Digital cooperation

Microsoft backs Australia’s next phase of digital government with new AI and cloud agreement

Australia’s rise to second place in the OECD Digital Government Index signals renewed momentum for national digital transformation.

A shift that comes as Microsoft signs a new five-year Volume Sourcing Arrangement with the Federal Government, designed to underpin modernisation across public services and create a secure, future-ready foundation for responsible AI adoption.

The agreement led by the Digital Transformation Agency gives agencies access to Microsoft Copilot, Azure, Microsoft 365, Dynamics 365 and a strengthened security and compliance framework instead of continuing reliance on ageing systems.

The arrangement sets clearer strategic pathways for innovation, procurement and skills development through an enhanced governance structure.

It recommits both sides to national security requirements, including the Security of Critical Infrastructure legislation, the Cloud Hosting Certification Framework and IRAP.

These measures allow agencies to expand AI use while retaining control of data and meeting the expectations placed on government institutions.

A successful Copilot trial in 2024 already demonstrated personal productivity gains of around one hour per day for participating staff.

Microsoft is also establishing a $1.55 million training fund for the Australian Public Service to support capability building in ethical AI use and modern cloud operations.

The company emphasises that Australia’s partner ecosystem will gain new opportunities because the agreement simplifies how local firms engage with government agencies. Such an approach forms an important part of the wider public sector reform agenda announced last year.

The new deal aligns with national priorities set out in the Whole-of-Government Cloud Computing Policy and the National AI Plan.

Australia now enters a pivotal period in which digital transformation is guided not only by technological capacity but by the frameworks of trust, resilience and public benefit that shape how government services evolve.

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Colorado targets AI chatbot safety

AI chatbots operating in Colorado would face new child safety and suicide prevention requirements under a bipartisan bill introduced in the Colorado legislature. Lawmakers say the measure addresses parents to concerns about harmful chatbot interactions.

House Bill 1263 would require companies to clearly inform children in Colorado that they are interacting with AI rather than a real person. Platforms would also be barred from offering engagement rewards to child users.

The proposal mandates reasonable safeguards to prevent sexually explicit content and to stop chatbots from encouraging emotional dependence, including romantic role-playing. Parental control options would also be required where services are accessible to children in Colorado.

Companies would need to provide suicide prevention resources when users express self-harm thoughts and report such incidents to the Colorado attorney general. Violations would be treated as consumer protection infractions, carrying fines of up to $1,000 per occurrence in Colorado.

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UAE builds sovereign financial cloud

The Central Bank of the UAE has partnered with Abu Dhabi-based AI company Core42 to develop a sovereign financial cloud infrastructure in the UAE. The system is designed to ensure data sovereignty and strengthen protection against cyber threats.

According to the Central Bank of the UAE, the platform will operate on a centralised, highly secure and isolated infrastructure. It aims to support continuous financial services while boosting operational agility across the UAE.

The infrastructure will be powered by AI and provide automation and real-time data analysis for licensed institutions in the UAE. It will also enable unified management of multi-cloud services within a single regulatory framework.

Core42, established by G42 in 2023, said finance must remain sovereign as it relies on digital infrastructure. The Central Bank of the UAE described the project as a key pillar of its financial infrastructure transformation programme.

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How multimodal sensing powers physical AI

Multimodal sensing allows physical AI systems to combine inputs such as vision, audio, lidar and touch to build situational awareness in real time. The approach enables machines to operate autonomously in complex physical environments.

The architecture typically includes input modules for individual sensors, a fusion module to combine relevant data, and an output module to generate actions. Applications range from robotics and autonomous vehicles to spatial AI systems navigating dynamic 3D spaces.

Fusion techniques vary by use case, from Bayesian networks for uncertainty management to Kalman filters for navigation and neural networks for robotic manipulation. The aim is to leverage complementary sensor strengths while maintaining reliability.

Implementation presents technical challenges including environmental noise filtering, calibration across time and space, and balancing redundant versus complementary sensing. Engineers must also manage tradeoffs in processing power, controllers and system design.

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UiPath launches agentic AI to streamline healthcare operations

UiPath has unveiled new agentic AI solutions for healthcare providers and payers. The tools focus on medical record summarisation, claim denial prevention, and prior authorisation, connecting data to speed workflows and improve efficiency.

Healthcare organisations face labour shortages and fragmented systems, making revenue cycle management challenging. Providers produce large volumes of clinical documentation that must be quickly turned into actionable insights for accurate reimbursement.

The platform converts records into concise, citation-backed summaries, automates claim review and appeals, and streamlines eligibility checks. AI predicts risks, reduces errors, and accelerates clinical and administrative processes for providers and payers alike.

