Future of work

Ant Group launches trillion-parameter AI model Ling-1T

Ant Group has unveiled its Ling AI model family, introducing Ling-1T, a trillion-parameter large language model that has been open-sourced for public use.

The Ling family now includes three main series: the Ling non-thinking models, the Ring thinking models, and the multimodal Ming models.

Ling-1T delivers state-of-the-art performance in code generation, mathematical reasoning, and logical problem-solving, achieving 70.42% accuracy on the 2025 AIME benchmark.

A model that combines efficient inference with strong reasoning capabilities, marking a major advance in AI development for complex cognitive tasks.

Company’s Chief Technology Officer, He Zhengyu, said that Ant Group views AGI as a public good that should benefit society.

The release of Ling-1T and the earlier Ring-1T-preview underscores Ant Group’s commitment to open, collaborative AI innovation and the development of inclusive AGI technologies.

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Amazon launches Quick Suite for agentic AI in business

Amazon has launched Quick Suite, an AI-powered workspace that delivers fast insights and simplifies business operations. The platform gathers data from Slack, Salesforce, Snowflake, other databases, and the public internet, providing answers from single points to full research projects.

Quick Suite enables users to move seamlessly from insights to action, integrating with applications such as Salesforce, Jira, and ServiceNow. It automates tasks from daily routines, like responding to RFPs, to complex processes such as invoice handling, while keeping all data secure and private.

The platform is simple to deploy, with AWS administrators able to activate it in a few steps. New customers get a 30-day free trial for up to 25 users, with Quick Suite available in key AWS regions and expansion planned.

Quick Suite aims to enhance productivity and decision-making by combining AI-driven research, chat, and automation capabilities in one workspace, enabling businesses to act on insights faster than ever before.

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MIT creates AI tool to build virtual worlds for robots

Researchers at MIT’s Computer Science and AI Laboratory have developed a new AI system that can build realistic virtual environments for training robots. The tool, called steerable scene generation, creates kitchens, restaurants and living rooms filled with 3D objects where robots interact with the physical world.

The system uses a diffusion model guided by Monte Carlo tree search to produce scenes that follow real-world physics. Unlike traditional simulations, it can accurately position objects and avoid visual errors such as items overlapping or floating unrealistically.

By generating millions of unique, lifelike environments, the system can dramatically increase the training data available for robotic foundation models. Robots trained in these AI settings can practise everyday actions like stacking plates or placing cutlery with greater precision.

The researchers say the technique allows robots to learn more efficiently without the cost or limits of real-world testing. Future work aims to include movable objects and internet-sourced assets to make the simulations even more dynamic and diverse.

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Microsoft boosts AI leadership with NVIDIA GB300 NVL72 supercomputer

Microsoft Azure has launched the world’s first NVIDIA GB300 NVL72 supercomputing cluster, explicitly designed for OpenAI’s large-scale AI workloads.

The new NDv6 GB300 VM series integrates over 4,600 NVIDIA Blackwell Ultra GPUs, representing a significant step forward in US AI infrastructure and innovation leadership.

Each rack-scale system combines 72 GPUs and 36 Grace CPUs, offering 37 terabytes of fast memory and 1.44 exaflops of FP4 performance.

A configuration that supports complex reasoning and multimodal AI systems, achieving up to five times the throughput of the previous NVIDIA Hopper architecture in MLPerf benchmarks.

The cluster is built on NVIDIA’s Quantum-X800 InfiniBand network, delivering 800 Gb/s of bandwidth per GPU for unified, high-speed performance.

Microsoft and NVIDIA’s long-standing collaboration has enabled a system capable of powering trillion-parameter models, positioning Azure at the forefront of the next generation of AI training and deployment.

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Quantum innovations promise faster, cleaner, more efficient technologies

The Nobel Prize in Physics has spotlighted quantum mechanics’ growing role in shaping a smarter, more sustainable future. Such advances are reshaping technology across communications and energy.

Researchers are finding new ways to use quantum effects to boost efficiency. Quantum computing could ease AI’s power demands, while novel production methods may transform energy systems.

A Institute of Science Tokyo team has built a quantum energy harvester that captures waste heat and converts it into power, bypassing traditional thermodynamic limits.

MIT has observed frictionless electron movement, and new quantum batteries promise faster charging by storing energy in photons. The breakthroughs could enable cleaner and more efficient technologies.

Quantum advances offer huge opportunities but also risks, including threats to encryption. Responsible governance will be crucial to ensure these technologies serve the public good.

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Nvidia to invest $2bn in Elon Musk’s xAI

Nvidia is reportedly investing up to $2bn in Elon Musk’s AI company, xAI, as part of a $20bn funding round aimed at scaling its Colossus 2 data centre in Memphis. The capital will be used to buy Nvidia GPUs, essential for powering xAI’s next generation of AI models.

