Capacity development

Minister urges Indian start-ups to shift focus from ice cream to semiconductors

India’s Commerce Minister Piyush Goyal has sparked controversy by questioning whether Indian start-ups should focus on semiconductor chips instead of gluten-free ice creams and food delivery apps.

Speaking at a start-up conference, he compared India’s consumer internet boom unfavourably with China’s advances in robotics and AI, urging entrepreneurs to pursue more ambitious tech innovations instead of safe lifestyle products.

While acknowledging the position of India as the world’s third-largest start-up ecosystem, Goyal faced pushback from founders who argued consumer apps often evolve into tech pioneers.

Quick-commerce CEO Aadit Palicha noted that companies like Amazon began as consumer platforms before revolutionising cloud computing. However, investors admitted deep-tech struggles for funding, with most capital chasing quick-return ventures instead of long-term hardware or AI projects.

The debate highlights India’s innovation crossroads. Despite having 4,000 deep-tech start-ups, projected to reach 10,000 by 2030, they attracted just 5% of 2023 funding instead of China’s 35%.

Experts suggest the government could help by offering tax incentives instead of criticism, and building research bridges between academia and start-ups to compete globally in advanced technologies

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Trump moves to prop up struggling coal industry

President Trump is set to sign an executive order designating coal as a critical mineral instead of allowing its continued decline in the energy sector.

The order will force some coal-fired power plants slated for closure to remain operational, with the administration citing rising electricity demand from data centres instead of acknowledging coal’s dwindling competitiveness.

Currently, coal generates just 15% of US electricity instead of its 51% share in 2001, having been overtaken by cheaper natural gas and renewables.

Environmental experts warn coal remains the dirtiest energy source instead of cleaner alternatives, releasing harmful pollutants linked to health issues like heart disease and mercury poisoning. While the order may temporarily slow plant closures, analysts note it won’t reverse coal’s decline.

Solar and wind power now undercut operating costs at nearly all US coal plants instead of being more expensive, as was once the case.

The move could have more impact in steelmaking, where coal is still used instead of newer green steel techniques in most production. However, for power generation, renewables can be deployed faster than new coal plants instead of struggling to meet demand.

The order appears to prioritise political symbolism instead of addressing energy market realities, as even existing coal plants struggle to compete with increasingly affordable clean energy alternatives.

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New AI firm Deep Cogito launches versatile open models

A new San Francisco-based startup, Deep Cogito, has unveiled its first family of AI models, Cogito 1, which can switch between fast-response and deep-reasoning modes instead of being limited to just one approach.

These hybrid models combine the efficiency of standard AI with the step-by-step problem-solving abilities seen in advanced systems like OpenAI’s o1. While reasoning models excel in fields like maths and physics, they often require more computing power, a trade-off Deep Cogito aims to balance.

The Cogito 1 series, built on Meta’s Llama and Alibaba’s Qwen models instead of starting from scratch, ranges from 3 billion to 70 billion parameters, with larger versions planned.

Early tests suggest the top-tier Cogito 70B outperforms rivals like DeepSeek’s reasoning model and Meta’s Llama 4 Scout in some tasks. The models are available for download or through cloud APIs, offering flexibility for developers.

Founded in June 2024 by ex-Google DeepMind product manager Dhruv Malhotra and former Google engineer Drishan Arora, Deep Cogito is backed by investors like South Park Commons.

The company’s ambitious goal is to develop ‘general superintelligence,’ AI that surpasses human capabilities, rather than merely matching them. For now, the team says they’ve only scratched the surface of their scaling potential.

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Bank appoints head of AI enablement

Standard Chartered has appointed David Hardoon as its global head of AI enablement, further embedding AI across its operations.

Based in Singapore, he will report to group chief data officer Mohammed Rahim.

Hardoon will lead AI governance and identify areas where AI can enhance productivity, efficiency, and client experiences. His appointment follows the bank’s recent rollout of a generative AI tool to over 70,000 employees across 41 markets.

The bank has been steadily introducing AI-driven tools, including a smart video column to provide insights for clients in Asia. It plans further expansion of its internal AI systems across additional regions.

With more than 20 years of experience in data and AI, including with Singapore’s central bank, Hardoon is expected to guide the responsible and strategic use of AI technologies across Standard Chartered’s global footprint.

