Cloud computing

Spanish joins Google’s global AI Mode expansion

Google is rapidly expanding AI Mode, its generative AI-powered search assistant. The company has announced that the feature is now rolling out globally in Spanish. Spanish speakers can now interact with AI Mode to ask complex questions that traditional Search handles poorly.

AI Mode has seen swift adoption since its launch earlier this year. First introduced in March, the feature was rolled out to users across the US in May, followed by its first language expansion earlier this month.

Hindi, Indonesian, Japanese, Korean, and Brazilian Portuguese were the first languages added, and Spanish now joins the list. Google says more languages will follow soon as part of its global AI Mode rollout.

Google says the feature is designed to work alongside Search, not replace it, offering conversational answers with links to supporting sources. The company has stressed that responses are generated with safety filters and fact-checking layers.

The rollout reflects Google’s broader strategy to integrate generative AI into its ecosystem, spanning Search, Workspace, and Android. AI Mode will evolve with multimodal support and tighter integration with other Google services.

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AI image war heats up as ByteDance unveils Seedream 4.0

ByteDance has unveiled Seedream 4.0, its latest AI-powered image generation model, which it claims outperforms Google DeepMind’s Gemini 2.5 Flash Image. The launch signals ByteDance’s bid to rival leading creative AI tools.

Developed by ByteDance’s Seed division, the model combines advanced text-to-image generation with fast, precise image editing. Internal testing reportedly showed superior prompt accuracy, image alignment, and visual quality compared to US-developed DeepMind’s system.

Artificial Analysis, an independent AI benchmarking firm, called Seedream 4.0 a significant step forward. The model integrates Seedream 3.0’s generation capability with SeedEdit 3.0’s editing tools while maintaining a price of US$30 per 1,000 generations.

ByteDance claims that Seedream 4.0 runs over 10 times faster than earlier versions, enhancing the user experience with near-instant image inference. Early users have praised its ability to make quick, text-prompted edits with high accuracy.

The tool is now available to users in China through Jimeng and Doubao AI apps and businesses via Volcano Engine, ByteDance’s cloud platform. A formal technical report supporting the company’s claims has not yet been released.

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Alibaba unveils next-gen AI models and $53 billion infrastructure expansion

Just as Nvidia announced plans to spend $100 billion building out OpenAI’s infrastructure, Alibaba is doubling its ambitions, rolling out a powerful suite of AI models and expanding its data centres to support them.

At its annual Apsara Conference in Beijing, Alibaba unveiled Qwen3-Omni, a multimodal model capable of analysing text, images, audio, and video in real time. Released under an open Apache 2.0 license, businesses can freely download and deploy the system, setting it apart from closed, pay-to-use rivals like Google’s Gemini 2.5 Pro and OpenAI’s GPT-4o.

The company also introduced Qwen3-Max, its most advanced large language model yet, boasting over a trillion parameters. Alibaba executives say it shows particular strength in code generation and autonomous decision-making, enabling AI systems to act more independently than traditional chatbots. Benchmark tests indicate it outperforms models from Anthropic and DeepSeek in some areas.

What makes Qwen3-Omni unique is its architecture. Instead of adding vision or speech to a text-first system, it integrates all modalities from the ground up. The model is available in three versions, Instruct, Thinking, and Captioner, and can generate text and audio with low latency, outperforming rivals on reasoning, transcription, and video analysis.

Practical applications range from customer support tools that can analyse live video feeds of malfunctioning appliances to interactive assistants for virtual reality environments. Developers can fine-tune personality and style, from consumer services to enterprise transcription, adapting the system for industries.

Supporting these breakthroughs is a sweeping expansion of Alibaba’s infrastructure footprint. The firm plans to open its first data centres in Brazil, France, and the Netherlands, adding facilities in Mexico, Japan, South Korea, Malaysia, and Dubai. All this comes from an earlier pledge to invest $53 billion over three years into AI-related infrastructure.

By coupling record-setting AI models with a global data centre buildout, Alibaba is signalling it intends to compete head-to-head with US leaders. With open licensing, massive infrastructure spending, and technical performance that matches or surpasses its Western rivals, China’s e-commerce titan is making a bold play to reshape the global AI landscape.

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Gemini brings conversational AI to Google TV

Google has launched Gemini for TV, bringing conversational AI to the living room. The update builds on Google TV and Google Assistant, letting viewers chat naturally with their screens to discover shows, plan trips, or even tackle homework questions.

Instead of scrolling endlessly, users can ask Gemini to find a film everyone will enjoy or recap last season’s drama. The AI can handle vague requests, like finding ‘that new hospital drama,’ and provide reviews before you press play.

Gemini also turns the TV into an interactive learning tool. From explaining why volcanoes erupt to guiding kids through projects, it offers helpful answers with supporting YouTube videos for hands-on exploration.

Beyond schoolwork, Gemini can help plan meals, teach new skills like guitar, or brainstorm family trips, all through conversational prompts. Such features make the TV a hub for entertainment, education, and inspiration.

Gemini is now available on the TCL QM9K series, with rollout to additional Google TV devices planned for later this year. Google says additional features are coming soon, making TVs more capable and personalised.

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Europe prepares formal call for AI Gigafactory projects

The European Commission is collaborating with the EU capitals to narrow the list of proposals for large AI training hubs, known as AI Gigafactories. The €20 billion plan will be funded by the Commission (17%), the EU countries (17%), and industry (66%) to boost computing capacity for European developers.

