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 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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Under the deal, Microsoft will pay a licensing fee to Harvard. The partnership aims to enhance Microsoft’s Copilot AI assistant by enabling it to provide medical advice that more closely aligns with what a user might receive from a healthcare professional.
So far, Copilot’s underlying models have been powered primarily by OpenAI. But this agreement is part of Microsoft’s broader push to diversify and reduce its dependence on OpenAI’s technology stack.
Dominic King, Microsoft’s vice president of health, has said the goal is for Copilot’s responses to health queries to more accurately reflect what a medical practitioner would say, rather than generic or superficial answers.
Microsoft declined to comment in detail, but the move strengthens Copilot’s differentiation in the health domain, arguably a high-stakes vertical area where accuracy and trustworthiness matter greatly.
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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 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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Researchers are using satellite imagery and AI modelling to map global mining activity and close critical data gaps. Transition minerals, such as lithium and copper, are vital for renewable technologies but often come from ecologically sensitive regions, raising concerns about both environmental and social impacts.
Project lead Victor Maus from the Vienna University of Economics and Business said many new projects overlap with areas of high biodiversity or Indigenous lands. Over half of transition mineral resources are on or near Indigenous or subsistence farming territories, according to earlier studies.
Previous mapping efforts have struggled to document small-scale and informal mining, which remains unregulated despite its impact. Maus’s team compared satellite images of 120,000 square kilometres of mine footprints with the S&P Capital IQ Pro database and found over half missing.
To close these gaps, the team is creating a mining database under the EU-funded Mine the Gap initiative. By combining multispectral, radar, and hyperspectral imagery with AI, they aim to monitor land use, waste generation, and environmental degradation.
Experts say the database could support policymakers and increase transparency. Maus emphasised that global reporting standards are crucial for enhancing accountability and informing decisions on managing the environmental and social impacts of mining.
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Discord has confirmed that official ID images belonging to around 70,000 users may have been exposed in a cyberattack targeting a third-party service provider. The platform itself was not breached, but hackers targeted a company involved in age verification processes.
The leaked data may include personal information, partial credit card details, and conversations with Discord’s customer service agents. No full credit card numbers, passwords, or activity beyond support interactions were affected. Impacted users have been contacted, and law enforcement is investigating.
The platform has revoked the support provider’s access to its systems and has not named the third party involved. Zendesk, a customer service software supplier to Discord, said its own systems were not compromised and denied being the source of the breach.
Discord has rejected claims circulating online that the breach was larger than reported, calling them part of an attempted extortion. The company stated it would not comply with demands from the attackers. Cybercriminals often sell personal information on illicit markets for use in scams.
ID numbers and official documents are especially valuable because, unlike credit card details, they rarely change. Discord previously tightened its age-verification measures following concerns over the misuse of some servers to distribute illegal material.
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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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The European Commission has launched the AI in Science Strategy to position Europe at the forefront of AI-driven research and innovation. RAISE, a virtual European institute, pools AI resources to support scientific research and advance capabilities across Europe.
The strategy aims to attract global talent, provide €600 million from Horizon Europe for computational power, and double annual AI investments to over €3 billion. These measures aim to ensure researchers and startups have access to the infrastructure needed for AI breakthroughs.
It also supports scientists in identifying strategic data gaps, gathering, curating, and integrating datasets essential for AI in science. By doing so, Europe seeks to create a robust, data-driven environment that accelerates innovation across disciplines.
The Apply AI Strategy is also being implemented to encourage AI adoption in key industries and public services. Together with the AI Act Service Desk and AI Continent Action Plan, these initiatives strengthen Europe’s goal to lead in scientific research and industrial AI adoption.
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California has enacted SB 53, offering legal protection to employees reporting AI risks or safety concerns. The law covers companies using large-scale computing for AI model training, focusing on leading developers and exempting smaller firms.
It also mandates transparency, requiring risk mitigation plans, safety test results, and reporting of critical safety incidents to the California Office of Emergency Services (OES).
The legislation responds to calls from industry insiders, including former OpenAI and DeepMind employees, who highlighted restrictive offboarding agreements that silenced criticism and limited public discussion of AI risks.
The new law protects employees who have ‘reasonable cause’ to believe a catastrophic risk exists, defined as endangering 50 lives or causing $1 billion in damages. It allows them to report concerns to regulators, the Attorney General, or management without fear of retaliation.
While experts praise the law as a crucial step, they note its limitations. The protections focus on catastrophic risks, leaving smaller but significant harms unaddressed.
Harvard law professor Lawrence Lessig emphasises that a lower ‘good faith’ standard for reporting would simplify protections for employees, though it is currently limited to internal anonymous channels.
The law reflects growing recognition of the stakes in frontier AI, balancing the need for innovation with safeguards that encourage transparency. Advocates stress that protecting whistleblowers is essential for employees to raise AI concerns safely, even at personal or financial risk.
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