Digital cooperation

New ion trap chip paves way for scalable quantum systems

Researchers at the Quantum Systems Accelerator have announced significant progress in building scalable, stable quantum computers focusing on trapped-ion technology.

Their work marks a series of engineering milestones pushing quantum computing toward practical use.

A new ion trap chip can store up to 200 ions and significantly reduces power loss by redesigning its internal layout.

Developed and tested with collaborators at Duke and Cornell in the US, this design allows for the future creation of far larger qubit systems without overheating or energy waste.

At the University of Maryland, a team achieved parallel quantum gate operations using different spatial directions, overcoming prior interference issues.

However, this innovation boosts processing speed and accuracy, offering more efficient handling of time-sensitive quantum tasks.

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Nvidia and Samsung invest in Skild AI, boosting robotics innovation

Nvidia and Samsung are joining a major Series B funding round for Skild AI, a robotics software start-up, with investments of $25 million and $10 million, respectively.

According to Bloomberg, the round, led by SoftBank with a $100 million commitment, is expected to value the company at approximately $4.5 billion.

Skild AI develops foundation models and software designed for various robotic systems, from consumer devices to industrial machines. The company previously raised $300 million in Series A funding in 2023, when it was valued at $1.5 billion.

Samsung’s latest investment reinforces its growing focus on robotics. Earlier this year, it became the largest shareholder in South Korea-based Rainbow Robotics, which is known for its collaborative robots. The company also operates a Future Robotics Office to steer strategic innovation.

For Nvidia, the investment aligns with broader efforts in AI and automation. In March, the chipmaker partnered with General Motors to co-develop AI systems that train next-generation manufacturing models for use in vehicles, factories, and robotics.

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Meta hires top AI talent from Google and Sesame

Meta is assembling a new elite AI research team aimed at developing artificial general intelligence (AGI), luring top talent from rivals including Google and AI voice startup Sesame.

Among the high-profile recruits is Jack Rae, a principal researcher from Google DeepMind, and Johan Schalkwyk, a machine learning lead from Sesame.

Meta is also close to finalising a multibillion-dollar investment in Scale AI, a data-labelling startup led by CEO Alexandr Wang, who is also expected to join the new initiative.

The new group, referred to internally as the ‘superintelligence’ team, is central to CEO Mark Zuckerberg’s plan to close the gap with competitors like Google and OpenAI.

Following disappointment over Meta’s recent AI model, Llama 4, Zuckerberg hopes the newly acquired expertise will help improve future models and expand AI capabilities in areas like voice and personalisation.

Zuckerberg has taken a hands-on approach, personally recruiting engineers and researchers, sometimes meeting with them at his homes in California. Meta is reportedly offering compensation packages worth tens of millions of dollars, including equity, to attract leading AI talent.

The company aims to hire around 50 people for the team and is also seeking a chief scientist to help lead the effort.

The broader strategy involves investing heavily in data, chips, and human expertise — three pillars of advanced AI development. By partnering with Scale AI and recruiting high-profile researchers, Meta is trying to strengthen its position in the AI race.

Meanwhile, rivals like Google are reinforcing their defences, with Koray Kavukcuoglu named as chief AI architect in a new senior leadership role to ensure DeepMind’s technologies are more tightly integrated into Google’s products.

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Quantum cybersecurity goes live in Paris

Orange Business and Toshiba Europe have launched France’s first commercial quantum-safe network service in Paris.

The Orange Quantum Defender, now living in the greater Paris region, aims to shield organisations from cyber threats posed by future quantum computing capabilities.

The service combines Toshiba’s Quantum Key Distribution and Post-Quantum Cryptography technologies to protect sensitive data with a multi-layered approach. A major French financial institution already uses the network to safeguard its critical infrastructure.

After years of testing, the partners confirmed the system works over existing fibre networks, cutting costs and easing enterprise adoption.

Leaders at both companies say the launch marks a turning point in cybersecurity preparedness for the quantum age.

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AI must protect dignity, say US bishops

The US Conference of Catholic Bishops has urged Congress to centre AI policy on human dignity and the common good.

Their message outlines moral principles rather than technical guidance, warning against misuse of technology that may erode truth, justice, or the protection of the vulnerable.

The bishops caution against letting AI replace human moral judgement, especially in sensitive areas like family life, work, and warfare. They express concern about AI deepening inequality and harming those already marginalised without strict oversight.

Their call includes demands for greater transparency, regulation of autonomous weapons, and stronger protections for children and workers in the US.

Rooted in Catholic social teaching, the letter frames AI not as a neutral innovation but as a force that must serve people, not displace them.

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TechNext launches forecasting system to guide R&D strategy

Global R&D spending now exceeds $2 trillion a year, yet many companies still rely on intuition rather than evidence to shape innovation strategies—often at great cost.

