V. Rajaraman
| Photo Credit: V. Rajaraman

Over the past year, a considerable amount of recognition for machine learning (ML) has gone to researchers working in or alongside large technology firms, even as recent advances in artificial intelligence (AI) have been financed and built on corporate infrastructure.

In 2024, the Nobel Foundation awarded the physics prize to John Hopfield and Geoffrey Hinton for contributions that enabled learning with artificial neural networks, and the chemistry prize to Demis Hassabis and John Jumper for protein structure prediction (alongside David Baker’s computational design). Mr. Hassabis and Mr. Jumper were employed at Google DeepMind at the time of the award; Mr. Hinton had spent a decade at Google before departing in 2023. These affiliations don’t erase the laureates’ academic histories but they do indicate where prize-level research is now being performed.

This change rests on material conditions as well as ideas. State-of-the-art models depend on large computing clusters, curated data, and engineering teams. Google’s programme to develop tensor-processing units (TPU) for its data centres shows how fixed capital can become a scientific input rather than only an information technology cost. Microsoft’s multiyear financing and Azure supercomputers for OpenAI reflect the same political economy from a different angle.

Case for public access

Any research with public provenance should return to the public domain. In this context, public money has supported early theoretical work, academic posts, fellowships, shared datasets, publishing infrastructure, and often the researchers themselves. In parallel, the points at which the value became excludable lay increasingly downstream: with respect to computing resources (shortened as compute), this includes rights to data and code, the ability to deploy models at scale, and decisions to release or withhold weights. This helps explain why recent Nobel laureates have been situated in corporate laboratories and why frontier systems are predominantly trained on private cloud systems.

In the 20th century, firms such as Bell Labs and IBM hosted prize-winning basic research. However, much of the knowledge then moved through reproducible publications and open benchmarks. Today, reproducing the work of Mr. Jumper, for example, can require large compute budgets and specialised operations expertise. As a result the concern isn’t only that corporations receive prizes but that the path from a public insight to a working system is infrastructure and contracts controlled by a few firms.

The involvement of public funds should thus create concrete obligations at points where technology becomes enclosed for private control. If an academic laboratory accepts a public grant, the deliverables should include the artefacts that make the work usable, including the training code, evaluation suites, and weights in the AI models to be released under open licences. If a public agency buys cloud credits or commissions model development, procurement should require that the benchmarks and improvements flow back to the commons rather than become locked into a vendor.

Remove bottlenecks

The argument isn’t that corporate laboratories can’t do fundamental science; they clearly can. The claim is that public policy should reduce the structural advantages of private control. Consider the release of Google DeepMind’s AlphaFold 2, which, together with its code and public access to predictions, allowed researchers beyond the originating lab to run the system on (reasonably) standard hardware, retrieve large numbers of precomputed structures, and integrate their results into routine workflows. All this work was supported by public institutions that were willing to host and maintain the resources.

Where the corporate stack is indispensable, such as when training frontier models (with billions or trillions of parameters), claims about ‘responsible release’ often ironically translate to a closed release. Instead, a more consistent position should be to link risk management to a structured model of openness — perhaps one that includes staged releases, access to weights, open penetration testing tools, and a clear separation between safety rationales and business models — rather than allow private entities to resort to blanket secrecy in the name of safety.

The same logic applies to compute: that is, if computing resources become a scientific bottleneck, they should be treated as a public utility. National and regional compute commons should allocate resources for free or at-cost to academic groups, nonprofits, and small firms, and qualify them on open deliverables and safety practices. The ultimate goal is to restore the ability of public institutions to reproduce, test, and extend leading ML work without having to seek corporate permission. Without such a commons, however, publicly funded ideas will continue to be turned into working systems on private clouds and returned to the public as expensive information products.

Indeed, while it’s tempting to treat the entities employing the laureates and funding pipelines as separate issues, one symbolic and the other structural, they’re connected by the computing resources. The fact that the Nobel laureates worked at Google DeepMind reflects where teams with ML scientists, domain experts, data, and compute now operate. Likewise, the fact that the most visible systems of the past two years were trained on Microsoft Azure under a financing agreement explains who could attempt such training. Both facts reflect underlying resource concentrations.

Beyond industry vs academia

Public agencies’ response should be direct — by, say, tying funding to openness in grants and procurement and requiring detailed funding disclosures and compute-cost accounting in research papers. Where full openness would create unacceptable risks, agencies can use equity or royalties to fund compute and data commons that support the wider ecosystem. For corporate laboratories, on the other hand, their credibility should rest on measurable contributions to the commons.

Journalists and the publics should also move beyond an ‘industry versus academia’ framing.

The relevant questions are who sets the research agenda, who controls infrastructure, who can reproduce results, and who benefits from deploying the resulting AI models. Interpreting the 2024 Nobel Prizes as industry victories alone would miss the point that the knowledge base is cumulative and relies on public inputs, while the capacity to operationalise that knowledge is clustered. Articulating this pattern allows us to recognise scientific merit while demanding reforms that ensure public inputs produce public returns — in code, data, weights, benchmarks, and access to compute.

