Interdisciplinary approaches

New ChatGPT layout blends audio, text and maps in one view

OpenAI has unveiled an updated ChatGPT interface that combines voice and text features in a single view. Users can speak naturally at any point in a chat and receive responses in text, audio, or images. The new layout also introduces real-time map displays.

The redesign adds a scrolling transcript within the chat window. It allows users to revisit earlier exchanges and move easily between reading and listening. OpenAI states that the goal is to support voice-led tasks without compromising clarity.

With the unified experience, conversations no longer require switching modes. ChatGPT can deliver audio, written, and visual replies simultaneously. Maps and images appear directly alongside the voice response.

Every spoken message is automatically transcribed. However, this helps users follow more extended discussions and keep a record for later reference. OpenAI says the feature supports both accessibility and everyday convenience.

The update is rolling out gradually across web and mobile platforms. Users who prefer the earlier voice-only layout can revert to it in settings. OpenAI says the unified mode will remain the default as development continues.

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AI may reshape weather and climate modelling

The UK’s Met Office has laid out a strategic plan for integrating AI, specifically machine learning (ML), with traditional physics-based climate and weather models. The aim is to deliver what it calls an ‘optimal blend’ of AI-driven and physics-based forecasting.

To clarify what that blend might look like, the Met Office has defined five distinct approaches. One is the familiar independent physics-based model, which uses physical laws to simulate atmospheric dynamics, trusted but computationally intensive.

At the other end is an independent ML-based model that learns patterns entirely from data, offering far greater speed and scalability.

Between these extremes lie two ‘hybrid’ approaches: hybrid-integrated ML, where ML replaces or enhances parts of the physics model, and hybrid-composite ML, where ML and physics models run separately and feed into each other.

A fifth option is augmented ML, where ML is applied after the model has run to improve its output (for example, downscaling or refining ensemble forecasts).

However, this framework is more than a technical taxonomy; it provides a shared language for scientists, policymakers, and clients to understand how AI and traditional modelling can coexist.

It also helps guide future decisions, for example, allowing gradual adoption of ML in places where it makes sense, while preserving the robustness of well-understood physics methods in critical areas.

The move comes as ML-based weather and climate tools have shown increasing promise. For instance, in 2025, the Met Office published research showing a purely ML-based model achieved seasonal forecasting skill comparable to conventional physics-based methods, but with far lower computing demands.

For digital-policy watchers and climate analysts alike, this signals a shift: forecasting may become more dynamic, scalable and accessible, especially valuable in a changing climate where speed, resolution and adaptability matter as much as theoretical accuracy.

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AWS commits $50bn to US government AI

Amazon Web Services plans to invest $50 billion in high performance AI infrastructure dedicated to US federal agencies. The programme aims to broaden access to AWS tools such as SageMaker AI, Bedrock and model customisation services, alongside support for Anthropic’s Claude.

The expansion will add around 1.3 gigawatts of compute capacity, enabling agencies to run larger models and speed up complex workloads. AWS expects construction of the new data centres to begin in 2026, marking one of its most ambitious government-focused buildouts to date.

Chief executive Matt Garman argues the upgrade will remove long-standing technology barriers within government. The company says enhanced AI capabilities could accelerate work in areas ranging from cybersecurity to medical research while strengthening national leadership in advanced computing.

AWS has spent more than a decade developing secure environments for classified and sensitive government operations. Competitors have also stepped up US public sector offerings, with OpenAI, Anthropic and Google all rolling out heavily discounted AI products for federal use over the past year.

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ChatGPT for Teachers launched as OpenAI expands educator tools

OpenAI has launched ChatGPT for Teachers, offering US US educators a secure workspace to plan lessons and utilise AI safely. The service is free for verified K–12 staff until June 2027. OpenAI states that its goal is to support classroom tasks without introducing data risks.

Educators can tailor responses by specifying grades, curriculum needs, and preferred formats. Content shared in the workspace is not used to train models by default. The platform includes GPT-5.1 Auto, search, file uploads, and image tools.

The system integrates with widely used school software, including Google Drive, Microsoft 365, and Canva. Teachers can import documents, design presentations, and organise materials in one place. Shared prompt libraries offer examples from other educators.

Collaboration features enable co-planned lessons, shared templates, and school-specific GPTs. OpenAI says these tools aim to reduce administrative workloads. Schools can create collective workspaces to coordinate teaching resources more easily.

The service remains free through June 2027, with pricing updates to follow later. OpenAI plans to keep costs accessible for schools. Educators can begin using the platform by verifying their status through SheerID.

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India confronts rising deepfake abuse as AI tools spread

Deepfake abuse is accelerating across India as AI tools make it easy to fabricate convincing videos and images. Researchers warn that manipulated media now fuels fraud, political disinformation and targeted harassment. Public awareness often lags behind the pace of generative technology.

