MIT researchers have demonstrated a faster, more energy-efficient cooling technique for scalable trapped-ion quantum chips. The solution addresses a long-standing challenge in reducing vibration-related errors that limit the performance of quantum systems.
The method uses integrated photonic chips with nanoscale antennas that emit tightly controlled light beams. Using polarisation-gradient cooling, the system cools ions to nearly ten times below standard laser limits, and does so much faster.
Unlike conventional trapped-ion systems that depend on bulky external optics, the chip-based design generates stable light patterns directly on the device. The stability improves accuracy and supports scaling to thousands of ions on a single chip.
Researchers say the breakthrough lays the groundwork for more reliable quantum operations and opens new possibilities for advanced ion control, bringing practical, large-scale quantum computing closer to reality.
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The European Commission has announced €307.3 million ($356 million) in new funding to advance digital technologies across the EU. The initiative aims to strengthen Europe’s innovation, competitiveness, and strategic digital autonomy.
A total of €221.8 million will support projects in AI, robotics, quantum technologies, photonics, and virtual worlds. One focus is the development of trustworthy AI services and innovative data solutions to enhance EU digital leadership.
More than €40 million has been allocated to the Open Internet Stack Initiative, which aims to advance end-user applications and core stack technologies, boosting European digital sovereignty. A second call of €85.5 million will target open strategic autonomy in emerging digital technologies and raw materials.
The funding is open to businesses, academic institutions, public administrations, and other entities from EU member states and partner countries. Priority areas include next-generation AI agents, industrial and service robotics, and new materials with enhanced sensing capabilities.
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Innovations across China are moving rapidly from laboratories into everyday use, spanning robotics, autonomous vehicles and quantum computing. Airports, hotels and city streets are increasingly becoming testing grounds for advanced technologies.
In Hefei, humanoid cleaning robots developed by local start-up Zerith are already operating in public venues across major cities. The company scaled from prototype to mass production within a year, securing significant commercial orders.
Beyond robotics, frontier research is finding industrial applications in energy, healthcare and manufacturing. Advances from fusion research and quantum mechanics are being adapted for cancer screening, battery safety and precision measurement.
Policy support and investment are accelerating this transition from research to market. National planning and local funding initiatives aim to turn scientific breakthroughs into scalable technologies with global reach.
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Canadian quantum computing company Photonic has raised $130 million in the first close of a new investment round led by Planet First Partners. New backers include RBC and TELUS, alongside returning investors.
The funding brings Photonic’s total capital raised to $271 million and supports the development of fault-tolerant quantum systems. The company combines silicon-based qubits with built-in photonic connectivity.
Photonic’s entanglement-first architecture is designed to scale across existing global telecom networks. The approach aims to enable large, distributed quantum computers rather than isolated machines.
Headquartered in Vancouver, Photonic plans to utilise the investment to accelerate key product milestones and expand its team. Investors see strong potential across finance, sustainability, telecommunications and security sectors.
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AI is accelerating the creation of digital twins by reducing the time and labour required to build complex models. Consulting firm McKinsey says specialised virtual replicas can take six months or more to develop, but generative AI tools can now automate much of the coding process.
McKinsey analysts say AI can structure inputs and synthesise outputs for these simulations, while the models provide safe testing environments for AI systems. Together, the technologies can reduce costs, shorten development cycles, and accelerate deployment.
Quantum Elements, a startup backed by QNDL Participations and the USC Viterbi School of Engineering, is applying this approach to quantum computing. Its Constellation platform combines AI agents, natural language tools, and simulation software.
The company says quantum systems are hard to model because qubits behave differently across hardware types such as superconducting circuits, trapped ions, and photonics. These variations affect stability, error rates, and performance.
By using digital twins, developers can test algorithms, simulate noise, and evaluate error correction without building physical hardware. Quantum Elements says this can cut testing time from months to minutes.
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Taiwan aims to train 500,000 AI professionals by 2040, backed by a NT$100 billion (US$31.6 billion) government venture fund. President Lai Ching-te announced the 2026 AI talent forum in Taipei.
The government’s 10-year AI plan includes a national computing centre and the development of technologies such as silicon photonics, quantum computing, and robotics. President Lai said that national competitiveness depends on both chipmaking and citizens’ ability to utilise AI across various disciplines.
