Development

Veo 3.1 brings audio and control to AI filmmaking

Google DeepMind has unveiled Veo 3.1, the newest upgrade to its video generation model, bringing more artistic freedom, realism and sound integration to its AI filmmaking tool, Flow.

The update gives creators advanced scene control and introduces generated audio across existing features like ‘Ingredients to Video’, ‘Frames to Video’ and ‘Extend’.

Users can now fine-tune visuals by combining multiple reference images, seamlessly link frames into longer clips, and edit scenes with new insert and removal tools that handle shadows and lighting automatically.

Flow’s new precision tools mark a significant step toward cinematic-level storytelling powered by AI.

Veo 3.1 is also accessible through the Gemini API, Vertex AI and the Gemini app, broadening its availability to developers and enterprises alike.

These enhancements signal Google’s ongoing ambition to push the boundaries of generative video technology for creative and professional applications.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Google and Salesforce deepen AI partnership across Agentforce 360 and Gemini Enterprise

Salesforce and Google have expanded their long-term partnership, introducing new integrations between Salesforce’s Agentforce 360 platform and Google’s Gemini Enterprise. The collaboration aims to enhance productivity and build a new foundation for intelligent, connected business operations.

Through the expansion, Gemini models now power Salesforce’s Atlas Reasoning Engine, combining multimodal intelligence with hybrid reasoning to improve how AI agents handle complex, multistep enterprise tasks.

These integrations also extend across Google Workspace, bringing Agentforce 360 capabilities directly into Gmail, Meet, Docs, Sheets and Drive for sales, service and IT teams.

Salesforce highlights that fine-tuned Gemini models outperform competing LLMs on key CRM benchmarks, enabling businesses to automate workflows more reliably and consistently.

The companies also reaffirm their commitment to open standards like Model Context Protocol and Agent2Agent, allowing multi-agent collaboration and interoperability across enterprise systems.

A partnership that further integrates Gemini Enterprise with Slack’s real-time search API, enabling users to draw insights directly from organisational data within conversations.

Both companies stress that these advances mark a major step toward an ‘Agentic Enterprise’, where AI systems work alongside people to drive innovation, improve service quality and streamline decision-making.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Between trips, Uber pilots paid AI data work

Uber is piloting ‘Digital Tasks’ in the US, letting select drivers and couriers earn by training AI models between trips.

Tasks include short selfie videos in any language, uploading multilingual documents, and uploading category-tagged images; each takes minutes, and pay varies by task.

Uber says demand came from US drivers seeking off-road income; participants can opt in via the Work Hub and need no extra experience.

Partners commissioning the data aren’t named. The pilot starts later this year, with potential expansion to non-drivers and wider markets.

The move diversifies beyond rides and delivery as robotaxis loom. Uber argues for more earning channels now, while autonomy scales over time.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

Nurses gain AI support as Microsoft evolves Dragon Copilot in healthcare

Microsoft has announced major AI upgrades to Dragon Copilot, its healthcare assistant, extending ambient and generative AI capabilities to nursing workflows and third-party partner integrations.

The update is designed to improve patient journeys, reduce administrative workloads and enhance efficiency across healthcare systems.

The new features allow partners to integrate their own AI applications directly into Dragon Copilot, helping clinicians access trusted information, automate documentation and streamline financial management without leaving their workflow.

Partnerships with Elsevier, Wolters Kluwer, Atropos Health, Canary Speech and others will provide real-time decision support, clinical insights and revenue cycle automation.

Microsoft is also introducing the first commercial ambient AI solution built for nurses, designed to reduce burnout and enhance care quality.

A technology that automatically records nurse-patient interactions and transforms them into editable documentation for electronic health records, saving time and supporting accuracy.

Nurses can also access medical content within the same interface and automate note-taking and summaries, allowing greater focus on patient care.

The company says these developments mark a new phase in its AI strategy for healthcare, strengthening its collaboration with providers and partners.

