Artificial intelligence

AI to transform India’s $400 billion IT ambition by 2030

India’s IT sector could reach $400 billion by 2030, Prime Minister Narendra Modi said in an interview with ANI, highlighting AI as a key growth driver. Services exports remain central to India’s economic expansion, with AI expected to reshape outsourcing and domain-specific automation.

Modi argued that AI is not replacing the IT industry but transforming it. General-purpose AI tools are becoming widespread, while enterprise-grade adoption remains concentrated in specific sectors where established IT firms continue solving complex business challenges.

Government policy is anchored in the IndiaAI Mission, which aims to expand access to computing infrastructure and strengthen domestic innovation. Modi said GPU targets have already been exceeded, with further investment planned to ensure affordable access for startups and enterprises.

Four Centres of Excellence have been established in healthcare, agriculture, education and sustainable cities, alongside five National Centres of Excellence for Skilling. Authorities aim to equip the workforce with industry-relevant AI expertise to support long-term competitiveness.

Strategic ambition extends beyond service delivery toward building AI products and platforms for domestic and global markets. Policymakers in India position AI as a catalyst for higher productivity, stronger digital infrastructure, and broader economic resilience.

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India to host first global AI summit in the Global South

India will host the AI Impact Summit 2026 on 19–20 February at Bharat Mandapam in New Delhi, marking the first global AI summit to be held in the Global South. Announced by Prime Minister Narendra Modi, the event is positioned as a major international forum aimed at advancing inclusive and action-oriented AI cooperation.

Organised by the Ministry of Electronics and Information Technology, the summit seeks to build on previous global AI gatherings while shifting the focus from high-level political statements to measurable outcomes.

Officials say the objective is to ensure that AI supports social development, sustainable growth and broader access to technological opportunities, particularly for developing nations.

The summit will be guided by three core principles known as the ‘Three Sutras’, namely People, Planet and Progress, and structured around seven thematic areas including human capital, inclusion, trusted AI, scientific collaboration and democratising AI resources.

These domains are intended to translate broad ambitions into concrete areas of multilateral action.
A series of pre-summit initiatives, including global challenges focused on inclusive AI, women-led innovation and youth participation, will take place in the lead-up to the event.

Organisers have also issued a global call for proposals, inviting institutions to host in-person sessions aligned with the summit’s themes, reinforcing India’s effort to shape a broader international conversation on AI governance and impact.

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DeepMind chief outlines limits of current AGI systems

Artificial general intelligence remains a future ambition rather than a present reality, according to Google DeepMind chief executive Demis Hassabis. Speaking at an AI summit in New Delhi, he said current systems still fall short of matching human-level intelligence in several vital areas.

Hassabis identified three key limitations. Existing AI models lack continual learning, meaning they cannot update their knowledge dynamically once deployed. Instead, they rely on static training completed before release, preventing them from adapting to new contexts or personalising responses over time.

Long-term planning is another weakness. While advanced models can handle short-term reasoning tasks, they struggle to plan strategically over extended periods, as humans do.

Consistency also remains an issue, as systems may perform exceptionally well in complex domains but make unexpected errors in simpler tasks.

Despite these shortcomings, Hassabis has previously suggested that genuine AGI could emerge within the next five to ten years. For now, however, he maintains that present systems have not yet reached that threshold.

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Mistral AI expands European footprint with acquisition of Koyeb

Mistral AI has strengthened its position in Europe’s AI sector through the acquisition of Koyeb. The deal forms part of its strategy to build end-to-end capacity for deploying advanced AI systems across European infrastructure.

The company has been expanding beyond model development into large-scale computing. It is currently building new data centre facilities, including a primary site in France and a €1.2 billion facility in Sweden, both aimed at supporting high-performance AI workloads.

The acquisition follows a period of rapid growth for Mistral AI, which reached a valuation of €11.7 billion after investment from ASML. French public support has also played a role in accelerating its commercial and research progress.

Mistral AI now positions itself as a potential European technology champion, seeking to combine model development, compute infrastructure and deployment tools into a fully integrated AI ecosystem.

