Cybersecurity sector sees busy July for mergers

July witnessed a significant surge in cybersecurity mergers and acquisitions (M&A), spearheaded by Palo Alto Networks’ announcement of its definitive agreement to acquire identity security firm CyberArk for an estimated $25 billion.

The transaction, set to be the second-largest cybersecurity acquisition on record, signals Palo Alto’s strategic entry into identity security.

Beyond this significant deal, Palo Alto Networks also completed its purchase of AI security specialist Protect AI. The month saw widespread activity across the sector, including LevelBlue’s acquisition of Trustwave to create the industry’s largest pureplay managed security services provider.

Zurich Insurance Group, Signicat, Limerston Capital, Darktrace, Orange Cyberdefense, SecurityBridge, Commvault, and Axonius all announced or finalised strategic cybersecurity acquisitions.

The deals highlight a strong market focus on AI security, identity management, and expanding service capabilities across various regions.

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Delta’s personalised flight costs under scrutiny

Delta Air Lines’ recent revelation about using AI to price some airfares is drawing significant criticism. The airline aims to increase AI-influenced pricing to 20 per cent of its domestic flights by late 2025.

While Delta’s president, Glen Hauenstein, noted positive results from their Fetcherr-supplied AI tool, industry observers and senators are voicing concerns. Critics worry that AI-driven pricing, similar to rideshare surge models, could lead to increased fares for travellers and raise serious data privacy issues.

Senators like Ruben Gallego, Mark Warner, and Richard Blumenthal, highlighted fears that ‘surveillance pricing’ could utilise extensive personal data to estimate a passenger’s willingness to pay.

Despite Delta’s spokesperson denying individualised pricing based on personal information, AI experts suggest factors like device type and Browse behaviour are likely influencing prices, making them ‘deeply personalised’.

Different travellers could be affected unevenly. Bargain hunters with flexible dates might benefit, but business travellers and last-minute bookers may face higher costs. Other airlines like Virgin Atlantic also use Fetcherr’s technology, indicating a wider industry trend.

Pricing experts like Philip Carls warn that passengers won’t know if they’re getting a fair deal, and proving discrimination, even if unintended by AI, could be almost impossible.

American Airlines’ CEO, Robert Isom, has publicly criticised Delta’s move, stating American won’t copy the practice, though past incidents show airlines can adjust fares based on booking data even without AI.

With dynamic pricing technology already permitted, experts anticipate lawmakers will soon scrutinise AI’s role more closely, potentially leading to new transparency mandates.

For now, travellers can try strategies like using incognito mode, clearing cookies, or employing a VPN to obscure their digital footprint and potentially avoid higher AI-driven fares.

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OpenAI and Nscale to build an AI super hub in Norway

OpenAI has revealed its first European data centre project in partnership with British startup Nscale, selecting Norway as the location for what is being called ‘Stargate Norway’.

The initiative mirrors the company’s ambitious $500 billion US ‘Stargate’ infrastructure plan and reflects Europe’s growing demand for large-scale AI computing capacity.

Nscale will lead the development of a $1 billion AI gigafactory in Norway, with engineering firm Aker matching the investment. These advanced data centres are designed to meet the heavy processing requirements of cutting-edge AI models.

OpenAI expects the facility to deliver 230MW of computing power by the end of 2026, making it a significant strategic foothold for the company on the continent.

Sam Altman, CEO of OpenAI, stated that Europe needs significantly more computing to unlock AI’s full potential for researchers, startups, and developers. He said Stargate Norway will serve as a cornerstone for driving innovation and economic growth in the region.

Nscale confirmed that Norway’s AI ecosystem will receive priority access to the facility, while remaining capacity will be offered to users across the UK, Nordics and Northern Europe.

The data centre will support 100,000 of NVIDIA’s most advanced GPUs, with long-term plans to scale as demand grows.

The move follows broader European efforts to strengthen AI infrastructure, with the UK and France pushing for major regulatory and funding reforms.

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TikTok adopts crowd‑sourced verification tool to combat misinformation

TikTok has rolled out Footnotes in the United States, its crowd‑sourced debunking initiative to supplement existing misinformation controls.

Vetted contributors will write and rate explanatory notes beneath videos flagged as misleading or ambiguous. If a note earns broad support, it becomes visible to all US users.