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OpenAI negotiates $500m deal for AI startup

OpenAI is reportedly in talks to acquire io Products, an AI hardware startup co-founded by former Apple design chief Jony Ive and OpenAI CEO Sam Altman, in a deal that could exceed $500 million.

Instead of focusing solely on software like ChatGPT and API tools, OpenAI appears to be eyeing consumer devices as a way to diversify its revenue.

io Products is said to be working on AI-powered consumer tech, including a screenless smartphone and smart home gadgets.

The company’s team includes several former Apple designers, such as Tang Tan and Evans Hankey. Instead of traditional screens, these new devices are expected to explore more ambient and context-aware ways of interaction.

Jony Ive, best known for his role in designing iconic Apple products like the iPhone and iMac, left Apple in 2019 to launch his design consultancy, LoveFrom.

His collaboration with Altman on io Products was publicly confirmed last year and has already drawn interest from high-profile backers, including Laurene Powell Jobs. Funding for the startup was projected to reach $1 billion by the end of 2024.

The move echoes Altman’s previous investments in AI hardware, such as Humane Inc., a wearable tech startup that also focused on screenless interaction. Instead of scaling that venture, however, HP acquired some of Humane’s assets for $166 million earlier this year.

OpenAI’s potential acquisition of io Products could mark a significant shift toward physical consumer products in the AI space.

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Anthropic grows its presence in Europe

Anthropic is expanding its operations across Europe, with plans to add over 100 new roles in sales, engineering, research, and business operations. Most of these positions will be based in Dublin and London.

The company has also appointed Guillaume Princen, a former Stripe executive, as its head for Europe, the Middle East, and Africa. This move signals Anthropic’s ambition to strengthen its global presence, particularly in Europe where the demand for enterprise-ready AI tools is rising.

The company’s hiring strategy also reflects a wider trend within the AI industry, with firms like Anthropic competing for global market share after securing significant funding.

The recent $3.5 billion funding round bolsters Anthropic’s position as it seeks to lead the AI race across multiple regions, including the Americas, Europe, and Asia.

Instead of focusing solely on the US, Anthropic’s European push is designed to comply with local AI governance and regulatory standards, which are increasingly important to businesses operating in the region.

Anthropic’s expansion comes at a time when AI firms are facing growing competition from companies like Cohere, which has been positioning itself as a European-compliant alternative.

As the EU continues to shape global AI regulations, Anthropic’s focus on safety and localisation could position it favourably in these highly regulated markets. Analysts suggest that while the US may remain a less regulated environment for AI, the EU is likely to lead global AI policy development in the near future.

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Meta faces backlash over Llama 4 release

Over the weekend, Meta unveiled two new Llama 4 models—Scout, a smaller version, and Maverick, a mid-sized variant it claims outperforms OpenAI’s GPT-4o and Google’s Gemini 2.0 Flash across multiple benchmarks.

Maverick quickly climbed to second place on LMArena, an AI benchmarking platform where human evaluators compare and vote on model outputs. Meta proudly pointed to Maverick’s ELO score of 1417, placing it just beneath Gemini 2.5 Pro, instead of trailing behind the usual leaders.

However, AI researchers noticed a critical detail buried in Meta’s documentation: the version of Maverick that ranked so highly wasn’t the one released to the public. Instead of using the standard model, Meta had submitted an ‘experimental’ version specifically optimised for conversations.

LMArena later criticised this move, saying Meta failed to clearly indicate the model was customised, prompting the platform to update its policies to ensure future evaluations remain fair and reproducible.

Meta’s spokesperson acknowledged the use of experimental variants, insisting the company frequently tests different configurations.

While this wasn’t a violation of LMArena’s existing rules, the episode raised concerns about the credibility of benchmark rankings when companies submit fine-tuned models instead of the ones accessible to the wider community.

Independent AI researcher Simon Willison expressed frustration, saying the impressive ranking lost all meaning once it became clear the public couldn’t even use the same version.

The controversy unfolded against a backdrop of mounting competition in open-weight AI, with Meta under pressure following high-profile releases like China’s DeepSeek model.

