Stanford and Swiss institutes unite on open AI models

Stanford University, ETH Zurich, and EPFL have launched a transatlantic partnership to develop open-source AI models prioritising societal values over commercial interests.

The partnership was formalised through a memorandum of understanding signed during the World Economic Forum meeting in Davos.

The agreement establishes long-term cooperation in AI research, education, and innovation, with a focus on large-scale multimodal models. The initiative aims to strengthen academia’s influence over global AI by promoting transparency, accountability, and inclusive access.

Joint projects will develop open datasets, evaluation benchmarks, and responsible deployment frameworks, alongside researcher exchanges and workshops. The effort aims to embed human-centred principles into technical progress while supporting interdisciplinary discovery.

Academic leaders said the alliance reinforces open science and cultural diversity amid growing corporate influence over foundation models. The collaboration positions universities as central drivers of ethical, trustworthy, and socially grounded AI development.

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Education for Countries programme signals OpenAI push into public education policy

OpenAI has launched the Education for Countries programme, a new global initiative designed to support governments in modernising education systems and preparing workforces for an AI-driven economy.

The programme responds to a widening gap between rapid advances in AI capabilities and people’s ability to use them effectively in everyday learning and work.

Education systems are positioned at the centre of closing that gap, as research suggests a significant share of core workplace skills will change by the end of the decade.

By integrating AI tools, training and research into schools and universities, national education frameworks can evolve alongside technological change and better equip students for future labour markets.

The programme combines access to tools such as ChatGPT Edu and advanced language models with large-scale research on learning outcomes, tailored national training schemes and internationally recognised certifications.

A global network of governments, universities and education leaders will also share best practices and shape responsible approaches to AI use in classrooms.

Initial partners include Estonia, Greece, Italy, Jordan, Kazakhstan, Slovakia, Trinidad and Tobago and the United Arab Emirates. Early national rollouts, particularly in Estonia, already involve tens of thousands of students and educators, with further countries expected to join later in 2026.

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TikTok restructures operations for US market

TikTok has finalised a deal allowing the app to continue operating in America by separating its US business from its global operations. The agreement follows years of political pressure in the US over national security concerns.

Under the arrangement, a new entity will manage TikTok’s US operations, with user data and algorithms handled inside the US. The recommendation algorithm has been licensed and will now be trained only on US user data to meet American regulatory requirements.

Ownership of TikTok’s US business is shared among American and international investors, while China-based ByteDance retains a minority stake. Oracle will oversee data security and cloud infrastructure for users in the US.

Analysts say the changes could alter how the app functions for the roughly 200 million users in the US. Questions remain over whether a US-trained algorithm will perform as effectively as the global version.

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EU cyber rules target global tech dependence

The European Union has proposed new cybersecurity rules aimed at reducing reliance on high-risk technology suppliers, particularly from China. In the European Union, policymakers argue existing voluntary measures failed to curb dependence on vendors such as Huawei and ZTE.

The proposal would introduce binding obligations for telecom operators across the European Union to phase out Chinese equipment. At the same time, officials have warned that reliance on US cloud and satellite services also poses security risks for Europe.

Despite increased funding and expanded certification plans, divisions remain within the European Union. Countries including Germany and France support stricter sovereignty rules, while others favour continued partnerships with US technology firms.

Analysts say the lack of consensus in the European Union could weaken the impact of the reforms. Without clear enforcement and investment in European alternatives, Europe may struggle to reduce dependence on both China and the US.

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WEF paper warns of widening AI investment gap

Policy-makers are being urged to take a more targeted approach to ‘sovereign AI’ spending, as a new paper released alongside the World Economic Forum meeting in Davos argues that no country can realistically build every part of the AI stack alone. Instead, the authors recommend treating AI sovereignty as ‘strategic interdependence’, combining selective domestic investment with trusted partnerships and alliances.

The paper, co-authored by the World Economic Forum and Bain & Co, highlights how heavily the United States and China dominate the global AI landscape. It estimates that the two countries capture around 65% of worldwide investment across the AI value chain, reflecting a full-stack model, from chips and cloud infrastructure to applications, that most other economies cannot match at the same scale.

For smaller and mid-sized economies, that imbalance can translate into a competitive disadvantage, because AI infrastructure, such as data centres and computing capacity, is increasingly viewed as the backbone of national AI capability. Still, the report argues that faster-moving countries can carve out a niche by focusing on a few priority areas, pooling regional capacity, or securing access through partnerships rather than trying to replicate the US-China approach.

The message was echoed in Davos by Nvidia chief executive Jensen Huang, who said every country should treat AI as essential infrastructure, comparable to electricity grids and transport networks. He argued that building AI data centres could drive demand for well-paid skilled trades, from electricians and plumbers to network engineers, framing the boom as a major job creator rather than a trigger for widespread job losses.

At the same time, the paper warns that physical constraints could slow expansion, including the availability of land, energy and water, as well as shortages of highly skilled workers. It also notes that local regulation can delay projects, although some industry groups argue that regulatory and cost pressures may push countries to innovate sooner in efficiency and greener data-centre design.

In the UK, industry body UKAI says high energy prices, limited grid capacity, complex planning rules and public scrutiny already create the same hurdles many other countries may soon face. It argues these constraints are helping drive improvements in efficiency, system design and coordination, seen as building blocks for more sustainable AI infrastructure.

Diplo is live reporting on all sessions from the World Economic Forum 2026 in Davos.

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Tata’s $11 billion Innovation City plan gains global visibility at Davos

Tata Sons plans to invest $11 billion to build a large ‘Innovation City’ near the upcoming Navi Mumbai International Airport, according to Maharashtra Chief Minister Devendra Fadnavis, speaking at the World Economic Forum (WEF) in Davos. He said the project has drawn strong interest from international investors and will include major infrastructure upgrades alongside a data centre.

