Development

AI anxiety strains the modern workforce

Mounting anxiety is reshaping the modern workplace as AI alters job expectations and career paths. Pew Research indicates more than a third of employees believe AI could harm their prospects, fuelling tension across teams.

Younger workers feel particular strain, with 92% of Gen Z saying it is vital to speak openly about mental health at work. Communicators and managers must now deliver reassurance while coping with their own pressure.

Leadership expert Anna Liotta points to generational intelligence as a practical way to reduce friction and improve trust. She highlights how tailored communication can reduce misunderstanding and conflict.

Her latest research connects neuroscience, including the role of the vagus nerve, with practical workplace strategies. By combining emotional regulation with thoughtful messaging, she suggests that organisations can calm anxiety and build more resilient teams.

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Government AI investment grows while public trust falters

Rising investment in AI is reshaping public services worldwide, yet citizen satisfaction remains uneven. Research across 14 countries shows that nearly 45% of residents believe digital government services still require improvement.

Employee confidence is also weakening, with empowerment falling from 87% three years ago to 73% today. Only 35% of public bodies provide structured upskilling for AI-enabled roles, limiting workforce readiness.

Trust remains a growing concern for public authorities adopting AI. Only 47% of residents say they believe their government will use AI responsibly, exposing a persistent credibility gap.

The study highlights an ‘experience paradox’, in which the automation of legacy systems outpaces meaningful service redesign. Leading nations such as the UAE, Saudi Arabia and Singapore rank highly for proactive AI strategies, but researchers argue that leadership vision and structural reform, not funding alone, determine long-term credibility.

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India’s AI market set to surge to over $130 billion by 2032

The AI market in India has expanded from roughly $2.97 billion in 2020 to $7.63 billion in 2024, and is projected to reach $131.31 billion by 2032 at a compound annual growth rate (CAGR) of about 42.2 percent.

The growth outlook is underpinned by systematic progress across five layers of AI architecture, encompassing models, applications, chips, infrastructure and energy, with strong foundational infrastructure such as data centres and widespread internet connectivity enabling cloud adoption and data-driven services across sectors.

India’s acceleration in AI adoption aligns with broader digital trends and policy pushes, with readiness indices and talent penetration indicating that the nation is better positioned than many emerging economies to scale AI across industries.

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Half of xAI’s founding team has now left the company

Departures from Elon Musk’s AI startup xAI have reached a symbolic milestone, with two more co-founders announcing exits within days of each other. Yuhuai Tony Wu and Jimmy Ba both confirmed their decisions publicly, marking a turning point for the company’s leadership.

Losses now total six out of the original 12 founding members, signalling significant turnover in less than three years. Several prominent researchers had already moved on to competitors, launched new ventures, or stepped away for personal reasons.

Timing coincides with major developments, including SpaceX’s acquisition of xAI and preparations for a potential public listing. Financial opportunities and intense demand for AI expertise are encouraging senior talent to pursue independent projects or new roles.

Challenges surrounding the Grok chatbot, including technical issues and controversy over its harmful content, have added internal pressure. Growing competition from OpenAI and Anthropic means retaining skilled researchers will be vital to sustaining investor confidence and future growth.

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Northumbria graduate uses AI to revolutionise cardiovascular diagnosis

Jack Parker, a Northumbria University alumnus and CEO/co-founder of AIATELLA, is leading a pioneering effort to speed up cardiovascular disease diagnosis using artificial intelligence, cutting diagnostic times from over 30 minutes to under 3 minutes, a potential lifesaver in clinical settings.

His motivation stems from witnessing delays in diagnosis that affected his own father, as well as broader health disparities in the North East, where cardiovascular issues often go undetected until later stages.

Parker’s company, now UK-Finnish, is undergoing clinical evaluation with three NHS trusts in the North East (Northumbria, Newcastle, Sunderland), comparing the AI tool’s performance against cardiologists and radiologists.

The technology has already helped identify individuals needing urgent intervention while working with community organisations in the UK and Finland.

Parker credits Northumbria University’s practical and inclusive education pathway, including a foundation degree and biomedical science degree, with providing the grounding to translate academic knowledge into real-world impact.

Support from the university’s Incubator Hub also helped AIATELLA navigate early business development and access funding networks.

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AI drives bold transformation in the East African Community

The East African Community (EAC) is positioning AI as a strategic instrument to address long-standing structural inefficiencies. Rather than viewing AI as a technological trend, the bloc increasingly recognises it as central to strengthening governance, accelerating regional integration, and enhancing economic competitiveness.

