AI and quantum computing reshape the global cybersecurity landscape

Cybersecurity risks are increasing as digital connectivity expands across governments, businesses and households.

According to Thales Group, a growing number of connected devices and digital services has significantly expanded the potential entry points for cyberattacks.

AI is reshaping the cybersecurity landscape by enabling attackers to identify vulnerabilities at unprecedented speed.

Security specialists increasingly describe the environment as a contest in which defensive systems must deploy AI to counter adversaries using similar technologies to exploit weaknesses in digital infrastructure.

Security concerns also extend beyond large institutions. Connected devices in homes, including smart cameras and speakers, often lack robust security protections, increasing exposure for individuals and networks.

Policymakers in Europe are responding through measures such as the Cyber Resilience Act, which will introduce mandatory security requirements for connected products sold in the EU.

Long-term risks are also emerging from advances in quantum computing.

Experts warn that powerful future machines could eventually break widely used encryption systems that currently protect communications, financial data and government networks, prompting organisations to adopt quantum-resistant security methods.

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EU updates voluntary code for labelling AI-generated content

The European Commission has released a second draft of its voluntary Code of Practice on marking and labelling AI-generated content, designed to support compliance with transparency rules under the Artificial Intelligence Act.

Published on 5 March, the updated draft reflects feedback from hundreds of stakeholders, including industry groups, academic researchers, policymakers, and civil society organisations.

Revisions follow consultations held in early 2026 as part of the broader rollout of the EU’s AI regulatory framework.

The proposed code outlines technical approaches for identifying AI-generated material. A two-layered system using secure metadata and digital watermarking is recommended, with optional fingerprinting, logging, and verification to improve detection.

Guidelines also address how platforms and publishers should label deepfakes and AI-generated text related to matters of public interest. Public feedback is open until 30 March, with the final code expected in early June before transparency rules take effect on 2 August 2026.

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EU lawmakers call for stronger copyright safeguards in AI training

The European Parliament has adopted a report urging policymakers to establish a long-term framework protecting copyrighted works used in AI training.

These recommendations aim to ensure that creative industries retain transparency and fair treatment as generative AI technologies expand.

Among the central proposals is the creation of a European register managed by the European Union Intellectual Property Office. The database would list copyrighted works used to train AI systems and identify creators who have chosen to exclude their content from such use.

Lawmakers in the EU are also calling for greater transparency from AI developers, including disclosure of the websites from which training data has been collected. According to the report, failing to meet transparency requirements could raise questions about compliance with existing copyright rules.

The recommendations have received mixed reactions from industry stakeholders.

Organisations representing creators argue that stronger safeguards are necessary to ensure fair remuneration and legal clarity, while technology sector groups caution that additional requirements could create complexity for companies developing AI systems.

The report is not legally binding but signals the political direction of ongoing European discussions on copyright and AI governance.

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MIT scientists develop AI system to improve robot planning

Researchers at MIT have developed a hybrid AI framework designed to improve how robots plan and perform complex visual tasks. The approach combines generative AI with classical planning software, allowing machines to analyse images, simulate actions, and generate reliable plans to reach a goal.

The system relies on two specialised vision-language models. One model analyses an image, describes the environment, and simulates possible actions, while a second model converts those simulations into a formal programming language used for planning.

Generated files are then processed by established planning software to produce a step-by-step strategy.

Testing showed a significant improvement compared with existing techniques. The framework achieved an average success rate of about 70 percent, while many baseline methods reached roughly 30 percent.

Performance remained strong in unfamiliar scenarios, demonstrating the system’s ability to adapt to changing conditions.

The method could support applications such as robot navigation, autonomous driving, and multi-robot assembly systems. Continued development aims to handle more complex environments and reduce errors caused by AI model hallucinations.

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Dutch firms rank among EU leaders in sustainable ICT

Businesses in the Netherlands rank among the leading adopters of sustainable ICT practices in the EU, according to data from Statistics Netherlands and Eurostat. Around one quarter of companies use digital tools to reduce material consumption and improve resource efficiency.

The Netherlands ranked fourth in the EU for the use of technology to reduce waste and improve sustainability. Sectors including energy, water and waste management showed the strongest adoption of these ICT solutions.

Sustainable disposal of electronic equipment is also widespread among businesses in the Netherlands. About 9 in 10 companies recycle or return obsolete ICT equipment through approved e-waste collection systems.

Across the EU, more than three-quarters of businesses now dispose of outdated technology in environmentally responsible ways. Analysts say progress highlights growing corporate efforts to integrate the sustainability of e-waste into digital operations.

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Writers publish protest book to challenge AI use of copyrighted works

Thousands of writers have joined a symbolic protest against AI companies by publishing a book that contains no traditional content.

The work, titled “Don’t Steal This Book,” lists only the names of roughly 10,000 contributors who oppose the use of their writing to train AI systems without their permission.

An initiative that was organised by composer and campaigner Ed Newton-Rex and distributed during the London Book Fair. Contributors include prominent authors such as Kazuo Ishiguro, Philippa Gregory and Richard Osman, along with thousands of other writers and creative professionals.

Campaigners argue that generative AI systems are trained on vast collections of copyrighted material gathered from the internet without authorisation or compensation.

According to organisers, such practices allow AI tools to compete with the creators whose works were used to develop them.

The protest arrives as the UK Government prepares an economic assessment of potential copyright reforms related to AI. Proposals under discussion include allowing AI developers to use copyrighted material unless rights holders explicitly opt out.

