Capacity development

Armenia plans major AI hub with NVIDIA and Firebird

Armenia has unveiled plans to develop a $500mn AI supercomputing hub in partnership with US tech leader NVIDIA, AI cloud firm Firebird, and local telecoms group Team.

Announced at the Viva Technology conference in Paris, the initiative marks the largest tech investment ever seen in the South Caucasus.

Due to open in 2026, the facility will house thousands of NVIDIA’s Blackwell GPUs and offer more than 100 megawatts of scalable computing power. Designed to advance AI research, training and entrepreneurship, the hub aims to position Armenia as a leading player in global AI development.

Prime Minister Nikol Pashinyan described the project as the ‘Stargate of Armenia’, underscoring its potential to transform the national tech sector.

Firebird CEO Razmig Hovaghimian said the hub would help develop local talent and attract international attention, while the Afeyan Foundation, led by Noubar Afeyan, is set to come on board as a founding investor.

Instead of limiting its role to funding, the Armenian government will also provide land, tax breaks and simplified regulation to support the project, strengthening its push toward a competitive digital economy.

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Amazon launches AU$ 20 bn investment in Australian solar-powered data centres

Amazon will invest AU$ 20 billion to expand its data centre infrastructure in Australia, using solar and wind power instead of traditional energy sources.

The plan includes power purchase agreements with three utility-scale solar plants developed by European Energy, one of which—Mokoan Solar Park in Victoria—is already operational. The other two projects, Winton North and Bullyard Solar Parks, are expected to lift total solar capacity to 333MW.

The investment supports Australia’s aim to enhance its cloud and AI capabilities. Amazon’s commitment includes purchasing over 170MW of power from these projects, contributing to both data centre growth and the country’s renewable energy transition.

According to the International Energy Agency, electricity demand from data centres is expected to more than double by 2030, driven by AI.

Amazon Web Services CEO Matt Garman said the move positions Australia to benefit from AI’s economic potential. The company, already active in solar projects across New South Wales, Queensland and Victoria, continues to prioritise renewables to decarbonise operations and meet surging energy needs.

Instead of pursuing growth through conventional means, Amazon’s focus on clean energy could set a precedent for other tech giants expanding in the region.

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OpenAI turns to Google Cloud in shift from solo AI race

OpenAI has entered into an unexpected partnership with Google, using Google Cloud to support its growing AI infrastructure needs.

Despite being fierce competitors in AI, the two tech giants recognise that long-term success may require collaboration instead of isolation.

As the demand for high-performance hardware soars, traditional rivals join forces to keep pace. OpenAI, previously backed heavily by Microsoft, now draws from Google’s vast cloud resources, hinting at a changing attitude in the AI race.

Rather than going it alone, firms may benefit more by leveraging each other’s strengths to accelerate development.

Google CEO Sundar Pichai, speaking on a podcast, suggested there is room for multiple winners in the AI sector. He even noted that a major competitor had ‘invited me to a dance’, underscoring a new phase of pragmatic cooperation.

While Google still faces threats to its search dominance from tools like ChatGPT, business incentives may override rivalry.

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Taiwan tightens rules on chip shipments to China

Taiwan has officially banned the export of chips and chiplets to China’s Huawei and SMIC, joining the US in tightening restrictions on advanced semiconductor transfers.

The decision follows reports that TSMC, the world’s largest contract chipmaker, was unknowingly misled into supplying chiplets used in Huawei’s Ascend 910B AI accelerator. The US Commerce Department had reportedly considered a fine of over $1 billion against TSMC for that incident.

Taiwan’s new rules aim to prevent further breaches by requiring export permits for any transactions with Huawei or SMIC.

The distinction between chips and chiplets is key to the case. Traditional chips are built as single-die monoliths using the same process node, while chiplets are modular and can combine various specialised components, such as CPU or AI cores.

Huawei allegedly used shell companies to acquire chiplets from TSMC, bypassing existing US restrictions. If TSMC had known the true customer, it likely would have withheld the order. Taiwan’s new export controls are designed to ensure stricter oversight of future transactions and prevent repeat deceptions.

