As Chinese skater Sun Long stood on the Milan-Cortina Winter Olympics podium, the vivid red of his uniform reflected more than national pride. It also highlighted AI’s expanding role in China’s textile manufacturing.
In Shaoxing, AI-powered image systems calibrate fabric colours in real time. Factory managers say digital printing has lifted pass rates from about 50% to above 90%, easing longstanding production bottlenecks.
Tyre manufacturing firm Zhongce Rubber Group uses AI to generate multiple 3D designs in minutes. Engineers report shorter development cycles and reduced manual input across research and testing.
Electric vehicle maker Zeekr uses AI visual inspection in its 5G-enabled factory. Officials say tyre verification now takes seconds, helping eliminate assembly errors.
Provincial authorities in China report that large industrial firms are fully digitalized. Zhejiang plans to further integrate AI by 2027, expanding smart factories and industrial intelligence.
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ByteDance is facing scrutiny from Hollywood organisations over its AI video generator Seedance 2.0. Industry groups allege the system uses actors’ likenesses and copyrighted material without permission.
The Motion Picture Association said the tool reflects large-scale unauthorised use of protected works. Chairman Charles Rivkin called on ByteDance to halt what he described as infringing activities that undermine creators’ rights and jobs.
SAG-AFTRA also criticised the platform, citing concerns over the use of members’ voices and images. Screenwriter Rhett Reese warned that rapid AI development could reshape opportunities for creative professionals.
ByteDance acknowledged the concerns and said it would strengthen safeguards to prevent misuse of intellectual property. The company reiterated its commitment to respecting copyright while addressing complaints.
The dispute underscores wider tensions between technological innovation and rights protection as generative AI tools expand. Legal experts say the outcome could influence how AI video systems operate within existing copyright frameworks.
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A Pakistani American surgeon has launched what is described as the UAE’s first AI clinical intelligence platform across the country’s public healthcare system. The rollout was announced in Dubai in partnership with Emirates Health Services.
Boston Health AI, founded by Dr Adil Haider, introduced the platform known as Amal at a major health expo in Dubai. The system conducts structured medical interviews in Arabic, English and Urdu before consultations, generating summaries for physicians.
The company said the technology aims to reduce documentation burdens and cognitive load on clinicians in the UAE. By organising patient histories and symptoms in advance, Amal is designed to support clinical decision making and improve workflow efficiency in Dubai and other emirates.
Before entering the UAE market, Boston Health AI deployed its platform in Pakistan across more than 50 healthcare facilities. The firm states that over 30,000 patient interactions were recorded in Pakistan, where a local team continues to develop and refine the AI system.
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Quebec’s financial regulator has opened a review into how AI tools are being used to collect consumer debt across the province. The Autorité des marchés financiers is examining whether automated systems comply with governance, privacy and fairness standards in Quebec.
Draft guidelines released in 2025 require institutions in Quebec to maintain registries of AI systems, conduct bias testing and ensure human oversight. Public consultations closed in November, with regulators stressing that automation must remain explainable and accountable.
Many debt collection platforms now rely on predictive analytics to tailor the timing, tone and frequency of messages sent to borrowers in Quebec. Regulators are assessing whether such personalisation risks undue pressure or opaque decision making.
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AI adoption is prompting UK scale-ups to recalibrate workforce policies. Survey data indicates that 33% of founders anticipate job cuts within the next year, while 58% are already delaying or scaling back recruitment as automation expands. The prevailing approach centres on cautious workforce management rather than immediate restructuring.
Instead of large-scale redundancies, many firms are prioritising hiring freezes and reduced vacancy postings. This policy choice allows companies to contain costs and integrate AI gradually, limiting workforce growth while assessing long-term operational needs.
The trend aligns with broader labour market caution in the UK, where vacancies have cooled amid rising business costs and technological transition. Globally, the technology sector has experienced significant layoffs in 2026, reinforcing concerns about how AI-driven efficiency strategies are reshaping employment models.
At the same time, workforce readiness remains a structural policy challenge. Only a small proportion of founders consider the UK workforce prepared for widespread AI adoption, underscoring calls for stronger investment in skills development and reskilling frameworks as automation capabilities advance.
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A document released by the Republican-led House Judiciary Committee revived claims that the EU digital rules amount to censorship. The document concerns a €120 million fine against X under the Digital Services Act and was framed as a ‘secret censorship ruling’, despite publication requirements.
The document provides insight into how the European Commission interprets Article 40 of the DSA, which governs researcher access to platform data. The rule requires huge online platforms to grant qualified researchers access to publicly accessible data needed to study systemic risks in the EU.
Investigators found that X failed to comply with Article 40.12, in force since 2023 and covering public data access. The Commission said X applied restrictive eligibility rules, delayed reviews, imposed tight quotas, and blocked independent researcher access, including scraping.
The decision confirms platforms cannot price access to restrict research, deny access based on affiliation or location, or ban scraping by contract. The European Commission also rejected X’s narrow reading of ‘systemic risk’, allowing broader research contexts.
The ruling also highlights weak internal processes and limited staffing for handling access requests. X must submit an action plan by mid-April 2026, with the decision expected to shape future enforcement of researcher access across major platforms.
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Mortgage lenders face growing pressure to govern AI as regulatory uncertainty persists across the United States. States and federal authorities continue to contest oversight, but accountability for how AI is used in underwriting, servicing, marketing, and fraud detection already rests with lenders.
Effective AI risk management requires more than policy statements. Mortgage lenders need operational governance that inventories AI tools, documents training data, and assigns accountability for outcomes, including bias monitoring and escalation when AI affects borrower eligibility, pricing, or disclosures.
Vendor risk has become a central exposure. Many technology contracts predate AI scrutiny and lack provisions on audit rights, explainability, and data controls, leaving lenders responsible when third-party models fail regulatory tests or transparency expectations.
Leading US mortgage lenders are using staged deployments, starting with lower-risk use cases such as document processing and fraud detection, while maintaining human oversight for high-impact decisions. Incremental rollouts generate performance and fairness evidence that regulators increasingly expect.
Regulatory pressure is rising as states advance AI rules and federal authorities signal the development of national standards. Even as boundaries are debated, lenders remain accountable, making early governance and disciplined scaling essential.
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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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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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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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