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WordPress.com integrates AI assistant into its editing workflow

Major updates to AI tooling are reshaping website creation as WordPress.com brings an integrated assistant directly into its editor.

The new system works within each site rather than relying on external chat windows, allowing users to adjust layouts, create content, and modify designs in real time. The tool is available to customers on Business and Commerce plans, although activation requires a manual opt-in.

The assistant appears across several core areas of the platform. Inside the editor, it can refine writing, modify styles, translate text and generate new sections with simple instructions.

In the Media Library, you can create new images or apply targeted edits through the platform’s in-house Nano Banana models, eliminating the need for separate subscriptions. Block notes provide an additional way to request suggestions, checks, or link-based context directly within each page.

The updates aim to make site building faster and more efficient by keeping all AI interactions within the existing workflow. Users who prefer a manual experience can ignore the feature entirely, since the assistant remains inactive unless deliberately enabled.

WordPress.com also notes that the system works best with block themes, although image tools are still available for classic themes.

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Rising DRAM prices push memory to the centre of AI strategy

The cost of running AI systems is shifting towards memory rather than compute, as the price of DRAM has risen sharply over the past year. Efficient memory orchestration is now becoming a critical factor in keeping inference costs under control, particularly for large-scale deployments.

Analysts such as Doug O’Laughlin and Val Bercovici of Weka note that prompt caching is turning into a complex field.

Anthropic has expanded its caching guidance for Claude, with detailed tiers that determine how long data remains hot and how much can be saved through careful planning. The structure enables significant efficiency gains, though each additional token can displace previously cached content.

The growing complexity reflects a broader shift in AI architecture. Memory is being treated as a valuable and scarce resource, with optimisation required at multiple layers of the stack.

Startups such as Tensormesh are already working on cache optimisation tools, while hyperscalers are examining how best to balance DRAM and high-bandwidth memory across their data centres.

Better orchestration should reduce the number of tokens required for queries, and models are becoming more efficient at processing those tokens. As costs fall, applications that are currently uneconomical may become commercially viable.

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China boosts AI leadership with major model launches ahead of Lunar New Year

Leading Chinese AI developers have unveiled a series of advanced models ahead of the Lunar New Year, strengthening the country’s position in the global AI sector.

Major firms such as Alibaba, ByteDance, and Zhipu AI introduced new systems designed to support more sophisticated agents, faster workflows and broader multimedia understanding.

Industry observers also expect an imminent release from DeepSeek, whose previous model disrupted global markets last year.

Alibaba’s Qwen 3.5 model provides improved multilingual support across text, images and video while enabling rapid AI agent deployment instead of slower generation pipelines.

ByteDance followed up with updates to its Doubao chatbot and the second version of its image-to-video tool, SeeDance, which has drawn copyright concerns from the Motion Picture Association due to the ease with which users can recreate protected material.

Zhipu AI expanded the landscape further with GLM-5, an open-source model built for long-context reasoning, coding tasks, and multi-step planning. The company highlighted the model’s reliance on Huawei hardware as part of China’s efforts to strengthen domestic semiconductor resilience.

Meanwhile, excitement continues to build for DeepSeek’s fourth-generation system, expected to follow the widespread adoption and market turbulence associated with its V3 model.

Authorities across parts of Europe have restricted the use of DeepSeek models in public institutions because of data security and cybersecurity concerns.

Even so, the rapid pace of development in China suggests intensifying competition in the design of agent-focused systems capable of managing complex digital tasks without constant human oversight.

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Report warns of widening 5G capability gap

A new study by network analytics firm Ookla finds that while global 5G coverage gaps are narrowing, a deeper divide is emerging in network capabilities, with Europe falling behind. The report argues that the real competition is no longer about basic rollout, but about how effectively countries deploy advanced standalone (SA) 5G networks to support innovation, industry, and high-performance services.

According to the findings, North America and leading Asian markets have moved more decisively toward full standalone 5G architectures, achieving faster speeds and improved responsiveness. Gulf Cooperation Council countries have also advanced rapidly, with the region described as a 5G SA performance leader in 2025, delivering median download speeds reportedly more than five times higher than those in Europe.

