach significantly. The listenership could be doubled or tripled.

The major obstacle is the availability and affordability of digital receivers.

At present, the listenership base for FM stations is of around 200 million. Digital radio could be received through mobile handsets and digital transmission. The listenership base could rise to 400 million.

At present, radio operates under terrestrial music licenses. Whether digital transmission will attract additional fees is to be seen. Maybe, the present licenses will remain valid without any extra fee.

According to TAM, radio broadcasting heavily depends upon local advertising. In the last 15 years, the industry has barely expanded. The total size of the radio industry remains under Rs. 3000 crores. It is the smallest sector in M&E space. To make the industry grow, we should introduce major policy changes — lowering of license fees, opening up air waves for more competition and allowing news on radio.

There are four or five major networks. Smaller players struggle to survive. Local advertisers often delay payments creating cash flow issues.

For FM radio stations, events have become a key revenue stream. Events are a non-traditional revenue stream. Its share years have been 20 per cent. It is increasing to reach 28-30 per cent. It could reach to 50 per cent though digital initiatives, influencer marketing and IPs. The major focus is on community-led events e.g. Durga Puja, Premier League, Film Festival, South Side Story, Music Festivals.