To be sure, the central conclusion isn’t resentment about corporate salaries but responding to the fact that breakthroughs are increasingly occurring at the intersection of public knowledge and private infrastructure. The policy programme should be to reunite the layers where public and private enterprises diverge — artefacts, datasets, and compute — and to bake this expectation into contracts and norms that govern research.

In these conditions, future awards can be celebrated with corresponding public benefit because the outputs that make the science usable will be returned to the public.

Published – November 11, 2025 06:45 am IST

Electric cooking, or e-cooking, is the most affordable and sustainable cooking option for Indian households, according to a new report by the Institute for Energy Economics and Financial Analysis (IEEFA), a U.S.-based energy policy think tank.

The report, titled ‘India’s Clean Cooking Strategy: E-Cooking, the Next Frontier’, finds that e-cooking is 37% cheaper than non-subsidised liquefied petroleum gas (LPG), and 14% cheaper than piped natural gas (PNG), making it a compelling alternative in urban areas, where access to electricity is stable.  

“Electricity-based cooking means cost savings. Based on the analysis for FY2024-25, using PNG for cooking versus electricity-based devices can be 14% more expensive for households, while non-subsidised LPG can be 37% more expensive. Subsidising LPG for all consumers has made it only marginally more affordable than e-cooking. Only the heavily subsidised LPG pricing for beneficiaries of the Pradhan Mantri Ujjwala Yojana comes out cheaper than e-cooking,” Purva Jain, energy specialist at the IEEFA and the author of the report, said.

Despite near-universal electrification, the uptake of e-cooking remains sluggish. Ms. Jain attributes this to high upfront capital costs, limited device options, and low consumer awareness. “The initial cost of induction cooktops and compatible utensils can be a barrier. We need government support to reduce capital costs and build consumer confidence,” she said.

The report uses Delhi’s electricity tariffs for the financial year 2024-25 to calculate annual cooking costs, assuming a reasonably high usage slab. Ms. Jain explained that while the analysis is Delhi-specific, it can serve as a proxy for other States. “LPG prices are uniform across India, and PNG prices in Delhi are comparable to many geographical areas. Only a few gas agencies have lower prices than Delhi,” she said.

India’s LPG and liquified natural gas (LNG) import bills have increased by 50% over the past six years, reaching ₹2.2 lakh crore in FY2024-25. This accounts for nearly 3% of the country’s total import expenditure, and exposes it to global price volatility and geopolitical risks. While LPG and PNG are cleaner than traditional solid fuels, they remain carbon-intensive and contribute to rising residential emissions. Nearly 40% of Indian households still rely on firewood, dung, and other polluting fuels for cooking. 

Ms. Jain believes that shifting urban households to e-cooking could free up LPG and PNG resources for rural areas, where access to clean cooking options remains limited. “Shifting urban areas to e-cooking could be one solution to the problem of limited use of clean cooking fuels in rural areas. By reducing demand for LPG and PNG in urban areas, more of these limited resources could be redirected to rural areas,” she said.

Addressing concerns about grid load, the author noted that India is strengthening its national grid with various actions. Policy interventions, including time-of-day tariffs, and ensuring only energy-efficient devices are available in the market, can help manage peak demand.  

Cultural resistance to non-flame cooking is another challenge. Ms. Jain pointed to real-life case studies showing that chapattis can be cooked on induction cooktops with ease. “For households hesitant to give up flame-based cooking, fuel stacking is a practical solution. Start with boiling water or milk, cooking rice — simple steps on a single induction cooktop,” she added.  

On large-scale adoption of successful e-cooking demonstration, the report provides examples of institutional adoption, including Anganwadis supported by Energy Efficiency Services Limited under the National Efficient Cooking Programme. Kerala’s Angan-Jyoti scheme integrates e-cooking with solar power and energy-efficient cooling to promote grassroots sustainability.

While the report does not quantify lifecycle emissions, Ms. Jain noted that e-cooking aligns with India’s decarbonisation goals. “With the increasing greening of the electricity grid, relying on e-cooking as the fuel of the future is a good strategy. We should avoid locking expensive resources into fossil-based solutions like PNG,” she added.

Ms. Jain also acknowledged the need for financing options. There’s a brief mention of solutions to manage the relatively higher capital cost of procuring e-cooking devices. EMIs (equated monthly installment) and carbon credit programmes could be explored further, she said.  

As India continues its push toward clean energy, the authors of the report believe the time is ripe for a national roadmap. “The report is a small step in advocating the need for a detailed roadmap with timelines. We need to boost consumer and manufacturer confidence,” Ms. Jain said.    

E-cooking, Ms. Jain emphasised, is not just an alternative — it is a future-ready solution that offers affordability, safety, and sustainability. “It’s time we reimagine clean cooking in India. Electric cooking is the next frontier,” she said. 