Recent cases involving Ranveer Singh and Aamir Khan showed how synthetic political endorsements can spread rapidly online. Investigators say cloned voices and fabricated footage circulated widely during election periods. Rights groups warn that such incidents undermine trust in media and public institutions.

Women face rising risks from non-consensual deepfakes used for harassment, blackmail and intimidation. Cases involving Rashmika Mandanna and Girija Oak intensified calls for stronger protections. Victims report significant emotional harm as edited images spread online.

Security analysts warn that deepfakes pose growing risks to privacy, dignity and personal safety. Users can watch for cues such as uneven lighting, distorted edges, or overly clean audio. Experts also advise limiting the sharing of media and using strong passwords and privacy controls.

Digital safety groups urge people to avoid engaging with manipulated content and to report suspected abuse promptly. Awareness and early detection remain critical as cases continue to rise. Policymakers are being encouraged to expand safeguards and invest in public education on emerging risks associated with AI.

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AI helps you shop smarter this holiday season

Holiday shoppers can now rely on AI to make Black Friday and Cyber Monday less stressful. AI tools help track prices across multiple retailers and notify users when items fall within their budget, saving hours of online searching.

Finding gifts for difficult-to-shop-for friends and family is also easier with AI. By describing a person’s interests or lifestyle, shoppers receive curated recommendations with product details, reviews, and availability, drawing from billions of listings in Google’s Shopping Graph.

Local shopping is more convenient thanks to AI features that enhance the shopping experience. Shoppers can check stock at nearby stores without having to call around, and virtual try-on technology allows users to see how clothing looks on them before making a purchase.

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US warns of rising senior health fraud as AI lifts scam sophistication

AI-driven fraud schemes are on the rise across the US health system, exposing older adults to increasing financial and personal risks. Officials say tens of billions in losses have already been uncovered this year. High medical use and limited digital literacy leave seniors particularly vulnerable.

Criminals rely on schemes such as phantom billing, upcoding and identity theft using Medicare numbers. Fraud spans home health, hospice care and medical equipment services. Authorities warn that the ageing population will deepen exposure and increase long-term harm.

AI has made scams harder to detect by enabling cloned voices, deepfakes and convincing documents. The tools help impersonate providers and personalise attacks at scale. Even cautious seniors may struggle to recognise false calls or messages.

Investigators are also using AI to counter fraud by spotting abnormal billing, scanning records for inconsistencies and flagging high-risk providers. Cross-checking data across clinics and pharmacies helps identify duplicate claims. Automated prompts can alert users to suspicious contacts.

Experts urge seniors to monitor statements, ignore unsolicited calls and avoid clicking unfamiliar links. They should verify official numbers, protect Medicare details and use strong login security. Suspicious activity should be reported to Medicare or to local fraud response teams.

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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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LSEG data and LG’s EXAONE model combine in new AI-driven stock prediction service

LG AI Research and LSEG have launched an AI forecasting tool that scores around 5,000 NYSE stocks daily. It combines LSEG’s financial data with LG’s EXAONE model. The service was presented to Korean financial institutions in Seoul.

The AI Equity Forecasting Score provides a numeric outlook and a short explanation for each stock. It analyses structured market data and unstructured filings and news. LG says this improves transparency in automated research.

LSEG says the partnership combines its global data infrastructure with LG’s modelling capabilities. According to LG, the system can uncover patterns that traditional analysis often misses. Daily scores and weekly commentary are already available.

Pilot testing is underway in the US, Europe, Japan and Korea. Analysts say wider adoption will depend on clear performance metrics and independent validation. They also note the lack of disclosure on trading frictions.

LG plans to expand the service to more markets and add tools for portfolio construction and commodities. Deeper integration with LSEG’s APIs is also being explored. LG describes the system as a daily, automated investment memo.

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New NVIDIA model drives breakthroughs in conservation biology

Researchers have introduced a biology foundation model that can recognise over a million species and understand relationships across the animal and plant kingdoms.

BioCLIP 2 was trained on one of the most extensive biological datasets ever compiled, allowing it to identify traits, cluster organisms and reveal patterns that support conservation efforts.

A model that relies on NVIDIA accelerated computing instead of traditional methods and demonstrates what large-scale biological learning can achieve.

Training drew on more than two hundred million images that cover hundreds of thousands of taxonomic classes. The AI model learned how species fit within wider biological hierarchies and how traits differ across age, gender and related groups without explicit guidance.

It even separated diseased leaves from healthy samples, offering a route to improved monitoring of ecosystems and agricultural resilience.

Scientists now plan to expand the project by utilising wildlife digital twins that simulate ecological systems in controlled environments.

Researchers will be able to study species interactions and test scenarios instead of disturbing natural habitats. The approach opens possibilities for richer ecological research and could offer the public immersive ways to view biodiversity from the perspective of different animals.

BioCLIP 2 is available as open-source software and has already attracted strong global interest. Its capabilities indicate a shift toward more advanced biological modelling powered by accelerated computing, providing conservationists and educators with new tools to address long-standing knowledge gaps.

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