Artificial intelligence Archives | Page 25 of 707

OpenAI previews GPT-5.6 Sol model with stronger safeguards

OpenAI has begun a limited preview of GPT-5.6 Sol, a new flagship model in its new GPT-5.6 family, which also includes Terra and Luna. The company said all three models are expected to become generally available in the coming weeks.

The company said the preview is initially limited to a small group of trusted partners. OpenAI said it shared its release plans and model capabilities with the U S government before launch and is initially limiting access at the government’s request.

The company said it does not consider government pre-release access an appropriate long-term default. Instead, it described the limited preview as a temporary measure while working with the US administration on a repeatable release framework linked to a cybersecurity Executive Order.

OpenAI described GPT-5.6 Sol as its most capable model to date, highlighting improvements in agentic coding, biology and cybersecurity while saying a broader set of evaluation results will be published when the model becomes generally available.

For coding, OpenAI said GPT-5.6 Sol set a new state of the art on Terminal-Bench 2.1, which tests command-line workflows involving planning, iteration and tool coordination.

The company also reported improvements in biology workflows. On GeneBench v1, which evaluates long-horizon genomics and quantitative biology tasks, OpenAI said the model performed better than GPT-5.5 while using fewer tokens.

Cybersecurity is a major focus of the preview. OpenAI said GPT-5.6 Sol is its most capable model yet for cybersecurity tasks, including vulnerability research and exploitation-related workflows.

OpenAI said the model performs better at identifying and helping remediate vulnerabilities than at carrying out end-to-end offensive cyber operations. According to the company, GPT-5.6 Sol did not exceed the Cyber Critical threshold under its Preparedness Framework.

OpenAI said the GPT-5.6 release includes its most robust safeguards to date, with configurations tailored to each model’s capabilities. The company said these safeguards are intended to constrain prohibited offensive use while preserving access for legitimate work such as code review, vulnerability research, patch development, debugging, security education and defensive testing.

Safeguards include model-level protections, real-time generation checks, account-level monitoring, differentiated access controls, enforcement mechanisms and ongoing testing. OpenAI said some higher-risk requests may be delayed or blocked during the preview period.

The company said it devoted more than 700,000 A100-equivalent GPU hours to automated red-teaming, complemented by third-party expert testing, to evaluate the model’s resilience against jailbreak attempts.

During the preview, GPT-5.6 models will initially be available through the API and Codex to selected trusted partners and organisations. OpenAI said broader access for ChatGPT, Codex and API users is planned soon.

During the preview, GPT-5.6 models will be available through the API and Codex to selected partners. OpenAI said broader access across ChatGPT, Codex and the API is planned soon. It also announced pricing for the model family and said GPT-5.6 Sol will launch on Cerebras in July, initially for a limited group of customers.

Why does it matter?

GPT-5.6 Sol illustrates how frontier AI releases are becoming increasingly governed by phased deployment, targeted access and extensive safety testing rather than immediate public availability. OpenAI’s emphasis on cybersecurity evaluations, automated red-teaming and layered safeguards reflects growing efforts to manage the risks associated with increasingly capable foundation models.

The rollout also highlights the evolving relationship between AI companies and governments. By combining limited pre-release access, enterprise deployment and structured safety frameworks, OpenAI is helping shape emerging norms for how advanced AI systems are evaluated, governed and introduced into real-world use.

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Spain calls for stronger AI rules in labour relations

Spain’s Second Vice President and Minister of Labour and Social Economy, Yolanda Díaz, has called for stronger regulation of AI and algorithmic decision-making in the workplace.

Speaking at the University of Oxford, Díaz said the debate should no longer focus on whether AI should be used, but on how to organise its deployment so that labour rights and fundamental rights are protected.

She argued that AI and algorithms already influence recruitment, hiring, performance evaluation, promotion, contract changes, dismissals and pension-related decisions. According to Díaz, stronger oversight is needed to ensure transparency and accountability where algorithmic management affects workers.

