Capacity development

Private AI Compute by Google blends cloud power with on-device privacy

Google introduced Private AI Compute, a cloud platform that combines the power of Gemini with on-device privacy. It delivers faster AI while ensuring that personal data remains private and inaccessible, even to Google. The system builds on Google’s privacy-enhancing innovations across AI experiences.

As AI becomes more anticipatory, Private AI Compute enables advanced reasoning that exceeds the limits of local devices. It runs on Google’s custom TPUs and Titanium Intelligence Enclaves, securely powering Gemini models in the cloud. The design keeps all user data isolated and encrypted.

Encrypted attestation links a user’s device to sealed processing environments, allowing only the user to access the data. Features like Magic Cue and Recorder on Pixel now perform smarter, multilingual actions privately. Google says this extends on-device protection principles into secure cloud operations.

The platform’s multi-layered safeguards follow Google’s Secure AI Framework and Privacy Principles. Private AI Compute enables enterprises and consumers to utilise Gemini models without exposing sensitive inputs. It reinforces Google’s vision for privacy-centric infrastructure in cloud-enabled AI.

By merging local and cloud intelligence, Google says Private AI Compute opens new paths for private, personalised AI. It will guide the next wave of Gemini capabilities while maintaining transparency and safety. The company positions it as a cornerstone of responsible AI innovation.

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EU and Switzerland deepen research ties through Horizon Europe agreement

Switzerland has formally joined Horizon Europe, the EU’s flagship research and innovation programme, together with Digital Europe and the Euratom Research and Training Programme.

An agreement, signed in Bern by Commissioner Ekaterina Zaharieva and Federal Councillor Guy Parmelin, that grants Swiss researchers the same status as their EU counterparts.

They can now lead projects, receive EU funding, and access every thematic pillar, reinforcing cross-border collaboration in fields such as climate technology, digital transformation, and energy security.

The accord, effective from 1 January 2025, also enables Switzerland to become a member of Fusion for Energy in 2026, thereby integrating its researchers into ITER, the world’s largest fusion energy initiative.

Plans include Swiss participation in Erasmus+ from 2027 and in the EU4Health programme once a separate health agreement takes effect.

A development that forms part of a broader package designed to deepen EU–Swiss relations and modernise cooperation frameworks across science, technology, and education.

The European Commission reaffirmed its commitment to finalising ratification of all related agreements, ensuring long-term collaboration and strengthening Europe’s position as a global leader in innovation and research.

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AI-powered Google Photos features land on iOS, search expands to 100+ countries

Google Photos is introducing prompt-based edits, an ‘Ask’ button, and style templates across iOS and Android. In the US, iPhone users can describe edits by voice or text, with a redesigned editor for faster controls. The rollout builds on the August Pixel 10’s debut of prompt editing.

Personalised edits now recognise people from face groups, so you can issue multi-person requests, such as removing sunglasses or opening eyes. Find it under ‘Help me edit’, where changes apply to each named person. It’s designed for faster, more granular everyday fixes.

A new Ask button serves as a hub for AI requests, from questions about a photo to suggested edits and related moments. The interface surfaces chips that hint at actions users can take. The Ask experience is rolling out in the US on both iOS and Android.

Google is also adding AI templates that turn a single photo into set formats, such as retro portraits or comic-style panels. The company states that its Nano Banana model powers these creative styles and that templates will be available next week under the Create tab on Android in the US and India.

AI search in Google Photos, first launched in the US, is expanding to over 100 countries with support for 17 languages. Markets include Argentina, Australia, Brazil, India, Japan, Mexico, Singapore, and South Africa. Google says this brings natural-language photo search to a far greater number of users.

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€5.5bn Google plan expands German data centres, carbon-free power and skills programmes

Google will invest €5.5bn in Germany from 2026 to 2029, adding a Dietzenbach data centre and expanding its Hanau facility. It will expand offices in Berlin, Frankfurt, and Munich, and launch skilling and a first German heat-recovery project. Estimated impact: ~€1.016bn GDP and ~9,000 jobs annually.

Dietzenbach will strengthen German cloud regions within Google’s 42-region network, used by firms such as Mercedes-Benz. Google Cloud highlights Vertex AI, Gemini, and sovereign options for local compliance. Continued Hanau investment supports low-latency AI workloads.