Fadnavis said the aim is to turn Mumbai and its wider region into a global, ‘plug-and-play’ innovation hub where companies can quickly set up and scale new technologies. He described the initiative as the first of its kind in India and said work is expected to begin within six to eight months.

The location next to the Adani Group–developed Navi Mumbai Airport is being positioned as an advantage, linking global connectivity with the high-tech industry. The project also reflects a broader global rush to expand data centres as companies roll out AI services, with firms such as Microsoft, Alphabet, and Amazon investing heavily in new capacity worldwide.

Maharashtra, which contributes more than 10 percent of India’s GDP and hosts the country’s financial capital, is also pushing a wider infrastructure drive, including a $30 billion plan to upgrade Mumbai. State leaders have framed these investments as part of an effort to boost growth and respond to economic pressures, including unemployment.

The Innovation City is expected to support India’s ambitions in AI and semiconductors, with national officials pointing to a public-private partnership approach rather than leaving development solely to big tech companies. Alongside this, the state is exploring energy innovation, including potential collaborations on small modular nuclear reactors, following recent legislative support for smaller-scale nuclear projects.

Taken together, the plan is being presented as a bid to attract global investment, accelerate high-tech development, and strengthen India’s role in emerging industrial and technology shifts centred on AI, advanced manufacturing, and digital infrastructure.

Diplo is live reporting on all sessions from the World Economic Forum 2026 in Davos.

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AI Act strengthens training rules despite 2025 Digital Omnibus reforms

The European AI Regulation reinforces training and awareness as core compliance requirements, even as the EU considers simplifications through the proposed Digital Omnibus. Regulation (EU) 2024/1689 sets a risk-based framework for AI systems under the AI Act.

AI literacy is promoted through a multi-level approach. The EU institutions focus on public awareness, national authorities support voluntary codes of conduct, and organisations are currently required under the AI Act to ensure adequate AI competence among staff and third parties involved in system use.

A proposed amendment to Article 4, submitted in November 2025 under the Digital Omnibus, would replace mandatory internal competence requirements with encouragement-based measures. The change seeks to reduce administrative burden without removing AI Act risk management duties.

Even if adopted, the amendment would not eliminate the practical need for AI training. Competence in AI systems remains essential for governance, transparency, monitoring, and incident handling, particularly for high-risk use cases regulated by the AI Act.

Companies are therefore expected to continue investing in tailored AI training across management, technical, legal, and operational roles. Embedding awareness and competence into risk management frameworks remains critical to compliance and risk mitigation.

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Humanoid robots and AI take centre stage as Musk joins Davos 2026

Elon Musk made his first appearance at the World Economic Forum in Davos despite years of public criticism towards the gathering, arguing that AI and robotics represent the only realistic route to global abundance.

Speaking alongside BlackRock chief executive Larry Fink, Musk framed robotics as a civilisational shift rather than a niche innovation, claiming widespread automation will raise living standards and reshape economic growth.

Musk predicted a future where robots outnumber humans, with humanoid systems embedded across industry, healthcare and domestic life.

He highlighted elder care as a key use case in ageing societies facing labour shortages, suggesting that robotics could compensate for demographic decline rather than relying solely on migration or extended working lives.

Tesla’s Optimus humanoid robots are already performing simple factory tasks, with more complex functions expected within a year.

Musk indicated public sales could begin by 2027 once reliability thresholds are met. He also argued autonomous driving is largely resolved, pointing to expanding robotaxi deployments in the US and imminent regulatory decisions in Europe and China.

The global market for humanoid robotics remains relatively small, but analysts expect rapid expansion as AI capabilities improve and costs fall.

Musk at Davos 2026 presented robotics as an engine for economic acceleration, suggesting ubiquitous automation could unlock productivity gains on a scale comparable to past industrial revolutions.

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OpenAI ads in ChatGPT signal a shift in conversational advertising

The AI firm, OpenAI, plans to introduce advertising within ChatGPT for logged-in adult users, marking a structural shift in how brands engage audiences through conversational interfaces.

Ads would be clearly labelled and positioned alongside responses, aiming to replace interruption-driven formats with context-aware brand suggestions delivered during moments of active user intent.

Industry executives describe conversational AI advertising as a shift from exposure to earned presence, in which brands must provide clarity or utility to justify inclusion.

Experts warn that trust remains fragile, as AI recommendations carry the weight of personal consultation, and undisclosed commercial influence could prompt rapid user disengagement instead of passive ad avoidance.

Regulators and marketers alike highlight risks linked to dark patterns, algorithmic framing and subtle manipulation within AI-mediated conversations.

As conversational systems begin to shape discovery and decision-making, media planning is expected to shift toward intent-led engagement, authority-building, and transparency, reshaping digital advertising economics beyond search rankings and impression-based buying.

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New AI method boosts reasoning without extra training

Researchers at the University of California, Riverside, have introduced a technique that improves AI reasoning without requiring additional training data. Called Test-Time Matching, the approach enhances AI performance by enabling dynamic model adaptation.

The method addresses a persistent weakness in multimodal AI systems, which often struggle to interpret unfamiliar combinations of images and text. Traditional evaluation metrics rely on isolated comparisons that can obscure deeper reasoning capabilities.

By replacing these with a group-based matching approach, the researchers uncovered hidden model potential and achieved markedly stronger results.

Test-Time Matching lets AI systems refine predictions through repeated self-correction. Tests on SigLIP-B16 showed substantial gains, with performance surpassing larger models, including GPT-4.1, on key reasoning benchmarks.

The findings suggest that smarter evaluation and adaptation strategies may unlock powerful reasoning abilities even in smaller models. Researchers say the approach could speed AI deployment across robotics, healthcare, and autonomous systems.

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