Many writers and artists oppose that approach and demand stronger copyright protections. In parallel, the publishing sector is preparing a licensing initiative through Publishers’ Licensing Services to provide AI developers with legal access to books while ensuring authors receive compensation.

The dispute reflects a growing global debate over how copyright law should apply to generative AI systems that rely on massive datasets to develop chatbots and other digital tools.

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AI agents platform NemoClaw targets enterprise tools in Nvidia strategy

Nvidia is reportedly preparing to launch an open-source platform for AI agents, according to sources familiar with the company’s plans.

The platform, internally known as NemoClaw, is being pitched to enterprise software companies and would enable businesses to deploy AI agents to perform tasks for employees. Companies will be able to access the platform regardless of whether their products run on Nvidia hardware.

The initiative comes ahead of Nvidia’s annual developer conference in San Jose next week. The company has reportedly approached firms including Salesforce, Cisco, Google, Adobe, and CrowdStrike to explore potential partnerships for the platform. However, it remains unclear whether any formal agreements have been reached.

Sources say the open-source platform could offer early access to partners in exchange for contributions to the project, while also including built-in security and privacy tools designed for enterprise environments. Interest in the project reflects enthusiasm around open-source AI ‘claws,’ agents that run locally and autonomously handle multi-step tasks with less human oversight.

However, the use of autonomous agents in corporate environments remains controversial. Some technology companies have reportedly restricted their use on work devices due to concerns about unpredictability and security risks.

For Nvidia, NemoClaw may also represent a broader effort to expand its influence beyond hardware. By supporting open-source AI agents, the company could strengthen its position in enterprise AI infrastructure, even as several major AI developers are building their own chips.

NVIDIA has not publicly commented on the reported plans. Representatives from several companies linked to the project also declined to comment.

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AI-driven education push reshapes Chungnam National University strategy

Chungnam National University aims to become a leading centre for AI-driven education in Korea as AI reshapes how universities teach, learn, and manage operations. University President Kim Jeong-kyoum said higher education institutions must rethink how they approach AI and prepare for the profound changes AI-driven education is expected to bring across society.

‘AI will undoubtedly bring significant changes across industries and in our daily lives,’ Kim told The Korea Times in a recent interview. ‘Universities need to approach this shift with an open mindset and be ready to accept it. I want Chungnam National University to become a university that uses AI better than anyone else.’

While acknowledging that the phrase ‘AI-leading university’ is increasingly common, Kim said the university’s real priority is integrating AI into teaching practically. The institution is considering incorporating AI-related elements into more than 30 percent of its curriculum to ensure students gain hands-on experience with the technology and support the expansion of AI-driven education across disciplines.

‘We want to teach students how to use AI effectively in practice,’ he said. ‘Professors need to use and understand AI themselves to teach it properly, and students also need systematic training on how to use these tools well.’

Beyond the classroom, the university also plans to introduce AI into administrative systems to improve campus operations. ‘Administration is often the hardest part of a university to change,’ Kim said. ‘That’s why we believe introducing AI into administrative systems first could be particularly meaningful.’

The university is also expanding research through its Glocal Lab project, which aims to strengthen Chungnam National University’s role in AI-driven pharmaceutical and biotechnology research. The initiative is expected to more directly connect academic research with industry and support the development of specialised talent, strengthening the university’s broader ambitions in AI-driven education and innovation.

Kim said, ‘Until now, there have been clear limits to translating the university’s strong basic research into applications in local industries. We expect the Glocal Lab project to help bridge that gap by connecting academic research more directly with the industrial field.’

The project will integrate AI, mathematical sciences, and pharmaceutical and biotechnology research into a unified R&D platform. ‘Ultimately, the Glocal Lab project will help the university grow into a global R&D hub,’ Kim said. ‘By creating high-quality jobs locally, it can also help curb the outflow of talented young people to the Seoul metropolitan area and foster a virtuous cycle of regional settlement and innovation.’

The university is also enhancing internationalisation efforts, aiming to increase the share of international students to 10 percent while expanding global partnerships and strengthening its global profile in AI-driven education. ‘Universities should take the lead in presenting new models in a global society,’ Kim said. ‘By doing so, these ideas can spread beyond campus and ultimately influence local industries and businesses.’

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Energy Infrastructure faces critical challenges in Africa’s digital future

Energy infrastructure is becoming a key foundation for Africa’s digital transformation. The rapid expansion of AI, cloud computing, and digital services is increasing electricity demand. Reliable and scalable power systems are therefore essential to support the growth of the continent’s digital economy.

Governments are integrating digital development into national policy strategies. Initiatives such as the New Deal Technologique Horizon 2034 in Senegal and Digital Ethiopia 2030 in Ethiopia prioritise digital infrastructure, data centres, and cloud services. However, these strategies require stronger alignment with energy planning.

Energy systems need modernisation to support data centres and AI infrastructure. Traditional power models are not designed for the high and rapidly growing energy demands of digital technologies. Expanding renewable energy, storage systems, and smart energy management can improve reliability and efficiency.

Data centres are increasingly viewed as strategic infrastructure. As central hubs of the digital economy, they require stable electricity supply, efficient cooling systems, and resilient energy management to support computing services and digital platforms.

Modular and energy-efficient infrastructure can accelerate digital deployment. Scalable power systems, modular data centres, and advanced energy storage can reduce deployment time and operational costs while supporting expanding digital services.

Collaboration across sectors is necessary to support sustainable digital growth. Governments, utilities, enterprises, and technology providers need to coordinate policies and investments to align digital transformation with energy transition efforts.

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