Sustainable development

SAP elevates customer support with proactive AI systems

AI has pushed customer support into a new era, where anticipation replaces reaction. SAP has built a proactive model that predicts issues, prevents failures and keeps critical systems running smoothly instead of relying on queues and manual intervention.

Major sales events, such as Cyber Week and Singles Day, demonstrated the impact of this shift, with uninterrupted service and significant growth in transaction volumes and order numbers.

Self-service now resolves most issues before they reach an engineer, as structured knowledge supports AI agents that respond instantly with a confidence level that matches human performance.

Tools such as the Auto Response Agent and Incident Solution Matching enable customers to retrieve solutions without having to search through lengthy documentation.

SAP has also prepared organisations scaling AI by offering support systems tailored for early deployment.

Engineers have benefited from AI as much as customers. Routine tasks are handled automatically, allowing experts to focus on problems that demand insight instead of administration.

Language optimisation, routing suggestions, and automatic error categorisation support faster and more accurate resolutions. SAP validates every AI tool internally before release, which it views as a safeguard for responsible adoption.

The company maintains that AI will augment staff rather than replace them. Creative and analytical work becomes increasingly important as automation handles repetitive tasks, and new roles emerge in areas such as AI training and data stewardship.

SAP argues that progress relies on a balanced relationship between human judgement and machine intelligence, strengthened by partnerships that turn enterprise data into measurable outcomes.

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Canada sets national guidelines for equitable AI

Yesterday, Canada released the CAN-ASC-6.2 – Accessible and Equitable Artificial Intelligence Systems standard, marking the first national standard focused specifically on accessible AI.

A framework that ensures AI systems are inclusive, fair, and accessible from design through deployment. Its release coincides with the International Day of Persons with Disabilities, emphasising Canada’s commitment to accessibility and inclusion.

The standard guides organisations and developers in creating AI that accommodates people with disabilities, promotes fairness, prevents exclusion, and maintains accessibility throughout the AI lifecycle.

It provides practical processes for equity in AI development and encourages education on accessible AI practices.

The standard was developed by a technical committee composed largely of people with disabilities and members of equity-deserving groups, incorporating public feedback from Canadians of diverse backgrounds.

Approved by the Standards Council of Canada, CAN-ASC-6.2 meets national requirements for standards development and aligns with international best practices.

Moreover, the standard is available for free in both official languages and accessible formats, including plain language, American Sign Language and Langue des signes québécoise.

By setting clear guidelines, Canada aims to ensure AI serves all citizens equitably and strengthens workforce inclusion, societal participation, and technological fairness.

An initiative that highlights Canada’s leadership in accessible technology and provides a practical tool for organisations to implement inclusive AI systems.

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Uzbekistan sets principles for responsible AI

A new ethical framework for the development and use of AI technologies has been adopted by Uzbekistan.

The rules, prepared by the Ministry of Digital Technologies, establish unified standards for developers, implementing organisations and users of AI systems, ensuring AI respects human rights, privacy and societal trust.

A framework that is part of presidential decrees and resolutions aimed at advancing AI innovation across the country. It also emphasises legality, transparency, fairness, accountability, and continuous human oversight.

AI systems must avoid discrimination based on gender, nationality, religion, language or social origin.

Developers are required to ensure algorithmic clarity, assess risks and bias in advance, and prevent AI from causing harm to individuals, society, the state or the environment.

Users of AI systems must comply with legislation, safeguard personal data, and operate technologies responsibly. Any harm caused during AI development or deployment carries legal liability.

The Ministry of Digital Technologies will oversee standards, address ethical concerns, foster industry cooperation, and improve digital literacy across Uzbekistan.

An initiative that aligns with broader efforts to prepare Uzbekistan for AI adoption in healthcare, education, transport, space, and other sectors.

By establishing clear ethical principles, the country aims to strengthen trust in AI applications and ensure responsible and secure use nationwide.

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UNESCO launches AI guidelines for courts and tribunals

UNESCO has launched new Guidelines for the Use of AI Systems in Courts and Tribunals to ensure AI strengthens rather than undermines human-led justice. The initiative arrives as courts worldwide face millions of pending cases and limited resources.

In Argentina, AI-assisted legal tools have increased case processing by nearly 300%, while automated transcription in Egypt is improving court efficiency.

Judicial systems are increasingly encountering AI-generated evidence, AI-assisted sentencing, and automated administrative processes. AI misuse can have serious consequences, as seen in the UK High Court where false AI-generated arguments caused delays, extra costs, and fines.

