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Europe needs clearer regulation to capture AI growth, Google says

Google says Europe faces a pivotal moment as AI reshapes global competitiveness, arguing that the region has the talent to lead the way. It points to growing demand for tools that help businesses innovate and expand. Startups like Idoven are highlighted as examples of Europe’s emerging strengths.

Google highlights its long-standing partnership with Europe, pointing to significant investments in infrastructure, security, and research. It has more than 40 offices and 31,000 staff across the region. DeepMind’s scientific advances, including broad use of AlphaFold, remain central to that work.

Despite this foundation, Google warns that Europe risks falling behind other regions without faster access to advanced AI models.

Only 14% of European companies currently utilise AI, which is significantly lower than the adoption rates in China and the United States. Google says outdated technology limits competitiveness across sectors.

Regulatory complexity is another concern, with more than 100 digital rules introduced since 2019. Google supports regulation but notes that abrupt changes and overlapping requirements can slow product launches and hinder smaller developers. The company calls for more straightforward, more explicit rules that avoid penalising innovation.

Google argues that Europe must also expand AI skills, from technical expertise to leadership and workforce readiness. It cites a decade of training initiatives that helped 15 million Europeans gain digital skills. With the right tools and support, Google says Europe could unlock €1.2 trillion in economic value.

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Gemini 3 struggles to accept the year 2025

Google’s new AI model, Gemini 3, was left temporarily confused when it refused to accept that the year was 2025 during early testing by AI researcher Andrej Karpathy.

The model, pre-trained on data only through 2024 and initially disconnected from the internet, accused Karpathy of trickery and gaslighting before finally recognising the correct date.

Once Gemini 3 accessed real-time information, it expressed astonishment and apologised for its previous behaviour, demonstrating the model’s quirky but sophisticated reasoning capabilities. The interaction went viral online, drawing attention to both the humour and unpredictability of advanced AI systems.

Experts note that incidents like this illustrate the limitations of LLMs, which, despite their reasoning power, cannot inherently perceive reality and rely entirely on pre-training data and connected tools.

Observers emphasise that AI remains a powerful human aid rather than a replacement, and understanding its quirks is essential for practical use.

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Italy closes Google probe after consent changes

Italy has closed its investigation into Google after the company agreed to adjust how it requests user consent for personal data use. Regulators had accused Google of presenting unclear and potentially misleading choices when connecting users to its services.

The authority said Google will now offer clearer explanations about how consent affects data processing. Updates will outline where personal information may be combined or used across the company’s wider service ecosystem.

Officials launched the probe in July 2024, arguing Google’s approach could amount to aggressive commercial practice. Revised consent flows were accepted as sufficient remedies, leading to the closure of the case without financial penalties.

The Italian competition regulator indicated that transparency improvements were central to compliance. Similar scrutiny continues across Europe as regulators assess how large technology firms obtain permission for extensive data handling.

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Google launches AI skilling blueprint to close Africa’s skills gap

Google has launched an AI Skilling Blueprint for Africa, activating a $7.5 million commitment to support expert local organisations in training talent. An additional $2.25 million will be used to modernise public data infrastructure.

The initiative aims to address the continent’s widening AI skills gap, where over half of businesses report the biggest barrier to growth is a shortage of qualified professionals.

The framework identifies three core groups for development. AI Learners build foundational AI skills, AI Implementers upskill professionals across key sectors, and AI Innovators develop experts and entrepreneurs to create AI solutions suited to African contexts.

Partner organisations include FATE Foundation, the African Institute for Mathematical Sciences, JA Africa and the CyberSafe Foundation.

Complementing talent development, the initiative supports the creation of a Regional Data Commons through funding from Google.org and the Data Commons initiative, in partnership with UNECA, UN DESA and PARIS21.

High-quality, trustworthy data will enable African institutions to make informed decisions, drive innovation in public health, food security, economic planning, and ultimately strengthen a sustainable AI ecosystem across the continent.

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Google launches Nano Banana Pro image model

Google has launched Nano Banana Pro, a new image generation and editing model built on Gemini 3 Pro. The upgrade expands Gemini’s visual capabilities inside the Gemini app, Google Ads, Google AI Studio, Vertex AI and Workspace tools.

Nano Banana Pro focuses on cleaner text rendering, richer world knowledge and tighter control over style and layout. Creators can produce infographics, diagrams and character consistent scenes, and refine lighting, camera angle or composition with detailed prompts.

The AI model supports higher resolution visuals, localised text in multiple languages and more accurate handling of complex scripts. Google highlights uses in marketing materials, business presentations and professional design workflows, as partners such as Adobe integrate the model into Firefly and Photoshop.

Users can try Nano Banana Pro through Gemini with usage limits, while paying customers and enterprises gain extended access. Google embeds watermarking and C2PA-style metadata to help identify AI-generated images, foregrounding safety and transparency around synthetic content.

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Sundar Pichai warns users not to trust AI tools easily

Google CEO Sundar Pichai advises people not to unquestioningly trust AI tools, warning that current models remain prone to errors. He told the BBC that users should rely on a broader information ecosystem rather than treat AI as a single source of truth.

Pichai said generative systems can produce inaccuracies and stressed that people must learn what the tools are good at. The remarks follow criticism of Google’s own AI Overviews feature, which attracted attention for erratic and misleading responses during its rollout.