Spain’s Rider Law was presented as an early example of algorithmic transparency in labour relations, requiring digital labour platforms to disclose information about algorithms that affect working conditions and access to work.

Díaz also criticised proposals to deregulate AI, arguing that technological development should serve the public good rather than concentrate power among a small number of technology companies.

Her intervention comes as the EU rules for high-risk AI systems in areas including employment are set to apply later than initially expected. The European Commission says these rules will apply from 2 December 2027 under the new AI Omnibus enforcement timeline.

Díaz said governments should actively shape how AI is used in the workplace through regulation and public policy, rather than leaving the future of work to market forces alone.

Why does it matter?

AI is increasingly used to manage recruitment, performance assessment, scheduling, promotion and dismissal decisions. Spain’s position places algorithmic transparency and worker rights at the centre of the European AI debate, especially as the EU’s employment-related high-risk AI obligations are delayed. The intervention also shows how member states may move ahead with stricter national rules when they believe EU-level protections are too slow or insufficient.

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Amazon announces $48 billion investment in India by 2030

Amazon has announced an additional $13 billion investment to expand AI and cloud infrastructure in India, bringing its planned investment in the country to $48 billion between 2026 and 2030.

The company said the new funding will expand AWS data centre capacity in Mumbai and Hyderabad, giving startups, enterprises and government organisations access to AI chips, managed AI services, cloud technologies and developer tools.

The announcement builds on a $35 billion investment across Amazon’s businesses in India announced in 2025. Amazon said its cumulative investments in India from 2010 to 2030 now stand at more than $88 billion.

Beyond AI and cloud infrastructure, Amazon said it will continue investing in its e-commerce and logistics network. The company plans to launch more than 20 new fulfilment centres and over 100 last-mile delivery stations across India this year, with a focus on faster deliveries in smaller cities.

Amazon said it has digitised 12 million small businesses in India, supported 2.8 million jobs, enabled more than $20 billion in cumulative e-commerce exports and trained more than 10 million people in cloud skills.

The company said its long-term priorities in India include AI-led digitisation, export growth and job creation.

Why does it matter?

Amazon’s investment highlights India’s growing role as a major market for AI infrastructure, cloud services and digital commerce. Expanding AWS capacity in Mumbai and Hyderabad could strengthen access to AI compute and cloud tools for businesses, startups and public-sector organisations. The announcement also shows how global technology companies are linking data centre investment with national priorities such as small-business digitisation, skills development, exports and job creation.

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Moldova tightens rules on AI in university theses

Moldova has approved a national framework regulation on academic integrity in higher education, introducing common rules on plagiarism, unauthorised use of AI and other forms of academic fraud.

The regulation, approved by the government and developed by the Ministry of Education and Research, sets a single framework that all higher education institutions in Moldova will be required to implement.

Under the new rules, students will have to declare whether they used AI in their academic work and explain how they used it. The ministry said the framework is intended to increase transparency and strengthen responsibility in the use of digital tools.

Acceptable AI use may include support functions such as proofreading, formatting or organising material, while core academic work, including analysis, interpretation and conclusions, must remain the student’s own intellectual contribution.

The regulation also classifies academic integrity violations by severity, with sanctions ranging from rewriting assignments to suspension or expulsion. Academic staff and supervisors may also face disciplinary measures if they fail to enforce integrity rules.

The framework forms part of Moldova’s wider effort to strengthen trust in higher education, including the planned use of a national anti-plagiarism system for bachelor’s and master’s theses.

Why does it matter?

Moldova’s rules show how universities are moving from informal guidance on generative AI towards enforceable academic integrity frameworks. Requiring students to disclose AI use can help distinguish between acceptable assistance and improper authorship, while preserving the value of independent analysis and critical thinking. The approach also reflects a wider education-policy challenge: institutions need to adapt assessment and integrity systems without banning useful digital tools entirely.

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OECD proposes policy priorities for AI use in SME sustainable finance

The Organisation for Economic Co-operation and Development (OECD) has published a policy paper examining how AI and digital tools can help small and medium-sized enterprises (SMEs) gain better access to sustainable finance, where they remain significantly underrepresented.

