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Google Earth AI supports disease forecasting and public health planning

Researchers are increasingly combining geospatial data with predictive modelling to anticipate health risks.

In that context, Google has introduced new capabilities within Google Earth AI designed to help public health experts forecast outbreaks and identify vulnerable communities.

The system integrates environmental information such as weather patterns, flooding and air quality with population mobility data and health records.

These insights allow researchers to analyse how environmental conditions influence the spread of diseases, including Dengue Fever and Cholera.

Several research initiatives are already testing the models. In collaboration with the World Health Organisation Regional Office for Africa, forecasting tools combining Google’s time-series models with geospatial data improved cholera prediction accuracy by more than 35 percent.

Academic researchers are also applying the technology to other diseases. Scientists at the University of Oxford have used Earth AI datasets to improve six-month dengue forecasts in Brazil, helping local authorities prepare preventative responses.

The technology is also being tested for chronic disease analysis. In Australia, partnerships with health organisations are exploring how geospatial models can identify regional health needs and support preventative care strategies.

Combining environmental intelligence with health data could enable public health systems to shift from reactive crisis management to earlier detection and prevention of disease outbreaks.

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China prioritises AI and tech self-reliance in new five-year plan

A new five-year development plan approved by lawmakers in Beijing places innovation and advanced technology at the centre of future economic growth. The strategy is designed to strengthen technological capabilities and position China as a leading global tech power.

The plan outlines ambitions to upgrade China’s industrial sector, expand domestic research capacity, and reduce reliance on foreign technologies. Priority sectors include AI, robotics, aerospace, biotechnology, and quantum computing. Officials see these industries as key drivers of economic growth over the coming decades.

AI features prominently in the strategy, with the term appearing dozens of times in the policy document. Beijing plans to expand AI-related industries, invest in large computing clusters, and support the development of advanced systems capable of performing complex tasks beyond traditional chatbots.

China also aims to increase spending on science and technology, with government research budgets rising by around 10 percent annually. The plan sets a target of expanding research and development investment by at least 7 percent per year, reflecting Beijing’s intention to strengthen domestic innovation capacity.

Efforts to achieve greater technological self-sufficiency come amid continued tensions with the United States over trade and technology restrictions. Export controls on advanced semiconductor technologies have highlighted China’s dependence on foreign chips, prompting the government to pursue breakthroughs across the semiconductor supply chain and emerging technologies.

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France pushes EU AI gigafactories to support European technology

In the EU, France is calling for planned European AI ‘gigafactories’ to focus on testing and scaling European technologies rather than primarily increasing demand for hardware from companies such as Nvidia.

The large computing facilities are intended to provide the infrastructure needed to train advanced AI systems. However, officials in France argue that the projects should strengthen Europe’s technological capabilities rather than reinforce reliance on foreign suppliers.

Several EU countries, including Poland, Austria and Lithuania, support using the infrastructure to improve Europe’s digital resilience.

The initiative forms part of the European Commission’s wider plans to expand computing capacity and support the development of a stronger European AI ecosystem.

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OpenAI says ChatGPT advertisements remain limited to the US

Despite speculation that the feature was expanding internationally, OpenAI has clarified that advertisements in ChatGPT are currently available only to users in the US.

Questions about a broader rollout emerged after references to advertisements appeared in the platform’s updated privacy policy. Some users interpreted the language as evidence that advertising would soon be introduced globally.

OpenAI said the policy update does not signal an immediate expansion. According to the company, advertising features are still being tested within the US as part of a gradual deployment strategy.

ChatGPT advertisements were introduced in February 2026 and appear below responses generated by the chatbot. The ads are shown only to logged-in users on free subscription tiers and are not displayed to users under eighteen.

Company representatives stated that advertising systems operate independently from the AI model that generates responses. According to OpenAI, advertisers cannot influence or modify the content produced by ChatGPT.

The company also said it does not share user conversations or personal chat histories with advertisers. However, advertisements may still be personalised based on user queries, which has prompted discussions about how conversational interfaces could shape consumer decisions.

OpenAI indicated that it is adopting a cautious, phased approach before considering any wider rollout of ChatGPT advertising features in other markets.

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OpenAI plans to integrate Sora video generation into ChatGPT

According to reports, OpenAI is preparing to integrate its AI video generator Sora directly into ChatGPT, a move that could expand the platform’s capabilities beyond text and image generation.

Sora currently operates as a standalone application and web service. Integrating the tool into ChatGPT could dramatically increase its visibility and usage, particularly given the chatbot’s massive global user base.

The company released an updated version of the model in 2025 that allows users to create, remix and even appear inside AI-generated videos. Bringing those features into ChatGPT would represent a major step toward making video generation a mainstream function within conversational AI systems.

Competition in the generative video market is intensifying. Companies, including Google, are developing similar technologies, with the company’s Gemini platform offering video creation powered by the Veo system. Other developers are also launching text-to-video models as the field rapidly expands.

Despite the potential growth, integrating video generation into ChatGPT may significantly increase operating costs. Running large AI systems requires vast computing resources and energy, and the chatbot already costs billions of dollars annually to operate.

Although OpenAI earns revenue from subscriptions, the majority of ChatGPT users currently use the free version. The company is therefore exploring additional monetisation strategies, including advertising and new premium services.

Integrating Sora into ChatGPT could therefore serve both strategic and financial goals, strengthening the platform’s position in the competitive generative AI market while expanding the types of content users can create.