The system uses a ‘bridging‑based’ ranking framework to encourage agreement between users with differing viewpoints, making the process more robust and reducing partisan bias. Initially launched as a pilot, the platform has already enlisted nearly 80,000 eligible US users.

Footnotes complements TikTok’s integrity setup, including automated detection, human moderation, and partnerships with fact‑checking groups like AFP. Platform leaders note that effectiveness improves as contributors engage more across various topics.

Past research shows comparable crowd‑sourced systems often struggle to publish most submissions, with fewer than 10% of Notes appearing publicly on other platforms. Concerns remain over the system’s scalability and potential misuse.

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Australian companies unite cybersecurity defences to combat AI threats

Australian companies are increasingly adopting unified, cloud-based cybersecurity systems as AI reshapes both threats and defences.

A new report from global research firm ISG reveals that many enterprises are shifting away from fragmented, uncoordinated tools and instead opting for centralised platforms that can better detect and counter sophisticated AI-driven attacks.

The rapid rise of generative AI has introduced new risks, including deepfakes, voice cloning and misinformation campaigns targeting elections and public health.

In response, organisations are reinforcing identity protections and integrating AI into their security operations to improve both speed and efficiency. These tools also help offset a growing shortage of cybersecurity professionals.

After a rushed move to the cloud during the pandemic, many businesses retained outdated perimeter-focused security systems. Now, firms are switching to cloud-first strategies that target vulnerabilities at endpoints and prevent misconfigurations instead of relying on legacy solutions.

By reducing overlap in systems like identity management and threat detection, businesses are streamlining defences for better resilience.

ISG also notes a shift in how companies choose cybersecurity providers. Firms like IBM, PwC, Deloitte and Accenture are seen as leaders in the Australian market, while companies such as TCS and AC3 have been flagged as rising stars.

The report further highlights growing demands for compliance and data retention, signalling a broader national effort to enhance cyber readiness across industries.

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Alignment Project to tackle safety risks of advanced AI systems

The UK’s Department for Science, Innovation and Technology (DSIT) has announced a new international research initiative aimed at ensuring future AI systems behave in ways aligned with human values and interests.

Called the Alignment Project, the initiative brings together global collaborators including the Canadian AI Safety Institute, Schmidt Sciences, Amazon Web Services (AWS), Anthropic, Halcyon Futures, the Safe AI Fund, UK Research and Innovation, and the Advanced Research and Invention Agency (ARIA).

DSIT confirmed that the project will invest £15 million into AI alignment research – a field concerned with developing systems that remain responsive to human oversight and follow intended goals as they become more advanced.

Officials said this reflects growing concerns that today’s control methods may fall short when applied to the next generation of AI systems, which are expected to be significantly more powerful and autonomous.

This positioning reinforces the urgency and motivation behind the funding initiative, before going into the mechanics of how the project will work.

The Alignment Project will provide funding through three streams, each tailored to support different aspects of the research landscape. Grants of up to £1 million will be made available for researchers across a range of disciplines, from computer science to cognitive psychology.

A second stream will provide access to cloud computing resources from AWS and Anthropic, enabling large-scale technical experiments in AI alignment and safety.

The third stream focuses on accelerating commercial solutions through venture capital investment, supporting start-ups that aim to build practical tools for keeping AI behaviour aligned with human values.

An expert advisory board will guide the distribution of funds and ensure that investments are strategically focused. DSIT also invited further collaboration, encouraging governments, philanthropists, and industry players to contribute additional research grants, computing power, or funding for promising start-ups.

Science, Innovation and Technology Secretary Peter Kyle said it was vital that alignment research keeps pace with the rapid development of advanced systems.

‘Advanced AI systems are already exceeding human performance in some areas, so it’s crucial we’re driving forward research to ensure this transformative technology is behaving in our interests,’ Kyle said.

‘AI alignment is all geared towards making systems behave as we want them to, so they are always acting in our best interests.’

The announcement follows recent warnings from scientists and policy leaders about the risks posed by misaligned AI systems. Experts argue that without proper safeguards, powerful AI could behave unpredictably or act in ways beyond human control.

Geoffrey Irving, chief scientist at the AI Safety Institute, welcomed the UK’s initiative and highlighted the need for urgent progress.

‘AI alignment is one of the most urgent and under-resourced challenges of our time. Progress is essential, but it’s not happening fast enough relative to the rapid pace of AI development,’ he said.

‘Misaligned, highly capable systems could act in ways beyond our ability to control, with profound global implications.’

