Capacity development

Royal Wolverhampton NHS Trust reshapes care with AI and robotic

At The Royal Wolverhampton NHS Trust, AI is beginning to transform how doctors and patients experience healthcare, cutting down on paperwork and making surgery more precise. Hospital leaders say the shift is already delivering tangible results, from faster clinical letters to reduced patient hospital visits.

One of the most impactful innovations is CLEARNotes, a system that records and summarises doctor-patient consultations. Instead of doctors spending days drafting clinic letters, the technology reduces turnaround time from as long as a week to just a day or two. Clinicians report that this tool saves time and improves productivity by as much as 25% in some clinics while ensuring that safety and governance standards remain intact.

Surgery is another area where technology is making its mark. The trust operates two Da Vinci Xi robots, now a regular feature in complex procedures, including urology, colorectal, cardiothoracic, and gynaecology cases. Compared to traditional keyhole surgery, robotic operations give surgeons better control and dexterity through a console linked to a 3D camera, while patients benefit from shorter stays and faster recoveries.

Digital tools also shape the patient’s journey before surgery begins. With My Pre-Op, patients complete their pre-operative questionnaires online from home, reducing unnecessary hospital visits and helping to ensure they are in the best condition for their operation. Hospital staff say this streamlines both efficiency and patient comfort.

The innovations recently drew praise from Science, Innovation and Technology Secretary Peter Kyle, who visited the hospital to see the systems in action. He described the trust’s embrace of AI and robotics as ‘inspiring,’ noting how safe experimentation and digital adoption already translate into improved care and efficiency. For Wolverhampton’s healthcare providers, the changes represent not just a technological upgrade but a glimpse into the future of how the NHS might deliver care across the country.

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New OpenAI hire shares savvy interview strategies

Bas van Opheusden, who joined OpenAI as a technical staff member in July, has published a comprehensive eight-page guide for aspiring applicants, offering strategic advice spanning recruiter calls, coding interviews, compensation discussions and more.

He suggests treating recruiter conversations as strategic briefings, which are key for understanding the hiring manager’s priorities, team dynamics, role expectations, and organisational goals.

Van Opheusden recommends taking notes during calls, ideally using a dual-screen setup, and arranging windows so it appears you’re maintaining eye contact.

He also shared a standard error: arriving at coding interviews without remembering the exact role he’d applied for, underscoring the importance of clear preparation and role alignment.

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Candidates urged to balance AI support with integrity

Taylor Wessing has released guidance for early-career applicants on using AI tools such as ChatGPT, Copilot, Claude and Bing Chat during the application process. The firm frames AI as a helpful ally, not a shortcut, and emphasises responsible and authentic use.

AI can assist with refining cover letters, improving structure, and articulating motivations. It can also support interview preparation through mock question practice and help candidates deepen their understanding of legal issues.

However, authenticity is paramount. Taylor Wessing encourages applicants to ensure their work reflects their voice. Using AI to complete online assessments is explicitly discouraged, as these are designed to evaluate natural ability and personal fit.

According to the firm, while AI can bolster readiness for training schemes, over-reliance or misuse may backfire. They advise transparency about any AI assistance and underscore the importance of integrity throughout the process.

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Top cybersecurity vendors double down on AI-powered platforms

The cybersecurity market is consolidating as AI reshapes defence strategies. Platform-based solutions replace point tools to cut complexity, counter AI threats, and ease skill shortages. IDC predicts that security spending will rise 12% in 2025 to $377 billion by 2028.

Vendors embed AI agents, automation, and analytics into unified platforms. Palo Alto Networks’ Cortex XSIAM reached $1 billion in bookings, and its $25 billion CyberArk acquisition expands into identity management. Microsoft blends Azure, OpenAI, and Security Copilot to safeguard workloads and data.

Cisco integrates AI across networking, security, and observability, bolstered by its acquisition of Splunk. CrowdStrike rebounds from its 2024 outage with Charlotte AI, while Cloudflare shifts its focus from delivery to AI-powered threat prediction and optimisation.

Fortinet’s platform spans networking and security, strengthened by Suridata’s SaaS posture tools. Zscaler boosts its Zero Trust Exchange with Red Canary’s MDR tech. Broadcom merges Symantec and Carbon Black, while Check Point pushes its AI-driven Infinity Platform.

Identity stays central, with Okta leading access management and teaming with Palo Alto on integrated defences. The companies aim to platformise, integrate AI, and automate their operations to dominate an increasingly complex cyberthreat landscape.

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OpenAI’s GPT-5 faces backlash for dull tone

OpenAI’s GPT-5 launched last week to immense anticipation, with CEO Sam Altman likening it to the iPhone’s Retina display moment. Marketing promised state-of-the-art performance across multiple domains, but early user reactions suggested a more incremental step than a revolution.

Many expected transformative leaps, yet improvements mainly were in cost, speed, and reliability. GPT-5’s switch system, which automatically routes queries to the most suitable model, was new, but its writing style drew criticism for being robotic and less nuanced.

Social media buzzed with memes mocking its mistakes, from miscounting letters in ‘blueberry’ to inventing US states. OpenAI quickly reinstated GPT-4 for users who missed its warmer tone, underlining a disconnect between expectations and delivery.

Expert reviews mirrored public sentiment. Gary Marcus called GPT-5 ‘overhyped and underwhelming’, while others saw modest benchmark gains. Coding was the standout, with the model topping leaderboards and producing functional, if simple, applications.

OpenAI emphasised GPT-5’s practical utility and reduced hallucinations, aiming for steadiness over spectacle. At the same time, it may not wow casual users, its coding abilities, enterprise appeal, and affordability position it to generate revenue in the fiercely competitive AI market.