TechNext, co-founded by Anuraag Singh and MIT’s Prof. Christopher L. Magee, aims to change that with a newly patented system that delivers data-driven forecasts for technology performance.

Built on large-scale empirical datasets and proprietary algorithms, the system enables organisations to anticipate which technologies are likely to improve most rapidly.

‘R&D has become one of the fastest-growing expenses for companies, yet most decisions still rely on intuition rather than data,’ said Singh. ‘We have been flying blind’

The tool has already drawn attention from major stakeholders, including the United States Air Force, multinational firms, VCs, and think tanks.

By quantifying the future of technologies—from autonomous vehicle perception systems to clean energy infrastructure—TechNext promises to help decision-makers avoid expensive dead ends and focus on long-term winners.

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Meta strikes $15B deal with Scale AI

Meta Platforms is set to acquire a 49 percent stake in Scale AI for nearly $15 billion, marking its largest-ever deal.

CEO Mark Zuckerberg sees The agreement as a significant move to accelerate Meta’s push into AI instead of relying solely on in-house development.

Scale AI, founded in 2016, supplies curated training data to major players such as OpenAI, Google, Microsoft and Meta. The company expects to more than double its revenue in 2025 to around $2 billion.

Once the deal is finalised, Scale AI CEO Alexandr Wang is expected to join Meta’s new AI team focused on developing artificial general intelligence (AGI).

According to Bloomberg, Zuckerberg is hiring around 50 people for a ‘superintelligence’ team.

The effort aligns with Meta’s broader AI plans, including capital expenditure of up to $65 billion in 2025 to expand its AI infrastructure instead of falling behind rivals in the AI race.

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Apple study finds AI fails on complex tasks

A recent study by Apple researchers exposed significant limitations in the capabilities of advanced AI systems and huge reasoning models (LRMs).

Apple’s team suggested this may point to a fundamental limit in how current AI models scale up to general reasoning.

These models, designed to solve complex problems through step-by-step thinking, experienced what the paper called a ‘complete accuracy collapse’ when faced with high-complexity tasks. Even when given an algorithm that should have ensured success, the models failed to deliver correct solutions.

The study found that LRMs performed well with low- and medium-difficulty tasks but deteriorated sharply as the complexity increased.

Rather than increasing their effort as problems became harder, the models reduced their reasoning paradoxically, leading to complete failure.

Experts, including AI researcher Gary Marcus and University of Surrey’s Andrew Rogoyski in the UK, called the findings alarming and indicative of a potential dead end in current AI development.

The study tested systems from OpenAI, Google, Anthropic and DeepSeek, raising serious questions about how close the industry is to achieving AGI.

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OpenAI’s revenue almost doubles to $10 billion

OpenAI has revealed that its annualised revenue has surged to $10 billion as of June 2025, nearly doubling since December 2024, when it stood at $5.5 billion.

The rapid growth is driven by the widespread adoption of its ChatGPT AI models across consumer and business markets, putting the company on course to meet its earlier goal of $12.7 billion in revenue for the whole year.

The $10 billion figure excludes licensing income from Microsoft, a major investor, and some large one-off contracts, according to an OpenAI spokesperson. Despite recording a loss of about $5 billion last year, OpenAI’s impressive revenue scale places it well ahead of many rivals benefiting from the AI boom.

Other players in the AI space are also seeing strong growth. For instance, Anthropic recently surpassed $3 billion in annualised revenue, driven by startup demand using its code-generation models. Meanwhile, OpenAI plans to raise up to $40 billion in new funding, valuing the company at $300 billion.

Since launching ChatGPT over two years ago, OpenAI has expanded its offerings with various subscription plans and services. The company reported 500 million weekly active users as of March 2025, underscoring its dominant position in the AI market.

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XRobotics makes 25,000 pizzas a month with AI

XRobotics, a San Francisco-based startup, is gaining traction in the food tech sector with its compact pizza-making robot, the xPizza Cube. Roughly the size of a washing machine, the machine uses AI to apply sauce, cheese and toppings, producing up to 100 pizzas per hour.

At $1,300 monthly on a three-year lease, it’s designed to fit seamlessly into existing kitchens and support, not replace, staff. Unlike failed predecessors such as Zume, XRobotics has found success by offering assistive rather than disruptive technology.

Their initial, larger model proved impractical, but the current compact version, launched in 2023, now produces 25,000 pizzas each month across an undisclosed number of customer locations. Both small pizzerias and large chains use the robot to cut labour time and improve consistency.

With over 73,000 pizza outlets in the US, XRobotics plans to stay focused on pizza for now. Its founders, self-professed pizza lovers, say customer response has confirmed that a well-targeted tool can significantly impact even the most traditional kitchens.

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