The broader geopolitical stakes are clear. Taiwan views the transfer of advanced chips to China as a national security threat, given Beijing’s ambitions to reunify with Taiwan and the potential militarisation of high-end semiconductors.

With Huawei claiming its processors are nearly on par with Western chips—though analysts argue they lag two to three generations behind—the export ban could further isolate China’s chipmakers.

Speculation persists that Taiwan’s move was partly influenced by negotiations with the US to avoid the proposed fine on TSMC, bringing both countries into closer alignment on chip sanctions.

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Indonesia’s cyber strategy balances power and capacity

Indonesia has taken a major step in decentralising its cybersecurity efforts by launching eight regional Cyber Crime Directorates across provinces, including Jakarta, West Java, East Java, and Papua. That marks a significant shift from a centralised system to one that recognises the localised nature of cyber threats, from financial fraud and data breaches to online disinformation.

The move reflects a growing awareness that cybersecurity is no longer just a technical issue but a broader governance challenge involving law enforcement at multiple levels. The rationale behind the decentralisation is clear: bringing cyber governance closer to where threats emerge allows for quicker responses and better local engagement.

It aligns with global ideas of ‘multi-level security governance,’ where various authorities work together across layers. However, while the creation of these regional directorates in Indonesia signals progress, it also reveals deep structural limitations—many local units still lack trained personnel, sufficient technology, and flexible organisational systems needed to tackle sophisticated cybercrime.

Experts warn that these new directorates risk becoming symbolic rather than effective without serious investments in infrastructure, education, and staff development. Current bureaucratic rigidity, hierarchical communication, and limited agency coordination further hamper their potential.

In some provinces, such as Central Sulawesi and Papua, the initiative may also reflect broader state security goals, highlighting how cybersecurity policy often intersects with political and geographic sensitivities. For Indonesia to build a truly adaptive and resilient cyber governance framework, reforms must go beyond institutional expansion.

That includes fostering partnerships with academia and civil society, enabling regional units to respond dynamically to emerging threats, and ensuring that cyber capabilities are built on solid foundations rather than unevenly distributed resources. Otherwise, the decentralisation could reinforce old inefficiencies under a new name.

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Switzerland’s unique AI path: Blending innovation, governance, and local empowerment

In his recent blog post ‘Advancing Swiss AI Trinity: Zurich’s entrepreneurship, Geneva’s governance, and Communal subsidiarity,’ Jovan Kurbalija proposes a distinctive roadmap for Switzerland to navigate the rapidly evolving landscape of AI. Rather than mimicking the AI power plays of the United States or China, Kurbalija argues that Switzerland can lead by integrating three national strengths: Zurich’s thriving innovation ecosystem, Geneva’s global leadership in governance, and the country’s foundational principle of subsidiarity rooted in local decision-making.

Zurich, already a global tech hub, is positioned to drive cutting-edge development through its academic excellence and robust entrepreneurial culture. Institutions like ETH Zurich and the presence of major tech firms provide a fertile ground for collaborations that turn research into practical solutions.

With AI tools becoming increasingly accessible, Kurbalija emphasises that success now depends on how societies harness the interplay of human and machine intelligence—a field where Switzerland’s education and apprenticeship systems give it a competitive edge. Meanwhile, Geneva is called upon to spearhead balanced international governance and standard-setting for AI.

Kurbalija stresses that AI policy must go beyond abstract discussions and address real-world issues—health, education, the environment—by embedding AI tools in global institutions and negotiations. He notes that Geneva’s experience in multilateral diplomacy and technical standardisation offers a strong foundation for shaping ethical, inclusive AI frameworks.

The third pillar—subsidiarity—empowers Swiss cantons and communities to develop AI that reflects local values and needs. By supporting grassroots innovation through mini-grants, reimagining libraries as AI learning hubs, and embedding AI literacy from primary school to professional training, Switzerland can build an AI model that is democratic and inclusive.

Why does it matter?

Kurbalija’s call to action is clear: with its tools, talent, and traditions aligned, Switzerland must act now to chart a future where AI serves society, not the other way around.

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Google Gemini now summarizes PDFs with actionable prompts in Drive

Google is expanding Gemini’s capabilities by allowing the AI assistant to summarize PDF documents directly in Google Drive—and it’s doing more than just generating summaries.