The first call drew 76 proposals from 16 countries, far exceeding the initially planned four or five facilities. Most submissions must be merged or dropped, with Poland already seeking a joint bid with the Baltic states as talks continue.

Some EU members will inevitably lose out, with Ursula von der Leyen, the President of the European Commission, hinting that priority could be given to countries already hosting AI Factories. That could benefit Finland, whose Lumi supercomputer is part of a Nokia-led bid to scale up into a Gigafactory.

The plan has raised concerns that Europe’s efforts come too late, as US tech giants invest heavily in larger AI hubs. Still, Brussels hopes its initiative will allow EU developers to compete globally while maintaining control over critical AI infrastructure.

A formal call for proposals is expected by the end of the year, once the legal framework is finalised. Selection criteria and funding conditions will be set to launch construction as early as 2026.

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Misconfigurations drive major global data breaches

Misconfigurations in cloud systems and enterprise networks remain one of the most persistent and damaging causes of data breaches worldwide.

Recent incidents have highlighted the scale of the issue, including a cloud breach at the US Department of Homeland Security, where sensitive intelligence data was inadvertently exposed to thousands of unauthorised users.

Experts say such lapses are often more about people and processes than technology. Complex workflows, rapid deployment cycles and poor oversight allow errors to spread across entire systems. Misconfigured servers, storage buckets or access permissions then become easy entry points for attackers.

Analysts argue that preventing these mistakes requires better governance, training and process discipline rather. Building strong safeguards and ensuring staff have the knowledge to configure systems securely are critical to closing one of the most exploited doors in cybersecurity.

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Research shows AI complements, not replaces, human work

AI headlines often flip between hype and fear, but the truth is more nuanced. Much research is misrepresented, with task overlaps miscast as job losses. Leaders and workers need clear guidance on using AI effectively.

Microsoft Research mapped 200,000 Copilot conversations to work tasks, but headlines warned of job risks. The study showed overlap, not replacement. Context, judgment, and interpretation remain human strengths, meaning AI supports rather than replaces roles.

Other research is similarly skewed. METR found that AI slowed developers by 19%, but mostly due to the learning curves associated with first use. MIT’s ‘GenAI Divide’ measured adoption, not ability, showing workflow gaps rather than technology failure.

Better studies reveal the collaborative power of AI. Harvard’s ‘Cybernetic Teammate’ experiment demonstrated that individuals using AI performed as well as full teams without it. AI bridged technical and commercial silos, boosting engagement and improving the quality of solutions produced.

The future of AI at work will be shaped by thoughtful trials, not headlines. By treating AI as a teammate, organisations can refine workflows, strengthen collaboration, and turn AI’s potential into long-term competitive advantage.

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GPT-5-powered ChatGPT Edu comes to Oxford staff and students

The University of Oxford will become the first UK university to offer free ChatGPT Edu access to all staff and students. The rollout follows a year-long pilot with 750 academics, researchers, and professional services staff across the University and Colleges.

ChatGPT Edu, powered by OpenAI’s GPT-5 model, is designed for education with enterprise-grade security and data privacy. Oxford says it will support research, teaching, and operations while encouraging safe, responsible use through robust governance, training, and guidance.

Staff and students will receive access to in-person and online training, webinars, and specialised guidance on the use of generative AI. A dedicated AI Competency Centre and network of AI Ambassadors will support users, alongside mandatory security training.

The prestigious UK university has also established a Digital Governance Unit and an AI Governance Group to oversee the adoption of emerging technologies. Pilots are underway to digitise the Bodleian Libraries and explore how AI can improve access to historical collections worldwide.

A jointly funded research programme with the Oxford Martin School and OpenAI will study the societal impact of AI adoption. The project is part of OpenAI’s NextGenAI consortium, which brings together 15 global research institutions to accelerate breakthroughs in AI.

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Startups gain new tools on Google Cloud

Google Cloud says AI startups are increasingly turning to its technology stack, with more than 60% of global generative AI startups building on its infrastructure. Nine of the world’s top ten AI labs also rely on its cloud services.

To support this momentum, Google Cloud hosted its first AI Builders Forum in Silicon Valley, where hundreds of founders gathered to hear about new tools, infrastructure and programmes designed to accelerate innovation.

Google Cloud has also released a technical guide to help startups build and scale AI agents, including retrieval-augmented generation (RAG) and multimodal approaches. The guide highlights leveraging Google’s agentic development kit and agent-to-agent tools.

The support is bolstered by the Google for Startups Cloud Program, which offers credits worth up to $350,000, mentorship and access to partner AI models from Anthropic and Meta. Google says its goal is to give startups the technology and resources to launch, scale and compete globally.

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JFTC study and MSCA shape Japan’s AI oversight strategy

Japan is adopting a softer approach to regulating generative AI, emphasising innovation while managing risks. Its 2025 AI Bill promotes development and safety, supported by international norms and guidelines.

The Japan Fair Trade Commission (JFTC) is running a market study on competition concerns in AI, alongside enforcing the new Mobile Software Competition Act (MSCA), aimed at curbing anti-competitive practices in mobile software.

The AI Bill focuses on transparency, international cooperation, and sector-specific guidance rather than heavy penalties. Policymakers hope this flexible framework will avoid stifling innovation while encouraging responsible adoption.

The MSCA, set to be fully enforced in December 2025, obliges mobile platform operators to ensure interoperability and fair treatment of developers, including potential applications to AI tools and assistants.

With rapid AI advances, regulators in Japan remain cautious but proactive. The JFTC aims to monitor markets closely, issue guidelines as needed, and preserve a balance between competition, innovation, and consumer protection.

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