UiPath partners with innovators such as Genzeon to embed domain expertise. The solution addresses rising costs, complex regulations, and labour challenges, helping teams make data-driven decisions and improve patient outcomes.

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AI accelerates drug formulation through predictive modelling

Low solubility and poor bioavailability remain major hurdles in small-molecule drug development, often preventing promising candidates from reaching clinical trials. Traditional trial-and-error methods are time-consuming and depend heavily on the limited availability of active pharmaceutical ingredients (APIs).

AI and machine learning now provide predictive models that anticipate solubility, permeability and systemic exposure. These tools let scientists prioritise high-impact experiments while conserving valuable material.

Digital platforms combine predictive algorithms with stability testing to guide excipient and technology selection. AI can simulate molecular interactions and dose scenarios, helping teams identify risks early and refine first-in-human doses safely.

End-to-end AI/ML workflows integrate data, modelling and manufacturing insights. However, this accelerates development timelines, lowers the risk of late-stage reformulations and connects early formulation choices directly to clinical and manufacturing outcomes.

While AI enhances efficiency and precision, it does not replace human expertise. It amplifies formulation scientists’ work, freeing them to focus on innovative design, problem-solving and delivering high-quality therapies to patients more rapidly.

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National security concerns reshape US data policy

US policymakers are increasingly treating personal data as a dual use asset that carries both economic value and national security risks. Regulators have raised concerns about sensitive information, including geolocation data linked to military personnel.

Measures such as the Protecting Americans Data from Foreign Adversaries Act of 2024 and the Department of Justice Data Security Program aim to curb misuse by designated foreign adversaries. Both frameworks impose broad restrictions on cross border data transfers.

Experts warn that compliance remains complex and uncertain, with companies adapting in what one adviser described as a fog. Enforcement signals have already emerged, including a draft noncompliance letter from the Federal Trade Commission and litigation.

Organizations are being urged to integrate national security expertise into privacy and cybersecurity teams. Observers say early preparation is essential as selective enforcement risks increase under strict but evolving US data protection regimes.

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AI respond better to clarity than courtesy

Large language models are designed to mimic human conversation, but treating them like people can mislead users. Politeness, flattery, or threats do not consistently improve the accuracy of AI responses.

Experts recommend focusing on how questions are structured rather than on word choice. Asking for multiple options, giving examples, and conducting step-by-step interviews can make AI outputs more relevant and useful.

Role-playing may be effective for creative or exploratory tasks, but it can reduce reliability when precise answers are required. AI models are constantly updated, making old prompting tricks largely ineffective.

Maintaining neutrality in prompts prevents biased responses, and while politeness may not improve AI performance, it can make interactions more comfortable. Developing careful prompt strategies is more effective than relying on manners alone.

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EDPS and regulators unite to address misuse of AI imagery across jurisdictions

The European Data Protection Supervisor (EDPS) and authorities from 61 jurisdictions issued a joint statement on AI-generated imagery, warning about tools that create realistic depictions of identifiable individuals without consent. The move underscores concerns over privacy, dignity and child safety.

Authorities said advances in AI image and video tools, especially when integrated into social media platforms, have enabled non-consensual intimate imagery, defamatory depictions, and other harmful content. Children and vulnerable groups are seen as particularly at risk.

The EDPS and the other signatories reminded organisations that AI content-generation systems must comply with applicable data protection and privacy laws. They stressed that creating non-consensual intimate imagery may constitute a criminal offence in many jurisdictions.

Organisations are urged to implement safeguards against misuse of personal data, ensure transparency about system capabilities and uses, and provide accessible mechanisms for swift content removal. Stronger protections and age-appropriate information are expected where children are involved.

Authorities signalled plans for coordinated responses, including enforcement, policy development and education initiatives. The EDPS and fellow signatories urged organisations to engage proactively with regulators and ensure innovation does not undermine fundamental rights.

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Massive chip agreement signals shift in Meta strategy

Meta has committed to purchasing $60bn worth of AI chips from Advanced Micro Devices over five years, signalling one of the largest infrastructure bets in the sector despite ongoing concerns about an AI investment bubble.

The agreement includes a 10% stake in the chipmaker and large-scale deployment of next-generation hardware beginning later this year.

Analysts say the move signals a shift to secure compute capacity and cut reliance on Nvidia amid supply constraints. Talks with Google and ongoing in-house chip work signal a multi-vendor strategy to support expanding data centre operations.

Executives say the investment reflects a shift towards hosting AI workloads and infrastructure services. Custom processors built for performance and efficiency will complement AMD GPUs, supporting capacity expansion as enterprise demand rises.

Enterprise AI competition intensifies as Anthropic and OpenAI expand integrations and tools. Significant platform investments are reshaping semiconductors and signalling strong long-term confidence in AI computing demand.

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