The paper maps practical applications of AI and digital tools across the entire financing lifecycle, from sustainability data generation and reporting by SMEs to loan origination, credit assessment and portfolio monitoring by financial institutions. The OECD notes that AI has the potential to support the front, middle and back office of lending operations rather than a single stage of the financing process.

Drawing on country examples and recent initiatives, the OECD argues that technological adoption must be accompanied by appropriate governance. It identifies four policy priorities: developing interoperable data infrastructure, strengthening verification mechanisms, creating incentives for SME sustainability reporting and ensuring accountable use of AI in financing decisions.

Why does it matter?

Small and medium-sized enterprises account for much of economic activity and employment but often struggle to access sustainable finance because they lack the resources to produce the data and reporting required by lenders and investors. AI could reduce these costs by automating data collection, reporting and credit assessment, making green finance more accessible to smaller businesses.

The OECD also emphasises that technology alone will not close the financing gap. Real progress depends on reliable data infrastructure, effective verification and clear governance to ensure AI-supported financing decisions are transparent, accountable and fair, preventing existing inequalities from being reinforced.

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UNESCO summit backs ethical AI governance in Latin America and the Caribbean

Representatives from more than 20 Latin American and Caribbean countries have met in Santo Domingo for a regional summit on AI ethics and governance.

The Third Ministerial and High-Level Authorities Summit on the Ethics of Artificial Intelligence in Latin America and the Caribbean took place on 25 and 26 June in the Dominican Republic. It was organised by UNESCO, the Dominican Republic’s Government Office of Information and Communication Technologies (OGTIC), and CAF – Development Bank of Latin America and the Caribbean.

The summit brought together ministers, senior government officials, multilateral organisations, academics, private-sector representatives and civil society to strengthen regional cooperation and accelerate the implementation of public policies aligned with the UNESCO Recommendation on the Ethics of Artificial Intelligence.

UNESCO said the meeting builds on earlier summits held in Santiago in 2023 and Montevideo in 2024, as well as ongoing work to develop a shared regional roadmap for responsible AI governance.

Anne Lemaistre, Director of the UNESCO Regional Office in Havana, said AI presents significant opportunities but also challenges that require coordinated regional action.

Raquel Peña, Vice President of the Dominican Republic, said the region had decided to come together to address one of the greatest challenges of the time. She said the task is to harness AI’s potential while upholding the principles that should guide its development and use.

Peña also reaffirmed the Dominican Republic’s commitment to a human-centred approach to AI. She said AI must be developed and governed with ethics, responsibility, and a profoundly human vision.

Christian Asinelli, Corporate Vice President of Strategic Programming at CAF, said Latin America and the Caribbean should play a stronger role in shaping global AI governance rather than simply adapting to international developments.

Raúl Fuentes, European Union Ambassador to the Dominican Republic, said the EU wants to work with the region on practical solutions as well as shared principles. He said the AI component of the EU-Latin America and the Caribbean Digital Alliance is supporting knowledge exchange, innovation, sovereignty, and a human-centred approach.

During the summit, Dominican authorities announced the forthcoming adoption of a national Artificial Intelligence Code of Ethics, developed with input from government, academia, civil society and the private sector, and aligned with international standards.

Edgar Batista, Director General of OGTIC, said the initiative reinforces the Dominican Republic’s commitment to digital transformation centred on public value. He said the country will contribute actively to the development of regional standards for digital governance.

Delegations are discussing AI governance, institutional capacity, responsible innovation, and regional cooperation. The talks aim to support ethical and regulatory frameworks for safe, inclusive, and trustworthy technological development.

The Dominican Republic will also assume the Pro Tempore Presidency of the regional mechanism, reinforcing its role in promoting ethical, inclusive and sustainable AI governance across Latin America and the Caribbean.

Why does it matter?