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Seedbox.AI backs re-training AI models to boost Europe’s competitiveness

Germany’s Seedbox.AI is betting on re-training large language models (LLMs) rather than competing to build them from scratch. Co-founder Kai Kölsch believes this approach could give Europe a strategic edge in AI.

The Stuttgart-based startup adapts models like Google’s Gemini and Meta’s Llama for medical chatbots and real estate assistant applications. Kölsch compares Europe’s role in AI to improving a car already on the road, rather than reinventing the wheel.

A significant challenge, however, is access to specialised chips and computing power. The European Union is building an AI factory in Stuttgart, Germany, which Seedbox hopes will expand its capabilities in multilingual AI training.

Kölsch warns that splitting the planned EU gigafactories too widely will limit their impact. He also calls for delaying the AI Act, arguing that regulatory uncertainty discourages established companies from innovating.

Europe’s AI sector also struggles with limited venture capital compared to the United States. Kölsch notes that while the money exists, it is often channelled into safer investments abroad.

Talent shortages compound the problem. Seedbox is hiring, but top researchers are lured by Big Tech salaries, far above what European firms typically offer. Kölsch says talent inevitably follows capital, making EU funding reform essential.

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Google launches small AI model for mobiles and IoT

Google has released Gemma 3 270M, an open-source AI model with 270 million parameters designed to run efficiently on smartphones and Internet of Things devices.

Drawing on technology from the larger Gemini family, it focuses on portability, low energy use and quick fine-tuning, enabling developers to create AI tools that work on everyday hardware instead of relying on high-end servers.

The model supports instruction-following and text structuring with a 256,000-token vocabulary, offering scope for natural language processing and on-device personalisation.

Its design includes quantisation-aware training to work in low-precision formats such as INT4, reducing memory use and improving speed on mobile processors instead of requiring extensive computational power.

Industry commentators note that the model could help meet demand for efficient AI in edge computing, with applications in healthcare wearables and autonomous IoT systems. Keeping processing on-device also supports privacy and reduces dependence on cloud infrastructure.

Google highlights the environmental benefits of the model, pointing to reduced carbon impact and greater accessibility for smaller firms and independent developers. While safeguards like ShieldGemma aim to limit risks, experts say careful use will still be needed to avoid misuse.

Future developments may bring new features, including multimodal capabilities, as part of Google’s strategy to blend open and proprietary AI within hybrid systems.

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Cohere secures $500m funding to expand secure enterprise AI

Cohere has secured $500 million in new funding, lifting its valuation to $6.8 billion and reinforcing its position as a secure, enterprise-grade AI specialist.

The Toronto-based firm, which develops large language models tailored for business use, attracted backing from AMD, Nvidia, Salesforce, and other investors.

Its flagship multilingual model, Aya 23, supports 23 languages and is designed to help companies adopt AI without the risks linked to open-source tools, reflecting growing demand for privacy-conscious, compliant solutions.

The round marks renewed support from chipmakers AMD and Nvidia, who had previously invested in the company.

Salesforce Ventures’ involvement hints at potential integration with enterprise software platforms, while other backers include Radical Ventures, Inovia Capital, PSP Investments, and the Healthcare of Ontario Pension Plan.

The company has also strengthened its leadership, appointing former Meta AI research head Joelle Pineau as Chief AI Scientist, Instagram co-founder Mike Krieger as Chief Product Officer, and ex-Uber executive Saroop Bharwani as Chief Technology Officer for Applied R&D.

Cohere intends to use the funding to advance agentic AI, systems capable of performing tasks autonomously, while focusing on security and ethical development.

With over $1.5 billion raised since its 2019 founding, the company targets adoption in regulated sectors such as healthcare and finance.

The investment comes amid a broader surge in AI spending, with industry leaders betting that secure, customisable AI will become essential for enterprise operations.

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MIT AI creates antibiotics to tackle resistant bacteria

MIT researchers have used generative AI to design novel antibiotics targeting drug-resistant bacteria such as gonorrhea and MRSA. Laboratory tests show the compounds kill bacteria without harming human cells, marking a potential breakthrough in antibiotic development.

The AI system analysed over 36 million possible compounds, generating entirely new molecules with mechanisms that bypass existing resistance. Unlike traditional methods, this approach enables faster discovery, reducing drug development timelines from years to months.

Drug resistance is a growing global threat, with the World Health Organisation predicting 10 million annual deaths by 2050 if unchecked. MIT’s AI bypasses resistance, clearing infections in lab and animal tests with minimal toxicity.

Beyond antibiotics, this achievement highlights the broader potential of AI in pharmaceutical research. Smaller biotech firms could leverage AI for rapid drug design, reducing costs and opening new pathways for addressing urgent medical challenges.

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Chinese researchers advance atom-based quantum computing with massive atom array

Chinese physicist Pan Jianwei’s team created the world’s largest atom array, arranging over 2,000 rubidium atoms for quantum computing. The breakthrough at the University of Science and Technology of China could enable atom-based quantum computers to scale to tens of thousands of qubits.

Researchers used AI and optical tweezers to position all atoms simultaneously, completing the array in 60 milliseconds. The system achieved 99.97 percent accuracy for single-qubit operations and 99.5 percent for two-qubit operations, with 99.92 percent accuracy in qubit state detection.

Atom-based quantum computing is more promising for its stability and control than superconducting circuits or trapped ions. Until now, arrays were limited to a few hundred atoms, as moving each into position individually was slow and challenging.

Future work aims to expand array sizes further using stronger lasers and faster light modulators. Researchers hope that perfectly arranging tens of thousands of atoms leads to fully reliable and scalable quantum computers.

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