Instead of offering a smooth rollout, Meta released Llama 4 on a Saturday—an unusual move—which CEO Mark Zuckerberg explained simply as ‘that’s when it was ready.’ But for many in the AI space, the launch has only deepened confusion around what these models can genuinely deliver.

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Scientists achieve breakthrough in quantum computing stability

A new study by researchers from the University of Oxford, Delft University of Technology, Eindhoven University of Technology, and Quantum Machines has made a major step forward in quantum computing.

The team has found a way to make Majorana zero modes (MZMs)—special particles crucial for quantum computers—far more stable, bringing us closer to building error-free, scalable machines.

Quantum computers are incredibly powerful but face a key challenge: their basic units, qubits, are highly fragile and easily disrupted by environmental noise.

MZMs have long been seen as a potential solution because they are predicted to resist such disturbances, but stabilising them for practical use has been difficult until now.

The researchers created a structure called a three-site Kitaev chain, which is a simplified version of a topological superconductor.

By using quantum dots to trap electrons and connecting them with superconducting wires, they created a stable ‘sweet spot’ where MZMs could be farther apart, reducing interference and enhancing their stability.

Lead author Dr. Greg Mazur believes this breakthrough shows that it is possible to keep MZMs stable as quantum systems grow. With further research, the team aims to build longer chains to improve stability even more, potentially opening the door to reliable, next-generation quantum materials and devices.

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Microsoft rethinks AI data centre strategy amid market shifts

Microsoft has reportedly scaled back or delayed several major data centre projects, just three months after announcing plans to invest $80 billion in AI infrastructure through the current fiscal year.

According to Bloomberg, the company has paused developments in multiple locations, including Australia, Indonesia, the United Kingdom, and US states such as Illinois, North Dakota, and Wisconsin.

Instead of denying the report, Microsoft confirmed adjustments to its plans, citing the need for long-term flexibility. A spokesperson said the company continuously reviews future infrastructure needs to ensure alignment with growing AI demand, adding that the changes reflect Microsoft’s adaptable strategy.

The halted projects include negotiations for high-performance AI chip facilities in the UK and a site near Chicago, along with construction delays in Jakarta and Wisconsin.

These moves come amid growing scrutiny over whether the AI sector is entering a bubble, especially as emerging models challenge the assumption that vast computing power is always necessary for innovation.

Instead of sticking to high-cost development, Microsoft may be responding to a new trend: efficient, lower-cost AI models from Chinese firms that rival those of Western tech giants.

With AI development costs dropping and access expanding, Microsoft’s strategic pause could reflect a shift towards a more sustainable and agile future in AI infrastructure.

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India among few developing nations with strong AI investment

India and China were the only developing nations to attract notable private investment in AI in 2023, according to the UN’s Technology and Innovation Report 2025. Instead of the US simply leading the field, it dominated with $67 billion in AI investment, accounting for 70 per cent of the global total.

China followed with $7.8 billion, while India ranked tenth worldwide with $1.4 billion. Instead of being evenly distributed, access to AI infrastructure and research remains heavily concentrated in a handful of countries, mainly the US and China.

India’s rise in the AI space stems from policy-driven innovation and education rather than organic growth alone. It climbed to 36th place out of 170 on the UNCTAD Frontier Technologies Readiness Index in 2024, improving from 48th in 2022.

Instead of only focusing on economic size, the index measures readiness through ICT availability, skills, R&D, industrial capacity, and financing. India performed well in R&D and industrial capacity but fell behind in ICT access and skill development.

India has supported its AI ecosystem through collaboration between the government, academia, and the private sector. The country hosts a large developer base, around 13 million, and contributes actively to generative AI projects on platforms like GitHub.

Programmes such as the India AI Mission aim to boost AI education and innovation in smaller cities, instead of keeping progress limited to major urban centres. Institutes like IIT Hyderabad and IIT Kharagpur were named among the country’s key centres of AI excellence.

Still, India faces challenges in expanding its AI capabilities across all sectors. Instead of allowing AI to widen inequalities, the report urges investment in workforce reskilling and inclusion. While AI can boost productivity, it may also displace jobs unless paired with supportive policies.

The technology, if harnessed wisely, could create new industries and strengthen employment rather than replace it.

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