Artificial intelligence Archives | Page 2 of 585

AI is helping close the heart health gap in remote Australian communities

Google has launched a new AI-powered initiative aimed at reducing heart disease risk in rural Australia, where people living in remote communities are 60% more likely to die from heart disease than those in metropolitan areas.

The programme, a first for the Asia-Pacific region, is backed by a $1 million AUD investment from Google Australia’s Digital Future Initiative and brings together Wesfarmers Health, SISU Health, the Victor Chang Cardiac Research Institute, and Latrobe Health Services.

At the centre of the initiative is Google for Health’s Population Health AI (PHAI), an advanced analytics tool that analyses aggregated and de-identified datasets, including clinical records, air quality, pollen levels, and geographic data, to identify hidden health risks at a community level.

The aim is to help health organisations move away from reactive treatment towards proactively managing chronic condition risks tailored to specific towns or postcodes.

SISU Health will use PHAI insights to guide the delivery of over 50,000 new health screenings across remote areas, combining geographic AI analysis with on-the-ground community care. Google described the goal as ensuring every Australian has access to personalised care regardless of where they live.

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AI browsers expose new cybersecurity attack surfaces

Security researchers have demonstrated that agentic browsers, powered by AI, may introduce new cybersecurity vulnerabilities.

Experiments targeting the Comet AI browser, developed by Perplexity AI, showed that attackers could manipulate the system into executing phishing scams in only a few minutes.

The attack exploits the reasoning process used by AI agents when interacting with websites. These systems continuously explain their actions and observations, revealing internal signals that attackers can analyse to refine malicious strategies and bypass built-in safeguards.

Researchers showed that phishing pages can be iteratively trained using adversarial machine learning methods, such as Generative Adversarial Networks.

By observing how the AI browser responds to suspicious signals, attackers can optimise fraudulent pages until the system accepts them as legitimate.

The findings highlight a shift in the cybersecurity threat landscape. Instead of deceiving human users directly, attackers increasingly focus on manipulating the AI agents that perform online actions on behalf of users.

Security experts warn that prompt injection vulnerabilities remain a fundamental challenge for large language models and agentic systems.

Although new defensive techniques are being developed, researchers believe such weaknesses may remain difficult to eliminate.

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Generative AI in precision oncology faces a trust and safety challenge

A narrative review published in the Journal of Hematology & Oncology examined how generative AI tools could support oncologists in precision cancer care.

In this increasingly data-intensive field, clinicians must cross-reference genomic sequencing results, patient records, imaging findings, and a rapidly expanding body of biomedical literature to inform their decisions.

Researchers found promising results for AI-assisted clinical trial matching and diagnostic report drafting, but also highlighted significant risks that make unsupervised deployment dangerous.

On the positive side, the AI tool TrialGPT demonstrated 87.3% agreement with expert assessments when matching patients to clinical trials, while reducing processing time by an average of 42.6%.

Meanwhile, the vision-language model Flamingo-CXR matched or exceeded the performance of board-certified radiologists in 94% of chest X-ray cases with no clinically relevant findings.

Researchers cautioned, however, that clinically significant errors appeared in 24.8% of evaluated imaging reports, whether AI- or human-generated, underscoring the need for combined oversight.

The review’s authors advocate for ‘Human-in-the-Loop’ workflows, in which human experts review all AI outputs before clinical implementation, and for Retrieval-Augmented Generation techniques that force AI systems to draw on current medical guidelines rather than relying solely on their base training data.

The key conclusion is that AI should function as an assistant to oncologists, not as an autonomous decision maker.

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AI agents face growing prompt injection risks

AI developers are working on new defences against prompt-injection attacks that aim to manipulate AI agents. Security specialists warn that attackers are increasingly using social engineering techniques to influence AI systems that interact with online content.

Researchers say AI agents that browse the web or handle user tasks face growing risks from hidden instructions embedded in emails or websites. Experts in the US note that attackers often attempt to trick AI into revealing sensitive information.

Engineers are responding by designing systems that limit the impact of manipulation attempts. Developers in the US say AI tools must include safeguards preventing sensitive data from being transmitted without user approval.

Security teams are also introducing technologies that detect risky actions and prompt users for confirmation. Specialists argue that strong system design and user oversight will remain essential as AI agents gain more autonomy.

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MIT researchers outline future of AI and physical sciences

AI and the mathematical and physical sciences are entering a new phase of collaboration that could accelerate technological progress and scientific discovery. Researchers increasingly see the relationship as a two-way exchange rather than a one-sided use of AI tools.