Google and Engie will extend 24/7 Carbon-Free Energy in Germany through 2030, adding new wind and solar. The portfolio will be optimised with storage and Ørsted’s Borkum Riffgrund 3. Operations are projected to be 85% carbon-free in 2026.

A partnership with Energieversorgung Offenbach will utilise excess data centre heat to feed into Dietzenbach’s district network, serving over 2,000 households. Water work includes wetland protection with NABU in Hesse’s Büttelborn Bruchwiesen. Google reiterates its 24/7 carbon-free goal.

Office expansion includes Munich’s Arnulfpost for up to 2,000 staff, Frankfurt’s Global Tower space, and additional floors in Berlin. Local partnerships will fund digital skills and STEM programmes. Officials and customers welcomed the move for its benefits to infrastructure, sovereignty, and innovation.

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Banks and insurers pivot to AI agents at scale, Capgemini finds

Agentic AI is expected to deliver up to $450 billion in value by 2028, as financial institutions shift frontline processes to AI agents, according to Capgemini’s estimates. Banks start with customer service before expanding into fraud detection, lending, and onboarding, while insurers report similar priorities.

To seize the opportunity, 33% of banks are building agents in-house, while 48% of institutions are creating human supervisor roles. Cloud’s role is expanding beyond infrastructure, with 61% of executives calling cloud-based orchestration critical to scaling.

Adoption is accelerating but uneven. Four in five firms are in ideation or pilots, yet only 10% run agents at scale. Executives expect gains in real-time decision-making, accuracy, and turnaround, especially across onboarding, KYC, loan processing, underwriting, and claims.

Leaders also see growth levers. Most expect agents to support entry into new geographies, enable dynamic pricing, and deliver multilingual services that respect local norms and rules. Budgets reflect this shift, with up to 40% of generative AI spend already earmarked for agents.

Barriers persist. Skills shortages and regulatory complexity top the list of concerns, alongside high implementation costs. A quarter of firms are exploring ‘service-as-a-software’ models, paying for outcomes such as the resolution of fraud cases or the handling of customer queries.

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ChatGPT-5 outperformed by a Chinese startup model

A Chinese company has stunned the AI world after its new open-source model outperformed OpenAI’s ChatGPT-5 and Anthropic’s Claude Sonnet 4.5 in key benchmarks.

Moonshot AI’s Kimi K2 Thinking model achieved the best reasoning and coding scores yet, shaking confidence in American dominance over advanced AI systems.

The Beijing-based startup, backed by Alibaba and Tencent, released Kimi K2 Thinking on 6 November. It scored 44.9 percent in Humanity’s Last Exam and 60.2 percent in BrowseComp, both surpassing leading US models.

Analysts dubbed it another ‘DeepSeek moment ‘, echoing the earlier success of China in breaking AI cost barriers.

Moonshot AI trained the trillion-parameter system for just US$4.6 million (nearly ten times cheaper than GPT-5’s reported costs) using a Mixture-of-Experts structure and advanced quantisation for faster generation.

The fully open-weight model, released under a Modified MIT License, adds commercial flexibility and intensifies competition with US labs.

Industry observers called it a turning point. Hugging Face’s Thomas Wolf said the achievement shows how open-source models can now rival closed systems.

Researchers from the Allen Institute for AI noted that Chinese innovation is narrowing the gap faster than expected, driven by efficiency and high-quality training data rather than raw computing power.

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Global AI adoption rises quickly but benefits remain unequal

Microsoft’s AI Economy Institute has released its 2025 AI Diffusion Report, detailing global AI adoption, innovation hubs, and the impact of digital infrastructure. AI has reached over 1.2 billion users in under three years, yet its benefits remain unevenly distributed.

Adoption rates in the Global North are roughly double those in the Global South, highlighting the risk of long-term inequalities.

AI adoption depends on strong foundational infrastructure, including electricity, data centres, internet connectivity, digital and AI skills, and language accessibility.

Countries with robust foundations- such as the UAE, Singapore, Norway, and Ireland- have seen rapid adoption, even without frontier-level model development. In contrast, regions with limited infrastructure and low-resource languages lag significantly, with adoption in some areas below 10%.