UNESCO’s Guidelines aim to prevent such risks by emphasising human oversight, auditability, and ethical AI use.

The Guidelines outline 15 principles and provide recommendations for judicial organisations and individual judges throughout the AI lifecycle. They also serve as a benchmark for developing national and regional standards.

UNESCO’s Judges’ Initiative, which has trained over 36,000 judicial operators in 160 countries, played a key role in shaping and peer-reviewing the Guidelines.

The official launch will take place at the Athens Roundtable on AI and the Rule of Law in London on 4 December 2025. UNESCO aims for the standards to ensure responsible AI use, improve court efficiency, and uphold public trust in the judiciary.

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FCA launches AI Live Testing for UK financial firms

The UK’s Financial Conduct Authority has launched an AI Live Testing initiative to help firms safely deploy AI in financial markets. Major companies, including NatWest, Monzo, Santander, Scottish Widows, Gain Credit, Homeprotect, and Snorkl, are participating in the first cohort.

Firms receive tailored guidance from the FCA and its technical partner, Advai, to develop and assess AI applications responsibly.

AI testing focuses on retail financial services, exploring uses such as debt resolution, financial advice, improving customer engagement, streamlining complaints handling, and supporting smarter spending and saving decisions.

The project aims to answer key questions around evaluation frameworks, governance, live monitoring, and risk management to protect both consumers and markets.

Jessica Rusu, FCA chief data officer, said the initiative helps firms use AI safely while guiding the FCA on its impact in UK financial services. The project complements the FCA’s Supercharged Sandbox, which supports firms in earlier experimentation phases.

Applications for the second AI Live Testing cohort open in January 2026, with participating firms able to start testing in April. Insights from the initiative will inform FCA AI policy, supporting innovation while ensuring responsible deployment.

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Texas makes historic investment with $5 million Bitcoin purchase

Texas has become the first US state to fund a strategic cryptocurrency reserve, purchasing approximately $5 million in Bitcoin through BlackRock’s iShares Bitcoin Trust ETF.

The move follows Governor Greg Abbott signing Senate Bill 21, allowing the comptroller’s office to create a public crypto reserve. states, such as New Hampshire and Arizona, have passed similar bills, but Texas is the first to execute an actual purchase.

The ETF acquisition acts as a temporary measure while the state finalises a contract with a cryptocurrency custodian. Comptroller representatives called the purchase a ‘placeholder investment’ while reviewing bids for a permanent custodian.

Lawmakers have allocated $10 million to the reserve, a small portion of Texas’ $338 billion budget, yet supporters argue it marks an important step for the growing crypto industry.

Bitcoin prices have fluctuated significantly this year, peaking above $126,000 in October before dropping to around $85,000 recently. The state’s purchase at roughly $87,000 per bitcoin reflects ongoing market volatility.

Advocates see the investment as forward-looking, citing potential long-term benefits in job creation, tax revenue, and digital asset adoption.

Critics remain sceptical, warning that public crypto investments carry high risk and may favour industry interests over taxpayers. Some economists criticised the move as conflicting with Texas’ conservative fiscal approach and risky government speculation.

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Meta expands global push against online scam networks

The US tech giant, Meta, outlined an expanded strategy to limit online fraud by combining technical defences with stronger collaboration across industry and law enforcement.

The company described scams as a threat to user safety and as a direct risk to the credibility of its advertising ecosystem, which remains central to its business model.

Executives emphasised that large criminal networks continue to evolve and that a faster, coordinated response is essential instead of fragmented efforts.

Meta presented recent progress, noting that more than 134 million scam advertisements were removed in 2025 and that reports about misleading advertising fell significantly in the last fifteen months.

It also provided details about disrupted criminal networks that operated across Facebook, Instagram and WhatsApp.

Facial recognition tools played a crucial role in detecting scam content that utilised images of public figures, resulting in an increased volume of removals during testing, rather than allowing wider circulation.

Cooperation with law enforcement remains central to Meta’s approach. The company supported investigations that targeted criminal centres in Myanmar and illegal online gambling operations connected to transfers through anonymous accounts.

Information shared with financial institutions and partners in the Global Signal Exchange contributed to the removal of thousands of accounts. At the same time, legal action continued against those who used impersonation or bulk messaging to deceive users.