To achieve these goals, AI training courses are being introduced for public sector employees, and students are being encouraged to acquire AI skills. The initiative aims to foster cooperation between government, industry, and academia to drive economic transformation.
With a larger pool of AI professionals, Taiwan hopes to help small and medium-sized enterprises accelerate digital upgrades, enhance innovation, and strengthen the nation’s global competitiveness in emerging technologies.
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Portugal has announced a €400 million investment in AI over the period 2026-2030, primarily funded by European programmes. The National Artificial Intelligence Agenda (ANIA) and its Action Plan (PAANIA) aim to strengthen Portugal’s position in AI research, industry, and innovation.
The government predicts AI could boost the country’s GDP by €18-22 billion in the next decade. Officials highlight Portugal’s growing technical talent pool, strong universities and research centres, renewable energy infrastructure, and a dynamic start-up ecosystem as key advantages.
Key projects include establishing AI gigafactories and supercomputing facilities to support research, SMEs, and start-ups, alongside a National Data Centre Plan aimed to simplifying licensing and accelerating the sector.
Early investments of €10 million target AI applications in public administration, with a total of €25 million planned.
Sectoral AI Centres will focus on healthcare and industrial robotics, leveraging AI to enhance patient care, improve efficiency, and support productivity, competitiveness, and the creation of skilled jobs.
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Chinese researchers have reported a significant advance in quantum computing using a superconducting system. The Zuchongzhi 3.2 computer reached the fault-tolerant threshold, at which point error correction improves stability.
Pan Jianwei led the research and marks only the second time globally that this threshold has been achieved, following earlier work by Google. The result positions China as the first country outside the United States to demonstrate fault tolerance in a superconducting quantum system.
Unlike Google’s approach, which relies on extensive hardware redundancy, the Chinese team used microwave-based control to suppress errors. Researchers say this method may offer a more efficient path towards scalable quantum computing by reducing system complexity.
The breakthrough addresses a central challenge in quantum computing: qubit instability and the accumulation of undetected errors. Effective error management is crucial for developing larger systems that can maintain reliable quantum states over time.
While practical applications remain distant, researchers describe the experiment as a significant step in solving a foundational problem in quantum system design. The results highlight the growing international competition in the quest for scalable, fault-tolerant quantum computers.
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Researchers at Lomonosov Moscow State University have developed a 72-qubit quantum computer prototype based on single neutral rubidium atoms. It marks the third Russian quantum computer to surpass the 70-qubit milestone.
The achievement was announced by Rosatom Quantum Technologies and highlights progress in reliable quantum operations.
The atom-based prototype features three zones: one for computing and two for storage and readout. Experiments have demonstrated two-qubit logical operations with 94% accuracy, enabling practical testing and development of quantum algorithms.
Scientists stress that lower error rates are vital for scaling quantum computers to solve complex industrial and financial problems. The work also supports Russia’s technological sovereignty and strengthens the competitiveness of domestic enterprises.
The project actively involves young researchers, graduate students, and undergraduates alongside leading specialists, ensuring the next generation gains hands-on experience in one of Russia’s most significant scientific initiatives.
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Scientists have developed an AI model capable of simulating complex fusion plasma in seconds, a process that previously took hours or even days. The tool, named GyroSwin, offers a faster, more cost-effective approach to designing future fusion power plants.
Traditional five-dimensional plasma simulations, which account for spatial dimensions and particle velocities, require immense supercomputing power and long computation times.
GyroSwin uses AI to learn plasma dynamics, producing accurate simulations up to 1,000 times faster than conventional methods. Faster modelling will help optimise turbulence management, a key challenge in achieving practical fusion energy.
The AI tool preserves crucial physical information, such as fluctuation scales and sheared flows, ensuring simulations remain physically interpretable.
Researchers at UK Atomic Energy Authority, Johannes Kepler University, and Emmi AI believe GyroSwin could transform the design and operation of next-generation fusion plants, including the UK’s STEP project.
GyroSwin demonstrates how AI and supercomputing can accelerate the path towards clean, abundant fusion energy while reducing the cost and complexity of plasma modelling, paving the way for a new era of fusion innovation.
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