He praised the Alignment Project for its focus on international coordination and cross-sector involvement, which he said were essential for meaningful progress.

‘The Alignment Project tackles this head-on by bringing together governments, industry, philanthropists, VC, and researchers to close the critical gaps in alignment research,’ Irving added.

‘International coordination isn’t just valuable – it’s necessary. By providing funding, computing resources, and interdisciplinary collaboration to bring more ideas to bear on the problem, we hope to increase the chance that transformative AI systems serve humanity reliably, safely, and in ways we can trust.’

The project positions the UK as a key player in global efforts to ensure that AI systems remain accountable, transparent, and aligned with human intent as their capabilities expand.

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Scientists use quantum AI to solve chip design challenge

Scientists in Australia have used quantum machine learning to model semiconductor properties more accurately, potentially transforming how microchips are designed and manufactured.

The hybrid technique combines AI with quantum computing to solve a long-standing challenge in chip production: predicting electrical resistance where metal meets semiconductor.

The Australian researchers developed a new algorithm, the Quantum Kernel-Aligned Regressor (QKAR), which uses quantum methods to detect complex patterns in small, noisy datasets, a common issue in semiconductor research.

By improving how engineers predict Ohmic contact resistance, the approach could lead to faster, more energy-efficient chips. It also offers real-world compatibility, meaning it can eventually run on existing quantum machines as the hardware matures.

The findings highlight the growing role of quantum AI in hardware design and suggest the method could be adopted in commercial chip production in the near future.

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Alibaba launches Wan2.2 AI for text and image to video generation

Alibaba and Zhipu AI have unveiled new open-source models as China intensifies its efforts to compete with the US in AI development. Alibaba’s Wan2.2 is being promoted as the first large video generation model using a Mixture-of-Experts (MoE) architecture in the open-source space.

The Wan2.2 series includes models for generating video from text and images, supporting hybrid capabilities for advanced multimedia applications. MoE architecture allows these models to use less computing power by dividing tasks among specialised sub-networks.

Zhipu, one of China’s leading AI firms, launched the GLM-4.5 and GLM-4.5-Air models with up to 355 billion parameters, built on a self-developed architecture. The GLM-4.5 model ranked third globally and first among open-source models across 12 performance benchmarks.

China’s open-source ecosystem is expanding rapidly, with Zhipu’s models amassing over 40 million downloads and Alibaba’s Qwen series producing hundreds of derivatives. Industry momentum reflects a strategic shift towards wider adoption, improved efficiency and greater international reach.

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UAE partnership boosts NeOnc’s clinical trial programme

Biotech firm NeOnc Technologies has gained rapid attention after going public in March 2025 and joining the Russell Microcap Index just months later. The company focuses on intranasal drug delivery for brain cancer, allowing patients to administer treatment at home and bypass the blood-brain barrier.

NeOnc’s lead treatment is in Phase 2A trials for glioblastoma patients and is already showing extended survival times with minimal side effects. Backed by a partnership with USC’s Keck Medical School, the company is also expanding clinical trials to the Middle East and North Africa under US FDA standards.

A $50 million investment deal with a UAE-based firm is helping fund this expansion, including trials run by Cleveland Clinic through a regional partnership. The trials are expected to be fully enrolled by September, with positive preliminary data already being reported.

AI and quantum computing are central to NeOnc’s strategy, particularly in reducing risk and cost in trial design and drug development. As a pre-revenue biotech, the company is betting that innovation and global collaboration will carry it to the next stage of growth.

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Google backs EU AI Code but warns against slowing innovation

Google has confirmed it will sign the European Union’s General Purpose AI Code of Practice, joining other companies, including major US model developers.

The tech giant hopes the Code will support access to safe and advanced AI tools across Europe, where rapid adoption could add up to €1.4 trillion annually to the continent’s economy by 2034.

Kent Walker, Google and Alphabet’s President of Global Affairs, said the final Code better aligns with Europe’s economic ambitions than earlier drafts, noting that Google had submitted feedback during its development.

However, he warned that parts of the Code and the broader AI Act might hinder innovation by introducing rules that stray from EU copyright law, slow product approvals or risk revealing trade secrets.

Walker explained that such requirements could restrict Europe’s ability to compete globally in AI. He highlighted the need to balance regulation with the flexibility required to keep pace with technological advances.

Google stated it will work closely with the EU’s new AI Office to help shape a proportionate, future-facing approach.

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