Microsoft aims to make clinical workflows more connected, reliable and human-centred, while supporting safe, evidence-based decision-making through its expanding ecosystem of AI tools.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Microsoft warns of a surge in ransomware and extortion incidents

Financially motivated cybercrime now accounts for the majority of global digital threats, according to Microsoft’s latest Digital Defense Report.

The company’s analysts found that over half of all cyber incidents with known motives in the past year were driven by extortion or ransomware, while espionage represented only a small fraction.

Microsoft warns that automation and accessible off-the-shelf tools have allowed criminals with limited technical skills to launch widespread attacks, making cybercrime a constant global threat.

The report reveals that attackers increasingly target critical services such as hospitals and local governments, where weak security and urgent operational demands make them easy victims.

Cyberattacks on these sectors have already led to real-world harm, from disrupted emergency care to halted transport systems. Microsoft highlights that collaboration between governments and private industry is essential to protect vulnerable sectors and maintain vital services.

While profit-seeking criminals dominate by volume, nation-state actors are also expanding their reach. State-sponsored operations are growing more sophisticated and unpredictable, with espionage often intertwined with financial motives.

Some state actors even exploit the same cybercriminal networks, complicating attribution and increasing risks for global organisations.

Microsoft notes that AI is being used by both attackers and defenders. Criminals are employing AI to refine phishing campaigns, generate synthetic media and develop adaptive malware, while defenders rely on AI to detect threats faster and close security gaps.

The report urges leaders to prioritise cybersecurity as a strategic responsibility, adopt phishing-resistant multifactor authentication, and build strong defences across industries.

Security, Microsoft concludes, must now be treated as a shared societal duty rather than an isolated technical task.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Lehane backs OpenAI’s Australia presence as AI copyright debate heats up

OpenAI signalled a break with Australia’s tech lobby on copyright, with global affairs chief Chris Lehane telling SXSW Sydney the company’s models are ‘going to be in Australia, one way or the other’, regardless of reforms or data-mining exemptions.

Lehane framed two global approaches: US-style fair use that enables ‘frontier’ AI, versus a tighter, historical copyright that narrows scope, saying OpenAI will work under either regime. Asked if Australia risked losing datacentres without loser laws, he replied ‘No’.

Pressed on launching and monetising Sora 2 before copyright issues are settled, Lehane argued innovation precedes adaptation and said OpenAI aims to ‘benefit everyone’. The company paused videos featuring Martin Luther King Jr.’s likeness after family complaints.

Lehane described the US-China AI rivalry as a ‘very real competition’ over values, predicting that one ecosystem will become the default. He said US-led frontier models would reflect democratic norms, while China’s would ‘probably’ align with autocratic ones.

To sustain a ‘democratic lead’, Lehane said allies must add gigawatt-scale power capacity each week to build AI infrastructure. He called Australia uniquely positioned, citing high AI usage, a 30,000-strong developer base, fibre links to Asia, Five Eyes membership, and fast-growing renewables.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

AI Infrastructure Partnership and BlackRock consortium acquire Aligned Data Centers

A consortium comprising the Artificial Intelligence Infrastructure Partnership, MGX, and BlackRock’s Global Infrastructure Partners has announced the acquisition of Aligned Data Centers for an estimated forty billion dollars.

The move marks a major step towards expanding the infrastructure underpinning global AI and cloud growth.

Aligned, headquartered in Dallas, operates more than fifty campuses and five gigawatts of capacity across the US and Latin America. The company is known for its patented air, liquid, and hybrid cooling systems that enhance efficiency and sustainability, particularly in high-density AI environments.

Under the consortium, Aligned will accelerate the development of scalable and energy-efficient data facilities to meet rising global demand.

The Artificial Intelligence Infrastructure Partnership was founded by BlackRock, GIP, MGX, Microsoft, and NVIDIA to advance large-scale AI infrastructure investment.

Backed by sovereign wealth funds from Kuwait and Singapore, it aims to mobilise thirty billion dollars in equity and up to one hundred billion, including debt.

The Aligned acquisition represents its first major investment and positions the company as a cornerstone of the group’s strategy.

Executives from BlackRock, MGX, and GIP said the deal reflects a shared commitment to building sustainable, resilient infrastructure for the AI era.