The region faces persistent challenges, including slow customs clearance, fragmented data systems, weak coordination, and revenue leakages. AI-powered systems could streamline procedures, improve data management, and strengthen oversight to reduce corruption and delays.

Beyond trade facilitation, AI has implications for public financial management and service delivery. Machine learning tools can detect procurement anomalies, identify irregular payments, and strengthen auditing systems. Such applications could enhance fiscal stability, transparency, and public trust across member states.

However, East Africa’s AI adoption remains constrained by limited computing infrastructure, skills shortages, and fragmented regulatory frameworks. Without harmonised governance standards, reliable data infrastructure, and sustained investment in capacity-building, AI initiatives risk remaining isolated and underutilised.

The upcoming regional AI conference in Kigali signals high-level political recognition of AI’s transformative potential. It is expected to advance discussions on policy coordination, ethical frameworks, and the development of a shared regional strategy.

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Institute of AI Education marks significant step for responsible AI in schools

The Institute of AI Education was officially launched at York St John University, bringing together education leaders, teachers, and researchers to explore practical and responsible approaches to AI in schools.

Discussions at the event focused on critical challenges, including fostering AI literacy, promoting fairness and inclusion, and empowering teachers and students to have agency over how AI tools are used.

The institute will serve as a collaborative hub, offering research-based guidance, professional development, and practical support to schools. A central message emphasised that AI should enhance the work of educators and learners, rather than replace them.

The launch featured interactive sessions with contributions from both education and technology leaders, as well as practitioners sharing real-world experiences of integrating AI into classrooms.

Strong attendance and active participation underscored the growing interest in AI across the education sector, with representatives from the Department for Education highlighting notable progress in early years and primary school settings.

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Hybrid AI could reshape robotics and defence

Investors and researchers are increasingly arguing that the future of AI lies beyond large language models. In London and across Europe, startups are developing so-called world models designed to simulate physical reality rather than simply predict text.

Unlike LLMs, which rely on static datasets, world models aim to build internal representations of cause and effect. Advocates say these systems are better suited to autonomous vehicles, robotics, defence and industrial simulation.

London based Stanhope AI is among companies pursuing this approach, claiming its systems learn by inference and continuously update their internal maps. The company is reportedly working with European governments and aerospace firms on AI drone applications.

Supporters argue that safety and explainability must be embedded from the outset, particularly under frameworks such as the EU AI Act. Investors suggest that hybrid systems combining LLMs with physics aware models could unlock large commercial markets across Europe.

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Researchers tackle LLM regression with on policy training

Researchers at MIT, the Improbable AI Lab and ETH Zurich have proposed a fine tuning method to address catastrophic forgetting in large language models. The issue often causes models to lose earlier skills when trained on new tasks.

The technique, called self distillation fine tuning, allows a model to act as both teacher and student during training. In Cambridge and Zurich experiments, the approach preserved prior capabilities while improving accuracy on new tasks.

Enterprise teams often manage separate model variants to prevent regression, increasing operational complexity. The researchers argue that their method could reduce fragmentation and support continual learning, useful for AI, within a single production model.

However, the method requires around 2.5 times more computing power than standard supervised fine tuning. Analysts note that real world deployment will depend on governance controls, training costs and suitability for regulated industries.

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Latam-GPT signals new AI ambition in Latin America

Chile has introduced Latam-GPT to strengthen Latin America’s presence in global AI.

The project, developed by the National Centre for Artificial Intelligence with support across South America, aims to correct long-standing biases by training systems on the region’s own data instead of material drawn mainly from the US or Europe.

President Gabriel Boric said the model will help maintain cultural identity and allow the region to take a more active role in technological development.

Latam-GPT is not designed as a conversational tool but rather as a vast dataset that serves as the foundation for future applications. More than eight terabytes of information have been collected, mainly in Spanish and Portuguese, with plans to add indigenous languages as the project expands.

The first version has been trained on Amazon Web Services. At the same time, future work will run on a new supercomputer at the University of Tarapacá, supported by millions of dollars in regional funding.

The model reflects growing interest among countries outside the major AI hubs of the US, China and Europe in developing their own technology instead of relying on foreign systems.

Researchers in Chile argue that global models often include Latin American data in tiny proportions, which can limit accurate representation. Despite questions about resources and scale, supporters believe Latam-GPT can deliver practical benefits tailored to local needs.

Early adoption is already underway, with the Chilean firm Digevo preparing customer service tools based on the model.

These systems will operate in regional languages and recognise local expressions, offering a more natural experience than products trained on data from other parts of the world.

Developers say the approach could reduce bias and promote more inclusive AI across the continent.

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