Google and Cassava expand Gemini access in Africa

Google announced a partnership with Cassava Technologies to widen access to Gemini across Africa. The deal includes data-free Gemini usage for eligible users coordinated through Cassava’s network partners. The initiative aims to address affordability and adoption barriers for mobile users.

A six-month trial of the Google AI Plus plan is part of the package. Benefits include access to more capable Gemini models and added cloud storage. Coverage by regional tech outlets reported the exact core details.

Education features were highlighted, including NotebookLM for study aids and Gemini in Docs for writing support. Google said the offer aims to help students, teachers, and creators work without worrying about data usage. Reports highlight a focus on youth and skills development.

Cassava’s role aligns with broader investments in AI infrastructure and services across the continent; recent announcements reference model exchanges and planned AI facilities that support regional development. Observers see momentum behind accessible AI tools.

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Northern Ireland teachers reclaim hours with AI

A six-month pilot across Northern Ireland put Gemini and Workspace into classrooms. One hundred teachers participated under the Education Authority’s C2k programme. Reported benefits centred on time savings and practical support for everyday teaching.

Participants said they saved around ten hours per week on routine tasks where freed time was redirected to pupil engagement and professional development. More than six hundred use cases from the one hundred participants were documented during the trial period.

Teachers cited varied applications, from drafting parent letters to generating risk assessments quickly. NotebookLM helped transform curriculum materials into podcasts and interactive mind maps. Inclusive lessons were tailored, including Irish language activities and support for neurodivergent learners.

C2k plans wider training so more Northen Ireland educators can adopt the tools responsibly. Leadership framed AI as collaborative, not a replacement for teachers. Further partnerships are expected to align products with established pedagogical principles.

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Microsoft brings smarter search to Copilot

Microsoft is expanding Copilot with more precise citations that link directly to publisher sources. Users can also open aggregated references for each answer to review context. The emphasis sits on trust, control, and transparent sourcing throughout the experience.

A new dedicated search mode within Copilot delivers more detailed results when queries require specific information.

Summaries appear alongside links, enabling users to verify evidence and make informed decisions quickly. Industry coverage highlights the stronger focus on verifiable sources and publisher visibility.

The right pane offers a ‘Show all’ list of sources used in responses. Source-based citation pills replace opaque markers to aid credibility checks and exploration. Design choices aim to empower people to stay in control while navigating complex topics.

Updates are live across copilot.com, mobile apps, and Copilot in Edge, with more refinements expected. Microsoft positions the changes within a human-centred strategy where AI supports curiosity safely. Broader Copilot enhancements across Windows and Edge continue in parallel roadmaps.

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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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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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The AI soldier and the ethics of war

The rise of the machine soldier

For decades, Western militaries have led technological revolutions on the battlefield. From bows to tanks to drones, technological innovation has disrupted and redefined warfare for better or worse. However, the next evolution is not about weapons, it is about the soldier.

New AI-integrated systems such as Anduril’s EagleEye Helmet are transforming troops into data-driven nodes, capable of perceiving and responding with machine precision. This fusion of human and algorithmic capabilities is blurring the boundary between human roles and machine learning, redefining what it means to fight and to feel in war.

Today’s ‘AI soldier’ is more than just enhanced. They are networked, monitored, and optimised. Soldiers now have 3D optical displays that give them a god’s-eye view of combat, while real-time ‘guardian angel’ systems make decisions faster than any human brain can process.

Yet in this pursuit of efficiency, the soldier’s humanity and the rules-based order of war risk being sidelined in favour of computational power.

From soldier to avatar

In the emerging AI battlefield, the soldier increasingly resembles a character in a first-person shooter video game. There is an eerie overlap between AI soldier systems and the interface of video games, like Metal Gear Solid, where augmented players blend technology, violence, and moral ambiguity. The more intuitive and immersive the tech becomes, the easier it is to forget that killing is not a simulation.

By framing war through a heads-up display, AI gives troops an almost cinematic sense of control, and in turn, a detachment from their humanity, emotions, and the physical toll of killing. Soldiers with AI-enhanced senses operate through layers of mediated perception, acting on algorithmic prompts rather than their own moral intuition. When soldiers view the world through the lens of a machine, they risk feeling less like humans and more like avatars, designed to win, not to weigh the cost.

The integration of generative AI into national defence systems creates vulnerabilities, ranging from hacking decision-making systems to misaligned AI agents capable of escalating conflicts without human oversight. Ironically, the same guardrails that prevent civilian AI from encouraging violence cannot apply to systems built for lethal missions.

The ethical cost

Generative AI has redefined the nature of warfare, introducing lethal autonomy that challenges the very notion of ethics in combat. In theory, AI systems can uphold Western values and ethical principles, but in practice, the line between assistance and automation is dangerously thin.

When militaries walk this line, outsourcing their decision-making to neural networks, accountability becomes blurred. Without the basic principles and mechanisms of accountability in warfare, states risk the very foundation of rules-based order. AI may evolve the battlefield, but at the cost of diplomatic solutions and compliance with international law.  

AI does not experience fear, hesitation, or empathy, the very qualities that restrain human cruelty. By building systems that increase efficiency and reduce the soldier’s workload through automated targeting and route planning, we risk erasing the psychological distinction that once separated human war from machine-enabled extermination. Ethics, in this new battlescape, become just another setting in the AI control panel. 

The new war industry 

The defence sector is not merely adapting to AI. It is being rebuilt around it. Anduril, Palantir, and other defence tech corporations now compete with traditional military contractors by promising faster innovation through software.

As Anduril’s founder, Palmer Luckey, puts it, the goal is not to give soldiers a tool, but ‘a new teammate.’ The phrasing is telling, as it shifts the moral axis of warfare from command to collaboration between humans and machines.

The human-machine partnership built for lethality suggests that the military-industrial complex is evolving into a military-intelligence complex, where data is the new weapon, and human experience is just another metric to optimise.

The future battlefield 

If the past century’s wars were fought with machines, the next will likely be fought through them. Soldiers are becoming both operators and operated, which promises efficiency in war, but comes with the cost of human empathy.

When soldiers see through AI’s lens, feel through sensors, and act through algorithms, they stop being fully human combatants and start becoming playable characters in a geopolitical simulation. The question is not whether this future is coming; it is already here. 

There is a clear policy path forward, as states remain tethered to their international obligations. Before AI blurs the line between soldier and system, international law could enshrine a human-in-the-loop requirement for all lethal actions, while defence firms are compelled to maintain high ethical transparency standards.

The question now is whether humanity can still recognise itself once war feels like a game, or whether, without safeguards, it will remain present in war at all.

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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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