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AI tools encourage exploration in creative tasks

AI is often associated with automation and job replacement, yet new research from Swansea University suggests a different role. Findings indicate that AI can serve as a creative collaborator, encouraging exploration and deeper engagement during design tasks.

Researchers from the university’s Computer Science Department ran an experiment with over 800 participants using an AI-supported system to design virtual cars.

Rather than optimising results, the system generated galleries with varied design ideas, including effective, unusual, and intentionally flawed concepts.

According to lead researcher Sean Walton, exposure to AI-generated suggestions increased participants’ involvement. Many users spent longer working on the task and produced stronger designs after interacting with the system’s diverse proposals.

The study in ACM Transactions on Interactive Intelligent Systems argues that traditional methods for evaluating AI tools are too narrow. Researchers believe broader assessments are needed to measure how AI affects human thinking, emotions, and creative exploration.

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AI technology set to reshape farming and rural life in South Korea

South Korea has launched a national agenda to expand AI across agriculture, aiming to boost productivity and improve living standards in rural communities. Officials from the Ministry of Agriculture, Food and Rural Affairs and the Ministry of Science and ICT presented the strategy as part of a wider digital transformation effort.

Plans include expanding smart farm models that reduce labour-intensive tasks and allow more farmers to benefit from automated technologies. Shared machinery centres and autonomous farming tools such as drones will be developed with support from the Rural Development Administration.

Authorities also intend to apply AI to agricultural distribution through smart logistics facilities that manage receiving, sorting and shipping processes. Around 300 smart Agricultural Products Processing Centres are expected to operate nationwide by 2030.

Livestock grading systems using AI will be introduced to improve accuracy and consumer trust across pork and beef processing facilities. Officials aim to raise the share of AI-graded meat from 19.4 percent in 2025 to 70 percent by 2030.

Beyond production, the programme seeks to expand ‘smart rural communities’ offering AI-based services such as transport, daily living support and farming assistance. Policymakers believe that a stronger digital infrastructure will help rural regions respond to climate pressures and an ageing population.

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Writer files lawsuit against Grammarly over AI feature using experts’ identities

A journalist has filed a class action lawsuit against Grammarly after the company introduced an AI feature that generated editorial feedback by imitating well-known writers and public figures without their permission.

The legal complaint was submitted by investigative journalist Julia Angwin, who argued that the tool unlawfully used the identities and reputations of authors and commentators.

The feature, known as ‘Expert Review’, produced automated critiques presented as if they came from figures such as Stephen King, Carl Sagan and technology journalist Kara Swisher.

Such a feature was available to subscribers paying an annual fee and was designed to simulate professional editorial guidance.

Critics quickly questioned both the quality of the generated feedback and the decision to associate the tool with real individuals who had not authorised the use of their names or expertise.

Technology writer Casey Newton tested the system by submitting one of his own articles and receiving automated feedback attributed to an AI version of Swisher. The response appeared generic, casting doubt on the value of linking such commentary to prominent personalities.

Following criticism from writers and researchers, the feature was disabled. Shishir Mehrotra, chief executive of Grammarly’s parent company Superhuman, issued a public apology while defending the broader concept behind the tool.

The lawsuit reflects growing tensions around AI systems that replicate creative styles or professional expertise.

As generative AI technologies expand across writing and publishing industries, questions surrounding consent, intellectual labour and identity rights are becoming increasingly prominent.

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EU lawmakers move forward on AI Act changes

Members of the European Parliament have reached a preliminary political agreement on amendments to the EU Artificial Intelligence Act. The compromise will be reviewed by parliamentary committees before a scheduled vote in Brussels.

Lawmakers in the EU agreed to extend compliance deadlines for some high risk AI systems. The changes aim to give companies and regulators more time to prepare technical standards and enforcement frameworks.

The proposed amendments also include a ban on AI systems that create non consensual explicit deepfakes. Officials in the EU say the measure aims to strengthen consumer protection and improve online safety for children.

Industry groups in the EU have raised concerns about compliance burdens linked to the revised rules. Policymakers in the EU continue negotiations as the legislation moves toward committee approval.

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New venture aims to build AI that understands the real world

AI pioneer Yann LeCun has secured more than $1 billion in funding for a new startup that aims to rethink how AI systems learn about the world.

The venture, called Advanced Machine Intelligence (AMI), will focus on developing AI that learns from real-world signals, such as camera and sensor data, rather than relying primarily on text. According to this French company, such systems could make better decisions by understanding how events unfold in the physical world.

AMI plans to build what researchers call ‘world models’, AI systems designed to predict the consequences of actions before they happen. Developers believe that grounding AI in real-world data could make the technology more reliable and easier to control, especially in critical safety applications.

Operations will span several global research hubs, including Paris, New York City, Montreal and Singapore. The company has already begun assembling its leadership team, appointing entrepreneur Alex LeBrun as chief executive and AI researcher Saining Xie as chief science officer.

Support for the project quickly appeared online. Emmanuel Macron welcomed the launch, saying it represented a new chapter in AI and highlighting the role of researchers and innovators in shaping the technology’s future.

LeCun is widely regarded as one of the key figures behind modern AI. In 2018, he shared the prestigious Turing Award with fellow researchers Geoffrey Hinton and Yoshua Bengio for their contributions to deep learning.

Research at AMI will focus on building AI systems that can reason, plan actions and maintain long-term memory. Possible applications range from robotics and industrial automation to healthcare and wearable technologies, areas where dependable AI could have a major impact.

LeCun and his team argue that genuine intelligence cannot emerge from language alone. Understanding the world, they say, requires machines that learn directly from it.

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