The summit reflects growing efforts by Latin American and Caribbean countries to develop a shared approach to AI governance based on ethics, inclusion and sustainable development. Regional cooperation can help governments build institutional capacity, align regulatory approaches and ensure AI policies reflect local priorities rather than relying solely on frameworks developed elsewhere.

The meeting also highlights the increasing importance of regional voices in global AI governance. By grounding discussions in UNESCO’s Recommendation on the Ethics of Artificial Intelligence and strengthening collaboration among governments, international organisations and other stakeholders, the region is seeking to play a more active role in shaping international norms for trustworthy AI.

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ECB highlights gap between AI adoption and productivity

Firms across the euro area are increasingly adopting AI, but only a small share are integrating it deeply enough to generate meaningful productivity gains. Data from the European Central Bank’s SAFE survey shows that although more than 70% of firms report using AI in some form, only 7% have integrated it deeply into their core operations.

Firms that use AI intensively are more likely to embed it in core business processes rather than limiting it to routine or experimental tasks. They are also more likely to innovate, expand their product offerings and align AI investments with long-term growth strategies.

Competitive pressure is also driving deeper AI adoption, particularly among established firms responding to technologically advanced rivals. However, skills shortages, legacy systems and financing constraints continue to limit many companies’ ability to scale AI effectively.

Why does it matter?

The findings suggest that simply adopting AI is not enough to generate significant economic benefits. Productivity gains appear to depend on integrating AI into core business functions, innovation strategies and long-term investment plans rather than using it only for isolated or experimental tasks.

The survey also highlights structural challenges facing Europe’s digital transformation. Without investment in skills, financing and modern digital infrastructure, many firms may struggle to move beyond basic AI adoption, potentially widening the productivity gap between AI leaders and businesses that lack the resources to scale the technology.

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Microsoft and Europol disrupt Amadey and StealC malware infrastructure

Microsoft has disrupted more than 200 command-and-control servers linked to Amadey and StealC, two widely used cybercrime tools that support credential theft, fraud and ransomware attacks.

The company’s Digital Crimes Unit said the action targeted the shared infrastructure behind the two tools rather than treating them as separate threats. In the first two weeks of May, Amadey and StealC were linked to more than 140,000 infected computers worldwide.

Amadey is often used to gain access to devices, while StealC is used to steal passwords and sensitive information. Microsoft said the tools form part of a wider cybercrime supply chain in which specialised malware services help attackers turn initial access into fraud, ransomware, espionage or other operations.

Microsoft said investigators used AI, including Copilot, to analyse malware and identify connections between the two tools more quickly. The company said the analysis helped its legal team treat both malware families as part of a single conspiracy under the US Racketeer Influenced and Corrupt Organizations Act.

The action was carried out with Europol and industry partners, including ESET, BitSight, Lumen and Mitsui Bussan Secure Directions. Europol’s European Cybercrime Centre also investigated StealC as part of Operation Endgame, alongside European law enforcement partners and cybersecurity companies, including IBM X-Force and Proofpoint.

Microsoft said it has identified more than 18,000 victim computers since the start of the operation and is working with telecommunications providers to help protect affected users.

The company said findings from the case will feed into its Statutory Automated Disruption programme, which accelerates the removal of malicious domains and infrastructure.

Why does it matter?

The operation reflects a shift in cybercrime disruption strategy. Instead of targeting one malware family or service at a time, Microsoft and its partners focused on the shared infrastructure that allows criminal tools to work together. That matters because modern cybercrime increasingly operates as a modular supply chain: one tool gains access, another steals credentials, and other actors monetise that access through fraud, ransomware or espionage. The use of AI to accelerate malware analysis also points to how defenders are trying to match the speed and scale of cybercriminal operations.

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Cate Blanchett unveils AI consent tool at European Parliament

Actor and producer Cate Blanchett has launched the Human Consent Registry, a free online tool that allows individuals to specify how AI systems may use their identity. Presented at the European Parliament, the registry enables users to permit or prohibit the use of their name, image, voice, likeness and movements by AI systems, either unconditionally or subject to specific terms.