Experts say the risk grows when users depend on chatbots for health, science, or news. BBC research found major AI assistants misrepresented news stories in nearly half of the tests this year, underscoring concerns about factual reliability and the limits of current models.

Google is launching Gemini 3.0, which it claims offers stronger multimodal understanding and reasoning. The company says its new AI Mode in search marks a shift in how users interact with online information, as it seeks to defend market share against ChatGPT and other rivals.

Pichai says Google is increasing its investment in AI security and releasing tools to detect AI-generated images. He maintains that no single company should control such powerful technology and argues that the industry remains far from a scenario in which one firm dominates AI development.

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Scepticism needed for AI says Alphabet CEO

Alphabet CEO Sundar Pichai recently warned people against having total confidence in artificial intelligence tools. Speaking to the BBC, the head of Google’s parent company stressed that current state-of-the-art AI technology remains ‘prone to errors’ and must be used judiciously alongside other resources.

The executive also addressed wider concerns about a potential ‘AI bubble’ following increased tech valuations and spending across the sector. Pichai stated he believes no corporation, including Google, would be completely safe if such an investment surge were to collapse. He compared the current environment to the early internet boom, suggesting the profound impact of AI will nonetheless remain.

Simultaneously, the largest bank in the US, JPMorgan Chase, is sounding an alarm over market instability. Jamie Dimon, the bank’s chair and chief executive, expressed significant worry over a severe US stock market correction, predicting it could materialise within the next six months to two years. Concerns over the geopolitical climate, expansive fiscal spending, and worldwide remilitarisation are adding to this atmosphere of economic uncertainty.

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Meta wins antitrust case over monopoly claims

Meta has defeated a major antitrust challenge after a US federal judge ruled it does not currently hold monopoly power in social networking. The decision spares the company from being forced to separate Instagram and WhatsApp, which regulators had argued were acquired to suppress competition.

The judge found the Federal Trade Commission failed to prove Meta maintains present-day dominance, noting that the market has been reshaped by rivals such as TikTok. Meta argued it now faces intense competition across mobile platforms as user behaviour shifts rapidly.

FTC lawyers revisited internal emails linked to Meta’s past acquisitions, but the ruling emphasised that the case required proof of ongoing violations.

Analysts say the outcome contrasts sharply with recent decisions against Google in search and advertising, signalling mixed fortunes for large tech firms.

Industry observers note that Meta still faces substantial regulatory pressure, including upcoming US trials regarding children’s mental health and questions about its heavy investment in AI.

The company welcomed the ruling and stated that it intends to continue developing products within a competitive market framework.

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Google enters a new frontier with Gemini 3

A new phase of its AI strategy has begun for Google with the release of Gemini 3, which arrives as the company’s most advanced model to date.

The new system prioritises deeper reasoning and more subtle multimodal understanding, enabling users to approach difficult ideas with greater clarity instead of relying on repetitive prompting. It marks a major step for Google’s long-term project to integrate stronger intelligence into products used by billions.

Gemini 3 Pro is already available in preview across the Gemini app, AI Mode in Search, AI Studio, Vertex AI and Google’s new development platform known as Antigravity.

A model that performs at the top of major benchmarks in reasoning, mathematics, tool use and multimodal comprehension, offering substantial improvements compared with Gemini 2.5 Pro.

Deep Think mode extends the model’s capabilities even further, reaching new records on demanding academic and AGI-oriented tests, although Google is delaying wider release until additional safety checks conclude.

Users can rely on Gemini 3 to learn complex topics, analyse handwritten material, decode long academic texts or translate lengthy videos into interactive guides instead of navigating separate tools.

Developers benefit from richer interactive interfaces, more autonomous coding agents and the ability to plan tasks over longer horizons.

Google Antigravity enhances this shift by giving agents direct control of the development environment, allowing them to plan, write and validate code independently while remaining under human supervision.

Google emphasises that Gemini 3 is its most extensively evaluated model, supported by independent audits and strengthened protections against manipulation. The system forms the foundation for Google’s next era of agentic, personalised AI and will soon expand with additional models in the Gemini 3 series.

The company expects the new generation to reshape how people learn, build and organise daily tasks instead of depending on fragmented digital services.

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New Quantum Echoes system reveals molecular structures at scale

Google says its new Quantum Echoes algorithm runs 13,000 times faster than leading supercomputers, marking what it calls the first verifiable quantum result across different hardware. The breakthrough brings real-world use cases in medicine and materials science closer to feasibility.

Quantum Echoes is built to overcome a core limitation in today’s models: constrained memory that prevents long reasoning chains. The method uses structured world models to maintain a single research goal while processing tens of millions of tokens across multiple agent runs.

Powered by the Willow quantum chip, the system reads thousands of scientific papers and executes tens of thousands of lines of analysis code in a single run. Early estimates suggest one execution could match six months of human scientific labour.

Recent studies have shown that the algorithm reproduces known molecular findings and generates new insights using a technique likened to a quantum molecular ruler. Results matched those of nuclear magnetic resonance techniques, indicating that quantum tools could reveal previously inaccessible structural detail.

Experts still caution that practical quantum computing remains years away. Google faces competition from IBM, Microsoft, and Chinese labs, yet the company argues that Quantum Echoes proves its hardware and algorithms are converging toward usable scientific applications.

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