Published – November 10, 2025 05:04 pm IST

Vaishnavi Srinivasagopalan, a skilled Indian IT professional who has worked in both India and the U.S., has been looking for work in China. Beijing’s new K-visa program targeting science and technology workers could turn that dream into a reality.

The K-visa rolled out by Beijing last month is part of China’s widening effort to catch up with the U.S. in the race for global talent and cutting edge technology. It coincides with uncertainties over the U.S.’s H-1B program under tightened immigrations policies implemented by President Donald Trump.

“(The) K-visa for China (is) an equivalent to the H-1B for the U.S.,” said Srinivasagopalan, who is intrigued by China’s working environment and culture after her father worked at a Chinese university a few years back. “It is a good option for people like me to work abroad.”

The K-visa supplements China’s existing visa schemes including the R-visa for foreign professionals, but with loosened requirements, such as not requiring an applicant to have a job offer before applying.

Stricter U.S. policies toward foreign students and scholars under Trump, including the raising of fees for the H-1B visa for foreign skilled workers to $100,000 for new applicants, are leading some non-American professionals and students to consider going elsewhere.

“Students studying in the U.S. hoped for an (H-1B) visa, but currently this is an issue,” said Bikash Kali Das, an Indian masters student of international relations at Sichuan University in China.

China is striking while the iron is hot.

The ruling Communist Party has made global leadership in advanced technologies a top priority, paying massive government subsidies to support research and development of areas such as artificial intelligence, semiconductors and robotics.

“Beijing perceives the tightening of immigration policies in the U.S. as an opportunity to position itself globally as welcoming foreign talent and investment more broadly,” said Barbara Kelemen, associate director and head of Asia at security intelligence firm Dragonfly.

Unemployment among Chinese graduates remains high, and competition is intense for jobs in scientific and technical fields. But there is a skills gap China’s leadership is eager to fill. For decades, China has been losing top talent to developed countries as many stayed and worked in the U.S. and Europe after they finished studies there.

The brain drain has not fully reversed.

Many Chinese parents still see Western education as advanced and are eager to send their children abroad, said Alfred Wu, an associate professor at the National University of Singapore.

Still, in recent years, a growing number of professionals including AI experts, scientists and engineers have moved to China from the U.S., including Chinese-Americans. Fei Su, a chip architect at Intel, and Ming Zhou, a leading engineer at U.S.-based software firm Altair, were among those who have taken teaching jobs in China this year.

Many skilled workers in India and Southeast Asia have already expressed interest about the K-visa, said Edward Hu, a Shanghai-based immigration director at the consultancy Newland Chase.

With the jobless rate for Chinese aged 16-24 excluding students at nearly 18%, the campaign to attract more foreign professionals is raising questions.

“The current job market is already under fierce competition,” said Zhou Xinying, a 24-year-old postgraduate student in behavioural science at eastern China’s Zhejiang University.

While foreign professionals could help “bring about new technologies” and different international perspectives, Zhou said, “some Chinese young job seekers may feel pressure due to the introduction of the K-visa policy.”

Kyle Huang, a 26-year-old software engineer based in the southern city of Guangzhou, said his peers in the science and technology fields fear the new visa scheme “might threaten local job opportunities”.

A recent commentary published by a state-backed news outlet, the Shanghai Observer, downplayed such concerns, saying that bringing in such foreign professionals will benefit the economy. As China advances in areas such as AI and cutting-edge semiconductors, there is a “gap and mismatch” between qualified jobseekers and the demand for skilled workers, it said.

“The more complex the global environment, the more China will open its arms,” it said.

“Beijing will need to emphasize how select foreign talent can create, not take, local jobs,” said Michael Feller, chief strategist at consultancy Geopolitical Strategy. “But even Washington has shown that this is politically a hard argument to make, despite decades of evidence.”

Recruitment and immigration specialists say foreign workers face various hurdles in China. One is the language barrier. The ruling Communist Party’s internet censorship, known as the “Great Firewall,” is another drawback.

A country of about 1.4 billion, China had only an estimated 711,000 foreign workers residing in the country as of 2023.

The U.S. still leads in research and has the advantage of using English widely. There’s also still a relatively clearer pathway to residency for many, said David Stepat, country director for Singapore at the consultancy Dezan Shira & Associates.

Nikhil Swaminathan, an Indian H1-B visa holder working for a U.S. non-profit organisation after finishing graduate school there, is interested in China’s K-visa but skeptical. “I would’ve considered it. China’s a great place to work in tech, if not for the difficult relationship between India and China,” he said.

Given a choice, many jobseekers still are likely to aim for jobs in leading global companies outside China.

“The U.S. is probably more at risk of losing would-be H-1B applicants to other Western economies, including the UK and European Union, than to China,” said Feller at Geopolitical Strategy.

“The U.S. may be sabotaging itself, but it’s doing so from a far more competitive position in terms of its attractiveness to talent,” Feller said. “China will need to do far more than offer convenient visa pathways to attract the best.”

Published – November 10, 2025 01:34 pm IST