The funding package combines about $7.5bn in equity and up to $12.5bn in debt, structured through a special purpose vehicle that will lease the hardware to xAI over five years. The debt is secured by the GPUs themselves, allowing investors to recover their costs through chip rentals.

xAI faces mounting financial pressure, with reports indicating a cash burn of around $1bn per month. The firm raised $10bn earlier in the year and continues to draw on capital from Musk’s other ventures, including SpaceX.

The move comes amid an intense funding surge across the AI sector, as OpenAI, Meta and Oracle also announce multi-billion-dollar investments in infrastructure. Nvidia’s latest deal with xAI further cements its position at the centre of the global AI hardware ecosystem.

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OSCE warns AI threatens freedom of thought

The OSCE has launched a new publication warning that rapid progress in AI threatens the fundamental human right to freedom of thought. The report, Think Again: Freedom of Thought in the Age of AI, calls on governments to create human rights-based safeguards for emerging technologies.

Speaking during the Warsaw Human Dimension Conference, Professor Ahmed Shaheed of the University of Essex said that freedom of thought underpins most other rights and must be actively protected. He urged states to work with ODIHR to ensure AI development respects personal autonomy and dignity.

Experts at the event said AI’s growing influence on daily life risks eroding individuals’ ability to form independent opinions. They warned that manipulation of online information, targeted advertising, and algorithmic bias could undermine free thought and democratic participation.

ODIHR recommends states to prevent coercion, discrimination, and digital manipulation, ensuring societies remain open to diverse ideas. Protecting freedom of thought, the report concludes, is essential to preserving human dignity and democratic resilience in an age shaped by AI.

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European Commission launches Apply AI and AI in Science strategies

Countries are racing to harness AI, and the European Commission has unveiled two strategies to maintain Europe’s competitiveness. Apply AI targets faster adoption across industries and the public sector, while AI in Science focuses on boosting Europe’s research leadership.

Commission President Ursula von der Leyen stated that Europe must shape AI’s future by balancing innovation and safety. The European Commission is mobilising €1 billion to boost adoption in healthcare, manufacturing, energy, defence, and culture, while supporting SMEs.

Measures include creating AI-powered screening centres for healthcare, backing frontier models, and upgrading testing infrastructure. An Apply AI Alliance will unite industry, academia, civil society, and public bodies to coordinate action, while an AI Observatory will monitor sector trends and impacts.

The AI in Science Strategy centres on RAISE, a new virtual institute to pool and coordinate resources for applying AI in research. Investments include €600 million in compute power through Horizon Europe and €58 million for talent networks, alongside plans to double annual AI research funding to over €3 billion.

The EU aims to position itself as a global hub for trustworthy and innovative AI by linking infrastructure, data, skills, and investment. Upcoming events, such as the AI in Science Summit in Copenhagen, will showcase new initiatives as Europe pushes to translate its AI ambitions into tangible outcomes.

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Google invests €5 billion to boost Belgium’s AI infrastructure

The US tech giant, Google, has announced a €5 billion investment in Belgium to strengthen its AI and cloud infrastructure over the next two years.

A plan that includes major expansions of its Saint-Ghislain data centre campuses and the creation of 300 full-time jobs.

The company has also signed agreements with Eneco, Luminus and Renner to develop new onshore wind farms and supply the Belgian grid with clean energy.

Alongside the infrastructure push, Google will fund non-profits to deliver free AI training for low-skilled workers, ensuring broader access to digital skills.

By deepening its presence in Belgium, Google aims to bolster the country’s technological and economic future. The initiative marks one of Europe’s largest AI infrastructure investments, reflecting growing competition to secure leadership in the continent’s digital transformation.

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Alibaba’s Qwen lab launches robotics unit to drive embodied AI

Alibaba Group has established a robotics AI team within its Qwen lab, marking a significant step in its strategy to expand into AI-powered hardware.

However, this move reflects China’s broader push to lead in robotics and embodied intelligence, increasingly driven by generative AI and multimodal foundation models.

Qwen researcher Lin Junyang revealed the creation of the robotics unit on social media, describing it as part of Alibaba’s efforts to move AI from the virtual to the physical world.

The lab’s Qwen series has already achieved global prominence, with seven models ranking among the world’s top ten on Hugging Face, including the multimodal Qwen3-Omni in first place.

Group chairman Joe Tsai recently stressed that success in AI depends less on model scale and more on how rapidly technologies are adopted. He argued that China is focused on cost-effective, open-source AI models that can enable faster integration than the high-cost approach pursued in the US.

Alibaba CEO Eddie Wu Yongming confirmed plans to raise AI infrastructure investment to 380 billion yuan over three years to become a full-stack AI provider.

The company also invests in robotics ventures such as Unitree Robotics and X Square Robot, aligning its expansion with national industrial strategies and the country’s accelerating robotics leadership.

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