A 2025 MIT workshop brought together experts from astronomy, chemistry, materials science, mathematics and physics to examine the future of this collaboration.

Discussions resulted in a white paper published in Machine Learning: Science and Technology, outlining strategies for research institutions and funding bodies.

Participants agreed that stronger computing infrastructure, shared data resources and cross-disciplinary research methods are essential for progress. Scientists also improve AI by analysing neural networks, identifying principles and developing new algorithms.

Researchers highlighted the growing importance of so-called ‘centaur scientists’- specialists trained in both AI and traditional scientific disciplines. Universities, including MIT, are expanding interdisciplinary programmes and research initiatives to train experts who can work across AI and scientific fields.

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Leading tech companies deepen AI competition with new capabilities

AI competition among leading AI developers intensified in early 2026 as major companies expanded their models, platforms, and partnerships. Companies including Google, OpenAI, Anthropic, and xAI are introducing new capabilities and integrating AI systems into broader ecosystems.

Google has continued to expand its Gemini model family with updates to Gemini 3.1 Pro and 3.1 Flash, designed to support complex tasks across applications. The company is also integrating Gemini into services such as Docs, Sheets, Slides, and Drive, allowing users to generate documents and analyse data across multiple Google services.

Gemini has also been embedded into the Chrome browser and integrated with Samsung’s Galaxy devices, expanding its distribution across consumer platforms as AI competition among major developers accelerates.

Anthropic has focused on advancing the Claude model family while positioning the system for enterprise and professional use. Recent updates include Claude Sonnet 4.6, which introduces improvements in reasoning and coding capabilities alongside an expanded context window currently in beta. The company has also launched a limited preview of the Claude Marketplace, allowing organisations to use third-party tools built on Claude through partnerships with several software companies.

OpenAI has continued to update ChatGPT with the release of the GPT-5 series, including GPT-5.2 and GPT-5.4. The newer models combine reasoning, coding, and agent-based workflows, while also introducing computer-use capabilities that allow the system to interact with applications directly.

OpenAI has also introduced additional services, including ChatGPT Health and integrations designed to assist with spreadsheet modelling and data analysis, further intensifying AI competition across enterprise and consumer tools.

Meanwhile, xAI has expanded development of its Grok models while increasing computing infrastructure. The company has reported growth in Grok usage through integration with the X platform and other applications. Recent announcements include upgrades to Grok’s voice and multimodal capabilities, as well as continued training of future models.

Across the industry, developers are increasingly positioning their systems not only as conversational assistants but also as tools integrated into enterprise workflows, creative production, and software development. New releases in 2026 reflect a broader shift toward multimodal systems, agent-based capabilities, and deeper integration with existing digital platforms, highlighting how AI competition is shaping the next phase of AI development.

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ChatGPT dynamic visual explanations introduce interactive learning tools

OpenAI has introduced a new ChatGPT feature called dynamic visual explanations, allowing users to interact with mathematical and scientific concepts through real-time visuals.

Instead of relying solely on text explanations or static diagrams, the feature enables users to manipulate formulas and variables and immediately see how those changes affect results. For example, when exploring the Pythagorean theorem, users can adjust the triangle’s sides and see the hypotenuse update instantly.

To use the tool, users can ask ChatGPT questions such as ‘What is a lens equation?’ or ‘How can I find the area of a circle?’ The chatbot responds with both a written explanation and an interactive visual module that users can manipulate directly.

The feature currently supports more than 70 topics in mathematics and science. The topics include binomial squares, Charles’ law, compound interest, Coulomb’s law, exponential decay, Hooke’s law, kinetic energy, linear equations, and Ohm’s law.

OpenAI says it plans to expand the range of topics over time. The feature is already available to all logged-in ChatGPT users. The launch marks a shift in how ChatGPT supports learning. Instead of simply providing answers, the tool now encourages users to explore underlying concepts by experimenting with interactive models.

AI tools have become increasingly common in education, although their role remains widely debated. Some educators worry that students may become overly dependent on AI tools, while others see them as valuable learning aids.

According to OpenAI, more than 140 million people use ChatGPT every week to help with subjects such as mathematics and science, which many learners find challenging. Other technology companies are also experimenting with similar tools. Google’s Gemini introduced interactive diagrams and visual explanations last year.

The new feature joins several other ChatGPT learning tools, including study mode, which guides users through problems step by step, and QuizGPT, which allows users to create flashcards and test themselves before exams.

