Interdisciplinary approaches

OpenAI expands AI training for newsrooms worldwide

The US tech company, OpenAI, has launched the OpenAI Academy for News Organisations, a new learning hub designed to support journalists, editors and publishers adopting AI in their work.

An initiative that builds on existing partnerships with the American Journalism Project and The Lenfest Institute for Journalism, reflecting a broader effort to strengthen journalism as a pillar of democratic life.

The Academy goes live with practical training, newsroom-focused playbooks and real-world examples aimed at helping news teams save time and focus on high-impact reporting.

Areas of focus include investigative research, multilingual reporting, data analysis, production efficiency and operational workflows that sustain news organisations over time.

Responsible use sits at the centre of the programme. Guidance on governance, internal policies and ethical deployment is intended to address concerns around trust, accuracy and newsroom culture, recognising that AI adoption raises structural questions rather than purely technical ones.

OpenAI plans to expand the Academy in the year ahead with additional courses, case studies and live programming.

Through collaboration with publishers, industry bodies and journalism networks worldwide, the Academy is positioned as a shared learning space that supports editorial independence while adapting journalism to an AI-shaped media environment.

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New AI framework simplifies complex scientific problems into basic equations

A team of scientists has created a new AI method that addresses complex problems across science and engineering by reducing them to simpler mathematical equations.

Unlike typical black-box AI models, this approach focuses on interpretable representations that can be expressed in basic symbolic forms, aiding understanding and trust in AI-generated solutions.

The research demonstrates that this symbolic reasoning capability allows AI to uncover underlying structure in tasks such as physics simulations, optimisation challenges and system modelling, potentially boosting both accuracy and generalisation.

Researchers argue that breaking problems down into fundamental components not only enhances performance but also makes AI outputs more understandable to human experts.

By combining machine learning with classical mathematical reasoning, the work points toward a hybrid paradigm in which AI augments human insight rather than merely approximating outcomes. Such methods could accelerate scientific discovery in fields where complexity has traditionally limited the effectiveness of computational approaches.

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Google launches Gemini 3 Flash for scalable frontier AI

The US tech giant, Google, has unveiled Gemini 3 Flash, a new frontier AI model designed for developers who need high reasoning performance combined with speed and low cost.

Built on the multimodal and agentic foundations of Gemini 3 Pro, Gemini 3 Flash delivers faster responses at less than a quarter of the price, while surpassing Gemini 2.5 Pro across several major benchmarks.

The model is rolling out through the Gemini API, Google AI Studio, Vertex AI, Android Studio and other developer platforms, offering higher rate limits, batch processing and context caching that significantly reduce operational costs.

Gemini 3 Flash achieves frontier-level results on advanced reasoning benchmarks while remaining optimised for large-scale production workloads, reinforcing Google’s focus on efficiency alongside intelligence.

Early adopters are already deploying Gemini 3 Flash across coding, gaming, deepfake detection and legal document analysis, benefiting from improved agentic capabilities and near real-time multimodal reasoning.

By lowering cost barriers while expanding performance, Gemini 3 Flash enhances Google’s competitive position in the rapidly evolving AI model market. It broadens access to advanced AI systems for developers and enterprises.

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UNDP and UNESCO support AI training for judiciary

UNESCO and UNDP have partnered to enhance judicial capacity on the ethical use of AI. A three-day Bangkok training, supported by the Thailand Institute of Justice, brought together 27 judges from 13 Asia-Pacific countries to discuss the impact of AI on justice and safeguards for fairness.

Expert sessions highlighted the global use of AI in court administration, research, and case management, emphasising opportunities and risks. Participants explored ways to use AI ethically while protecting human rights and judicial integrity, warning that unsupervised tools could increase bias and undermine public trust.

Trainers emphasised that AI must be implemented with careful attention to bias, transparency, and structural inequalities.

Judges reflected on the growing complexity of verifying evidence in the age of generative AI and deepfakes, and acknowledged that responsible AI can improve access to justice, support case reviews, and free time for substantive decision-making.

The initiative concluded with a consensus that AI adoption in courts should be guided by governance, transparency, and ongoing dialogue. The UNDP will continue to collaborate in advancing ethical, human rights-focused AI in regional judiciaries.

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AI-generated ads face new disclosure rules in South Korea

South Korea will require advertisers to label AI-generated or AI-assisted advertising from early 2026, marking a shift in how the country governs AI in online commerce and consumer protection.

The measure responds to a sharp rise in deceptive ads using synthetic imagery and deepfakes, particularly in healthcare and financial promotions. Regulators say transparency at the point of content delivery is intended to reduce manipulation and restore consumer trust.

Authorities in South Korea acknowledge that mandatory labelling alone may not deter malicious actors, who can bypass rules through offshore hosting or rapidly changing content. Detection challenges and uneven enforcement capacity across platforms remain open concerns.

South Korea’s industry groups warn that the policy could have uneven economic effects within the country’s advertising ecosystem. Large platforms and agencies are expected to adapt quickly, while smaller firms may face higher compliance costs that slow experimentation with generative tools.

Policymakers argue the framework aligns with South Korea’s broader AI governance strategy, positioning the country between innovation-led and precautionary regulatory models as synthetic media becomes more widespread.

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Segment Anything adds audio as Meta unveils SAM Audio

Meta has introduced SAM Audio, a new AI model that uses intuitive prompts to isolate and segment sounds from complex audio recordings. The release extends the company’s Segment Anything collection beyond visuals into audio and video workflows.