The platform is available to individuals as well as representatives, such as agents and managers. Its developers say it will eventually expand to cover works of art, fictional characters and brands. It was developed by RSL Media, a nonprofit co-founded by Blanchett that focuses on building consent tools related to AI use, which launched in May to wide support from figures across the entertainment industry.

Blanchett has been a prominent advocate for stronger safeguards against unauthorised AI use. In March 2025, she joined more than 400 artists in signing an open letter urging the US administration to maintain copyright protections and reject proposals that would allow AI developers to train models on copyrighted works without permission or compensation.

The launch comes amid growing concern among artists over the unauthorised use of creative works and personal likenesses for AI training. Singer SZA recently said more than 200 of her songs had been used to train AI systems, while actor Matthew McConaughey has trademarked his image, voice and a well-known catchphrase.

The Human Consent Registry positions itself as a scalable and accessible alternative to such individual legal measures, offering a standardised mechanism that does not require significant resources to deploy. The tool is free to use and designed to be available to anyone, not only those with the means to pursue trademark or copyright protections independently.

The registry was launched during an event at the European Parliament hosted by Bulgarian MEP Eva Maydell of the European People’s Party. Director Steven Soderbergh also attended the event in Brussels.

Why does it matter?

The Human Consent Registry highlights a growing gap between existing intellectual property laws and the capabilities of generative AI. While copyright and trademark protections offer some legal remedies, they often do not provide individuals with a simple way to express or enforce consent over the use of their identity, voice or likeness by AI systems.

The initiative also reflects a broader shift towards consent-based AI governance. By launching the registry at the European Parliament, its creators are seeking to influence ongoing debates on AI regulation, copyright and personality rights, while promoting practical mechanisms that could complement future legal frameworks for the responsible use of AI-generated content.

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NIST explores OT asset management to strengthen cybersecurity

NIST’s National Cybersecurity Center of Excellence (NCCoE) is seeking public feedback on a new project focused on operational technology (OT) asset management as the foundation for stronger OT cybersecurity.

The draft project description, Asset Management as a Foundation for OT Cybersecurity, outlines the project’s scope, challenges and technical approach. The NCCoE plans to demonstrate practical methods for OT asset discovery, inventory, configuration and change management.

The project will involve collaboration with asset owners, operators, and solution providers. The NCCoE plans to demonstrate real-world OT asset management and visibility solutions using commercially available products.

The proposal also includes a high-level reference architecture, desired technical capabilities and alignment with relevant standards, including outcomes from the NIST Cybersecurity Framework 2.0.

The NCCoE said AI is accelerating both the discovery and exploitation of vulnerabilities, making strong OT asset management increasingly important as organisations modernise industrial systems, adopt zero trust architectures and respond to AI-driven cyber threats.

Many organisations struggle to maintain a complete inventory of OT assets. Without effective asset management, activities such as risk assessment, network segmentation, vulnerability management, incident response and technology modernisation become significantly more difficult.

The NCCoE said the laboratory demonstration will support the development of source code, scripts, architectures, procedures, and guidelines. These resources are intended to help organisations gain the visibility needed to detect and respond to modern cyber threats in OT environments.

The centre is seeking input from asset owners, operators, technology providers, and cybersecurity practitioners. Feedback will help refine the project scope, use cases, reference architecture, and demonstration objectives.

Following the consultation, the NCCoE plans to recruit collaborators for project demonstrations and development activities. Public comments on the draft are open until 31 July 2026.

Why does it matter?

Operational technology underpins critical infrastructure, manufacturing and industrial operations, making accurate asset visibility a prerequisite for effective cybersecurity. As AI enables attackers to identify and exploit vulnerabilities more quickly, organisations need reliable inventories, configuration management and continuous monitoring to support risk assessments, zero trust strategies and incident response.

The project also reflects a broader shift towards practical cybersecurity guidance. By working with industry to develop reference architectures, tools and implementation guidance aligned with the NIST Cybersecurity Framework 2.0, the NCCoE aims to help organisations translate cybersecurity best practices into operational improvements across industrial environments.

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