Europe, by contrast, is characterised as lagging due to slow commercialisation, fragmented device ecosystems, and uneven tariff structures. While some countries, such as Spain, are cited as positive examples, the broader region risks losing ground as others accelerate deployment of 5G Advanced technologies, including enhanced spectrum use and more sophisticated network optimisation tools.

The report highlights national policy frameworks as a decisive factor in 5G competitiveness. Spectrum allocation strategies, infrastructure investment rules, and regulatory innovation are seen as equally important as technical upgrades. The findings come as the European Union advances its proposed Digital Networks Act, which has drawn mixed reactions from industry stakeholders concerned about investment conditions.

Beyond deployment, Ookla stresses that simply launching standalone 5G does not guarantee strong performance. Advanced optimisation strategies, such as cloud-native network design, deeper virtualisation, and improved spectrum efficiency, are key to unlocking the technology’s full potential. Enterprise adoption, initially slow under earlier non-standalone models, is now showing signs of growth, particularly in markets offering network slicing services.

The study concludes that decisions made in the next two years will be critical for long-term digital competitiveness. As 5G increasingly intersects with national AI strategies, industrial policy, and digital sovereignty agendas, countries that treat standalone networks as a strategic priority may gain a structural advantage, while others risk seeing the gap widen further as the transition toward 6G approaches.

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Meta explores AI system for digital afterlife

Meta has been granted a patent describing an AI system that could simulate a person’s social media activity, even after their death. The patent, originally filed in 2023 and approved in late December, outlines how AI could replicate a user’s online presence by drawing on their past posts, messages and interactions.

According to the filing, a large language model could analyse a person’s digital history, including comments, chats, voice messages and reactions, to generate new content that mirrors their tone and behaviour. The system could respond to other users, publish updates and continue conversations in a way that resembles the original account holder.

The patent suggests the technology could be used when someone is temporarily absent from a platform, but it also explicitly addresses the possibility of continuing activity after a user’s death. It notes that such a scenario would carry more permanent implications, as the person would not be able to return and reclaim control of the account.

More advanced versions of the concept could potentially simulate voice or even video interactions, effectively creating a digital persona capable of engaging with others in real time. The idea aligns with previous comments by Meta CEO Mark Zuckerberg, who has said AI could one day help people interact with digital representations of loved ones, provided consent mechanisms are in place.

Meta has stressed that the patent does not signal an imminent product launch, describing it as a protective filing for a concept that may never be developed. Still, similar services offered by startups have already sparked ethical debate, raising questions about digital identity, consent and the emotional impact of recreating the online presence of someone who has died.

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AI cheating allegation sparks discrimination lawsuit

A University of Michigan student has filed a federal lawsuit accusing the university of disability discrimination after professors allegedly claimed she used AI to write her essays. The student, identified in court documents as ‘Jane Doe,’ denies using AI and argues that symptoms linked to her medical conditions were wrongly interpreted as signs of cheating.

According to the complaint, Doe has obsessive-compulsive disorder and generalised anxiety disorder. Her lawyers argue that traits associated with those conditions, including a formal tone, structured writing, and consistent style, were cited by instructors as evidence that her work was AI-generated. They say she provided proof and medical documentation supporting her case but was still subjected to disciplinary action and prevented from graduating.

The lawsuit alleges that the university failed to provide appropriate disability-related accommodations during the academic integrity process. It also claims that the same professor who raised the concerns remained responsible for grading and overseeing remedial work, despite what the complaint describes as subjective judgments and questionable AI-detection methods.

The case highlights broader tensions on campuses as educators grapple with the rapid rise of generative AI tools. Professors across the United States report growing difficulty distinguishing between student work and machine-generated text, while students have increasingly challenged accusations they say rely on unreliable detection software.

Similar legal disputes have emerged elsewhere, with students and families filing lawsuits after being accused of submitting AI-written assignments. Research has suggested that some AI-detection systems can produce inaccurate results, raising concerns about fairness and due process in academic settings.

The University of Michigan has been asked to comment on the lawsuit, which is likely to intensify debate over how institutions balance academic integrity, disability rights, and the limits of emerging AI detection technologies.

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