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UK approves £7.5bn AI data centre campus at Elsham Tech Park

Plans for one of the UK’s largest AI data centre campuses have been approved in North Lincolnshire, denoting a significant investment in digital infrastructure.

The project, known as Elsham Tech Park, will be developed near Elsham Wolds Industrial Estate on the site of the former RAF Elsham Wolds airfield. The development is expected to deliver more than 1.5 million square metres of hyperscale data centre floorspace across 15 data halls, with an estimated construction cost of around £7.5 billion.

If fully developed, the campus could provide up to 1GW (1,000MW) of computing capacity, placing it among the largest proposed AI data centre facilities in the UK. The project is being led by Elsham Tech Park Ltd, a company created for the development and overseen by infrastructure developer Greystoke.

The proposed campus would cover approximately 176 hectares (435 acres) and include an on-site energy centre capable of generating up to 49.9MW of electricity. Plans also include battery storage facilities, substations, district heating infrastructure, and additional commercial space.

The masterplan incorporates a greenhouse complex that reuses excess heat from the data centre servers to support agricultural production. Developers say this approach could improve energy efficiency by enabling greenhouse cultivation using waste heat generated by computing infrastructure.

Construction is expected to begin in 2027, with the first phase of the campus scheduled to open in 2029. The development timeline covers roughly ten years.

During construction, the project could support between 2,600 and 3,600 full-time equivalent jobs annually across on-site and supply chain roles. Once operational, the facility is expected to create around 900 long-term skilled jobs.

North Lincolnshire Council said the project could attract up to £10 billion in investment and strengthen the region’s role in the country’s growing AI and cloud computing infrastructure sector.

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Anthropic lawsuit gains Big Tech support in AI dispute

Several major US technology companies have backed Anthropic in its lawsuit challenging the US Department of Defence’s decision to label the AI company a national security ‘supply chain risk’.

Google, Amazon, Apple, and Microsoft have filed legal briefs supporting Anthropic’s attempt to overturn the designation issued by Defence Secretary Pete Hegseth. Anthropic argues the decision was retaliation after the company declined to allow its AI systems to be used for mass surveillance or autonomous weapons.

In court filings, the companies warned that the government’s action could have wider consequences for the technology sector. Microsoft said the decision could have ‘broad negative ramifications for the entire technology sector’.

Microsoft, which works closely with the US government and the Department of Defence, said it agreed with Anthropic’s position that AI systems should not be used to conduct domestic mass surveillance or enable autonomous machines to initiate warfare.

A joint amicus brief supporting Anthropic was also submitted by the Chamber of Progress, a technology policy organisation funded by companies including Google, Apple, Amazon and Nvidia. The group said it was concerned about the government penalising a company for its public statements.

The brief described the designation as ‘a potentially ruinous sanction’ for businesses and warned it could create a climate in which companies fear government retaliation for expressing views.

Anthropic’s lawsuit claims the government violated its free speech rights by retaliating against the company for comments made by its leadership. The dispute escalated after Anthropic declined to remove contractual restrictions preventing its AI models from being used for mass surveillance or autonomous weapons.

The company had previously introduced safeguards in government contracts to limit certain uses of its technology. Negotiations over revised contract language continued for several weeks before the disagreement became public.

Former military officials and technology policy advocates have also filed supporting briefs, warning that the decision could discourage companies from participating in national security projects if they fear retaliation for voicing concerns. The case is currently being heard in federal court in San Francisco.

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Google outlines roadmap for safer generative AI for young users

Google has presented a strategy for developing generative AI systems designed to protect younger users better better while supporting learning and creativity.

The approach emphasises building conversational AI experiences that balance innovation with safeguards tailored to children and teenagers.

The company’s framework rests on three pillars: protecting young people online, respecting the role of families in digital environments and enabling youth to explore AI technologies responsibly.

According to Google, safety policies prohibit harmful content, including material linked to child exploitation, violent extremism and self-harm, while additional restrictions target age-inappropriate topics.

Safeguards are integrated throughout the AI development lifecycle, from user input to model responses. Systems use specialised classifiers to detect potentially harmful queries and prevent inappropriate outputs.

These protections are also applied to models such as Gemini, which incorporates defences against prompt manipulation and cyber misuse.

Beyond preventing harm, Google aims to support responsible AI adoption through educational initiatives.

Resources designed for families encourage discussions about responsible technology use, while tools such as Guided Learning in Gemini seek to help students explore complex topics through structured explanations and interactive learning support.

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