Aligned CEO Andrew Schaap added that the partnership would strengthen the company’s global reach and innovation capacity, redefining standards for digital infrastructure in an increasingly AI-driven economy.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Oracle launches embedded AI Agent Marketplace in Fusion Applications

Oracle has announced substantial enhancements to its AI Agent Studio for Fusion Applications, introducing a native AI Agent Marketplace, broader LLM support, and advanced agent tooling and governance features.

The AI Agent Marketplace is embedded within Fusion Applications, allowing customers to browse, test and deploy partner-built, Oracle-validated agents directly within their enterprise workflows. These agents can supplement or replace built-in agents to address industry-specific tasks.

Oracle is also expanding support for external large language models: customers and partners can now select from providers including OpenAI, Anthropic, Cohere, Google, Meta and xAI. This gives flexibility in choosing which LLM best fits a given use case.

New capabilities in Agent Studio include MCP support to integrate agents with third-party data systems, agent cards for cross-agent communication and collaboration, credential store for secure access to external APIs, monitoring dashboard, and agent tracing and performance metrics for observability.

It will also have prompt libraries and version control for managing agent prompts across lifecycles, workflow chaining and deterministic execution to organise multi-step agent tasks, and human-in-the-loop support to combine automation with oversight.

Oracle also highlights its network of 32,000 certified experts trained in building AI agents via Agent Studio. These experts can help customers optimise use, extend the marketplace, and ensure agent quality and safety.

Overall, Oracle’s release positions its Fusion ecosystem as a more open, flexible, and enterprise-ready platform for AI agent deployment, balancing embedded automation with extensibility and governance.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot! 

New method helps AI models locate personalised objects in scenes

MIT and the MIT-IBM Watson AI Lab have developed a training approach that enables generative vision-language models to localise personalised objects (for example, a specific cat) across new scenes, a task at which they previously performed poorly.

While vision-language models (VLMs) are good at recognising generic object categories (dogs, chairs, etc.), they struggle when asked to point out your specific dog or chair under different conditions.

To remedy this, the researchers framed a fine-tuning regime using video-tracking datasets, where the same object appears in multiple frames.

Crucially, they used pseudo-names (e.g. ‘Charlie’) instead of real object names to prevent the model from relying on memorised label associations. This encourages it to reason about context, scene layout, appearance cues, and relative position, rather than shortcut to category matches.

AI models trained with the method showed a 12% average improvement in personalised localization. In some settings, especially with pseudo-naming, gains reached 21%. Importantly, this enhanced ability did not degrade the model’s overall object recognition performance.

Potential applications include smart home cameras recognising your pet, assistive devices helping visually impaired users find items, robotics, surveillance, and ecological monitoring (e.g. tracking particular animals). The approach helps models better generalise from a few example images rather than needing full retraining for each new object.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot! 

Adaptive optics meets AI for cellular-scale eye care

AI is moving from lab demos to frontline eye care, with clinicians using algorithms alongside routine fundus photos to spot disease before symptoms appear. The aim is simple: catch diabetic retinopathy early enough to prevent avoidable vision loss and speed referrals for treatment.

New imaging workflows pair adaptive optics with machine learning to shrink scan times from hours to minutes while preserving single-cell detail. At the US National Eye Institute, models recover retinal pigment epithelium features and clean noisy OCT data to make standard scans more informative.

Duke University’s open-source DCAOSLO goes further by combining multiplexed light signals with AI to capture cellular-scale images quickly. The approach eases patient strain and raises the odds of getting diagnostic-quality data in busy clinics.

Clinic-ready diagnostics are already changing triage. LumineticsCore, the first FDA-cleared AI to detect more-than-mild diabetic retinopathy from primary-care images, flags who needs urgent referral in seconds, enabling earlier laser or pharmacologic therapy.

Researchers also see the retina as a window on wider health, linking vascular and choroidal biomarkers to diabetes, hypertension and cardiovascular risk. Standardised AI tools promise more reproducible reads, support for trials and, ultimately, home-based monitoring that extends specialist insight beyond the clinic.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!