Users will now see clickable suggestions like drafting proposals or creating interview questions based on resume content, making Gemini a more proactive productivity tool.

However, this update builds on earlier integrations of Gemini in Drive, which now surface pop-up summaries and action prompts when a PDF is opened.

Users with smart features and personalization turned on will notice a new preview window interface, eliminating the need to open a separate tab.

Gemini’s PDF summaries are now available in over 20 languages and will gradually roll out over the next two weeks.

The feature supports personal and business accounts, including Business Standard/Plus users, Enterprise tiers, Gemini Education, and Google AI Pro and Ultra plans.

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Nvidia’s Huang: ‘The new programming language is human’

Speaking at London Tech Week, Nvidia CEO Jensen Huang called AI ‘the great equaliser,’ explaining how AI has transformed who can access and control computing power.

In the past, computing was limited to a select few with technical skills in languages like C++ or Python. ‘We had to learn programming languages. We had to architect it. We had to design these computers that are very complicated,’ Huang said.

That’s no longer necessary, he explained. ‘Now, all of a sudden, there’s a new programming language. This new programming language is called ‘human’,’ Huang said, highlighting how AI now understands natural language commands. ‘Most people don’t know C++, very few people know Python, and everybody, as you know, knows human.’

He illustrated his point with an example: asking an AI to write a poem in the style of Shakespeare. The AI delivers, he said—and if you ask it to improve, it will reflect and try again, just like a human collaborator.

For Huang, this shift is not just technical but transformational. It makes the power of advanced computing accessible to billions, not just a trained few.

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Meta bets big on AI, partners with Scale AI in strategic move

Meta Platforms has made a major move in the AI space by investing $14.8 billion in Scale AI, acquiring a 49% stake and pushing the data-labelling startup’s valuation past $29 billion.

As part of the deal, Scale AI founder Alexandr Wang will join Meta’s leadership to head its new superintelligence unit, while continuing to serve on Scale AI’s board. The investment deepens Meta’s commercial ties with Scale and is seen as a strategic step to secure top-tier AI expertise.

Scale AI will use the funds to drive innovation and strengthen client partnerships, while also providing partial liquidity to shareholders and equity holders. Jason Droege, Scale’s Chief Strategy Officer and former Uber Eats executive, will serve as interim CEO.

‘This partnership is a testament to our team’s work and the scale of opportunity ahead,’ said Droege. Wang added, ‘Meta’s investment affirms the limitless path forward for AI and Scale’s role in bridging human values with transformative technologies.’

Scale will remain independent, continuing to support AI labs, corporations, and government agencies with data infrastructure as the race for AI dominance intensifies.

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Meta’s V-JEPA 2 teaches AI to think, plan, and act in 3D space

Meta has released V-JEPA 2, an open-source AI model designed to understand and predict real-world environments in 3D. Described as a ‘world model’, it enables machines to simulate physical spaces—offering a breakthrough for robotics, self-driving cars, and intelligent assistants.

Unlike traditional AI that relies on labelled data, V-JEPA 2 learns from unlabelled video clips, building an internal simulation of how the world works. However, now, AI can reason, plan, and act more like humans.

Based on Meta’s JEPA architecture and containing 1.2 billion parameters, the model improves significantly on action prediction and environmental modelling compared to its predecessor.

Meta says this approach mirrors how humans intuitively understand cause and effect—like predicting a ball’s motion or avoiding people in a crowd. V-JEPA 2 helps AI agents develop this same intuition, making them more adaptive in dynamic, unfamiliar situations.

Meta’s Chief AI Scientist Yann LeCun describes world models as ‘abstract digital twins of reality’—vital for machines to understand and predict what comes next. This effort aligns with Meta’s broader push into AI, including a planned $14 billion investment in Scale AI for data labelling.

V-JEPA 2 joins a growing wave of interest in world models. Google DeepMind is building its own called Genie, while AI researcher Fei-Fei Li recently raised $230 million for her startup World Labs, focused on similar goals.

Meta believes V-JEPA 2 brings us closer to machines that can learn, adapt, and operate in the physical world with far greater autonomy and intelligence.

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