Meta stated that it backs bipartisan legislation designed to support a national response to online fraud. The company argued that new laws are necessary to weaken transnational groups behind large-scale scam operations and to protect users more effectively.

A broader aim is to strengthen trust across Meta’s services, rather than allowing criminal activity to undermine user confidence and advertiser investment.

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Mistral AI unveils new open models with broader capabilities

Yesterday, Mistral AI introduced Mistral 3 as a new generation of open multimodal and multilingual models that aim to support developers and enterprises through broader access and improved efficiency.

The company presented both small dense models and a new mixture-of-experts system called Mistral Large 3, offering open-weight releases to encourage wider adoption across different sectors.

Developers are encouraged to build on models in compressed formats that reduce deployment costs, rather than relying on heavier, closed solutions.

The organisation highlighted that Large 3 was trained with extensive resources on NVIDIA hardware to improve performance in multilingual communication, image understanding and general instruction tasks.

Mistral AI underlined its cooperation with NVIDIA, Red Hat and vLLM to deliver faster inference and easier deployment, providing optimised support for data centres along with options suited for edge computing.

A partnership that introduced lower-precision execution and improved kernels to increase throughput for frontier-scale workloads.

Attention was also given to the Ministral 3 series, which includes models designed for local or edge settings in three sizes. Each version supports image understanding and multilingual tasks, with instruction and reasoning variants that aim to strike a balance between accuracy and cost efficiency.

Moreover, the company stated that these models produce fewer tokens in real-world use cases, rather than generating unnecessarily long outputs, a choice that aims to reduce operational burdens for enterprises.

Mistral AI continued by noting that all releases will be available through major platforms and cloud partners, offering both standard and custom training services. Organisations that require specialised performance are invited to adapt the models to domain-specific needs under the Apache 2.0 licence.

The company emphasised a long-term commitment to open development and encouraged developers to explore and customise the models to support new applications across different industries.

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AI helps detect congenital heart defects in unborn babies

Mount Sinai doctors in New York City are the first to utilise AI to enhance prenatal ultrasounds and detect congenital heart defects more effectively. BrightHeart’s FDA-approved technology is now used at Mount Sinai-affiliated Carnegie Imaging for Women across three Manhattan locations.

Congenital heart defects affect about 1 in 500 newborns and often require urgent intervention.

A study in Obstetrics & Gynecology found AI-assisted ultrasounds detected major defects with over 97 percent accuracy, cut reading time by 18 percent, and raised confidence scores by 19 percent.

The study reviewed 200 fetal ultrasounds from 11 centres across two countries, with and without AI assistance, by obstetricians and maternal-fetal medicine specialists.

AI improved detection, confidence, and efficiency, especially in centres without specialised fetal heart experts.

Experts say AI can level the field of prenatal diagnosis and optimise patient care. Dr Lam-Rachlin and Dr Rebarber emphasised AI’s potential to standardise detection and urged further research for routine clinical use.

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NVIDIA platform lifts leading MoE models

Frontier developers are adopting a mixture-of-experts architecture as the foundation for their most advanced open-source models. Designers now rely on specialised experts that activate only when needed instead of forcing every parameter to work on each token.

Major models, such as DeepSeek-R1, Kimi K2 Thinking, and Mistral Large 3, rise to the top of the Artificial Analysis leaderboard by utilising this pattern to combine greater capability with lower computational strain.

Scaling the architecture has always been the main obstacle. Expert parallelism requires high-speed memory access and near-instant communication between multiple GPUs, yet traditional systems often create bottlenecks that slow down training and inference.

NVIDIA has shifted toward extreme hardware and software codesign to remove those constraints.

The GB200 NVL72 rack-scale system links seventy-two Blackwell GPUs via fast shared memory and a dense NVLink fabric, enabling experts to exchange information rapidly, rather than relying on slower network layers.

Model developers report significant improvements once they deploy MoE designs on NVL72. Performance leaps of up to ten times have been recorded for frontier systems, improving latency, energy efficiency and the overall cost of running large-scale inference.

Cloud providers integrate the platform to support customers in building agentic workflows and multimodal systems that route tasks between specialised components, rather than duplicating full models for each purpose.

Industry adoption signals a shift toward a future where efficiency and intelligence evolve together. MoE has become the preferred architecture for state-of-the-art reasoning, and NVL72 offers a practical route for enterprises seeking predictable performance gains.

NVIDIA positions its roadmap, including the forthcoming Vera Rubin architecture, as the next step in expanding the scale and capability of frontier AI.

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