Ukraine exemplifies the potential for rapid AI growth, despite current disruptions from the war, with an adoption rate of 9.1%. Strategic investments in connectivity, AI skills, and language-inclusive solutions could accelerate recovery, strengthen resilience, and drive innovation.

AI is already supporting cybersecurity and helping businesses and organisations maintain operations amid ongoing challenges.

The concentration of AI infrastructure remains high, with the US and China hosting 86% of the global data centre capacity. A few countries dominate frontier AI development, yet the performance gap between leading models is narrowing.

Coordinated efforts across infrastructure, skills, and policy are crucial to ensure equitable access and maximise AI’s potential worldwide.

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Nvidia stake sale powers SoftBank’s $22.5bn OpenAI bet

SoftBank sold its entire Nvidia stake for $5.83 billion and part of its T-Mobile holding for $9.17 billion, raising cash for OpenAI. Alongside a margin loan on Arm, the proceeds fund a $22.5 billion commitment and other projects. Nvidia slipped 2%; SoftBank referred to it as asset monetisation, not a valuation call.

Executives said the goal is an investor opportunity with balance-sheet strength, including backing for ABB’s robotics deal. Analysts called the quarter’s funding need unusually large but consistent with an AI pivot. SoftBank said the sale recycles capital, not a retreat from Nvidia.

SoftBank has a history with Nvidia: the Vision Fund invested in 2017 and exited in 2019; group ventures still utilise its technology. Projects include the $500 billion Stargate data centre programme, built on accelerated computing. Shares remain volatile amid concerns about the AI bubble and questions regarding the timing of deployment.

Results reflected the shift, with $19 billion in Vision Fund gains helping to double profit in fiscal Q2. SoftBank says its OpenAI stake will rise from 4% to 11% after the recapitalisation, with scope to increase further. The group aims to avoid setting a controlling threshold while scaling exposure to AI.

Management stressed liquidity and shareholder access, flagging a four-for-one stock split and ‘very safe’ funding plans. Further portfolio monetisation is possible as it backs AI infrastructure and applications at scale. Investors will closely monitor execution risks and the timing of returns from OpenAI and its adjacent bets.

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MK1 joins AMD to accelerate enterprise AI and reasoning technologies

AMD has completed the acquisition of MK1, a California-based company specialising in high-speed inference and reasoning-based AI technologies.

The move marks a significant step in AMD’s strategy to strengthen AI performance and efficiency across hardware and software layers. MK1’s Flywheel and comprehension engines are designed to optimise AMD’s Instinct GPUs, offering scalable, accurate, and cost-efficient AI reasoning.

The MK1 team will join the AMD Artificial Intelligence Group, where their expertise will advance AMD’s enterprise AI software stack and inference capabilities.

Handling over one trillion tokens daily, MK1’s systems are already deployed at scale, providing traceable and efficient AI solutions for complex business processes.

By combining MK1’s advanced AI software innovation with AMD’s compute power, the acquisition enhances AMD’s position in the enterprise and generative AI markets, supporting its goal of delivering accessible, high-performance AI solutions globally.

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Deezer study shows most listeners cannot tell AI music from human tracks

A global study by Deezer and Ipsos highlights growing challenges and concerns around AI-generated music. Surveying 9,000 participants in eight countries, the study found that 97% could not distinguish between AI-generated music and human-created tracks.

Over half of the respondents reported discomfort at being unable to distinguish between the two.

The study also reveals strong support for transparency and fair treatment of artists. Eighty percent of respondents believe AI music should be clearly labelled, while most oppose using copyrighted material to train AI models.

Concerns over income losses are significant, with 70% saying AI tracks could threaten artists’ earnings, and nearly two-thirds fearing a reduction in creativity and musical quality.

Deezer now receives around 40,000 fully AI-generated tracks daily, representing over one-third of its daily uploads. To address transparency, the platform is the only streaming service to detect and label AI music clearly.

All AI tracks are excluded from algorithmic recommendations and editorial playlists, and manipulated streams are removed from royalty calculations.

The study marks a key moment for the music industry, stressing clear labelling, ethical AI use, and protecting artists’ livelihoods alongside innovation. Deezer’s proactive approach sets new industry standards for transparency and fairness in AI music streaming.

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