SAM Audio allows users to separate sounds through text prompts, visual cues, or time-based selections. Creators can extract vocals or instruments, remove background noise, or isolate specific sound sources in recordings without specialised audio engineering tools.

Meta describes SAM Audio as a unified model designed around how people naturally think about sound. It supports combined text, visual, and time-based prompts, enabling flexible audio separation across music, podcasting, film, accessibility, and research.

Meta says the model achieves strong performance across diverse audio environments and is already being used internally to develop next-generation creative tools. The approach lowers technical barriers while expanding the range of possible audio editing applications.

SAM Audio is available through the Segment Anything Playground, where users can test the model with sample assets or upload their own files. Meta has also made the model available for download, signalling broader ambitions to make audio segmentation a core capability of its AI ecosystem.

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AI helps Everbloom create sustainable cashmere alternatives

Everbloom has developed Braid.AI, an AI system that transforms waste fibres into high-quality textiles. The process can use poultry feathers, wool, and other keratin-rich materials to replicate fabrics like cashmere.

The system works with standard textile machinery, combining chopped waste with proprietary compounds to produce biodegradable fibres. Everbloom aims to reduce environmental impact while maintaining material quality comparable to traditional cashmere.

Co-founder Sim Gulati said the startup aims to make materials economically accessible. Products are designed to offer both environmental benefits and cost-effectiveness, avoiding a ‘sustainable premium’ for consumers.

The AI can fine-tune fibre properties for multiple fabrics beyond cashmere, including polyester alternatives. Everbloom collects waste from farms, mills, and other sources to create a sustainable supply chain.

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EU approves €1.8 billion clean energy boost through Modernisation Fund

The European Commission and the European Investment Bank have approved €1.8 billion in new clean energy funding under the EU Modernisation Fund, supporting 45 projects across 12 member states.

Portugal receives funding for the first time after becoming eligible in 2024, while total support from the Fund since 2021 has now reached €20.7 billion across 294 investments.

Financed through revenues from the EU Emissions Trading System, the Fund targets high-impact projects that reduce greenhouse gas emissions in energy, industry and transport, while improving energy efficiency and strengthening energy security.

In 2025 alone, total disbursements reached €5.46 billion, with significant allocations directed to Czechia, Poland, Romania and Hungary, alongside support for Greece, Portugal and Slovenia.

All projects approved during 2025 focus on renewable electricity generation, energy storage, grid modernisation and efficiency upgrades in public infrastructure and industry.

The Modernisation Fund plays a central role in supporting national climate plans, reducing dependence on fossil fuel imports and advancing the EU’s Fit for 55 and REPowerEU objectives, with further investment proposals scheduled for early 2026.

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AI shows promise in scientific research tasks

FrontierScience, a new benchmark from OpenAI, evaluates AI capabilities for expert-level scientific reasoning across physics, chemistry, and biology.

The benchmark measures Olympiad-style reasoning and real-world research tasks, showing how AI can aid complex scientific workflows. Generative AI models like GPT‑5 are now used for literature searches, complex proofs, and tasks that once took days or weeks.

The benchmark consists of two tracks: FrontierScience-Olympiad, with 100 questions created by international Olympiad medalists to assess constrained scientific reasoning, and FrontierScience-Research, with 60 multi-step research tasks developed by PhD scientists.

Initial evaluations show GPT‑5.2 scoring 77% on the Olympiad set and 25% on the Research set, outperforming other frontier models. The results show AI can support structured scientific reasoning but still struggles with open-ended problem solving and hypothesis generation.

FrontierScience also introduces a grading system tailored to each track. The Olympiad set uses short-answer verification, while the Research set employs a 10-point rubric assessing both final answers and intermediate reasoning steps.

Model-based grading allows for scalable evaluation of complex tasks, although human expert oversight remains ideal. Analyses reveal that AI models still make logic, calculation, and factual errors, particularly with niche scientific concepts.

While FrontierScience does not capture every aspect of scientific work, it provides a high-resolution snapshot of AI performance on difficult, expert-level problems. OpenAI plans to refine the benchmark, extend it to new domains, and combine it with real-world tests to track AI’s impact on scientific discovery.

The ultimate measure of success remains the novel insights and discoveries AI can help generate for the scientific community.

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BioTechEU aims to close Europe’s biotech funding gap

The European Commission and the European Investment Bank Group have launched BioTechEU, a new initiative to mobilise €10 billion in investment for biotechnology and life sciences between 2026 and 2027.

The programme targets Europe’s biotech funding gap, seeking to strengthen global competitiveness by channelling public and private capital into health innovation, including gene therapies, mRNA treatments, personalised medicine and AI-enabled medical technologies.

BioTechEU will operate under the EIB Group’s TechEU framework and draw on instruments such as the InvestEU guarantee. The initiative aligns with broader EU efforts to retain strategic health innovation within Europe and reduce reliance on external markets.

European Health Commissioner Olivér Várhelyi said under-investment continues to constrain biotech startups, adding that the European Commission sees BioTechEU as a way to help promising treatments scale and reach patients more efficiently across the EU.

EIB President Nadia Calviño said Europe has strong scientific talent and ideas, but deeper capital markets are needed. She described BioTechEU as a catalyst for enabling EU-based biotech companies to grow and compete globally.

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