Google is seeking permission to bundle its Gemini AI application with long-standing services such as YouTube and Maps, even as US regulators press for restrictions to curb its dominance in search.
At a recent court hearing, Google’s lawyer John Schmidtlein told Judge Amit Mehta that tying Gemini to its core apps is vital to delivering a consistent AI experience across its ecosystem.
He insisted the courts should not treat the AI market as a settled domain subject to old rules, and claimed that neither Maps nor YouTube is a monopoly product justifying special constraints.
The government’s position is more cautious. During the hearing, Judge Mehta questioned whether allowing Google to require its AI app to be installed to access Maps or YouTube would give it unfair leverage over competitors, mirroring past practices that regulators found harmful in search and browser markets.
This moment frames a broader tension: how antitrust frameworks will adapt (or not) when dominant platforms seek to integrate generative AI across many services. The outcome could shape the future of bundling practices and interoperability in AI ecosystems.
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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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Intel has revealed its next-gen client and server processors using Intel 18A, the most advanced US-made semiconductor node. The new Intel Core Ultra 3 (Panther Lake) and Xeon 6+ (Clearwater Forest) promise major performance and efficiency gains, with production already underway at Fab 52 in Arizona.
Panther Lake introduces a scalable multi-chiplet architecture for consumer and commercial AI PCs, gaming devices, and edge applications. It offers over 50% faster CPU and GPU performance, up to 180 TOPS for AI, and new robotics AI capabilities.
High-volume production begins later this year, with broad availability expected in January 2026.
Clearwater Forest is designed for hyperscale data centres, cloud providers, and telcos. Built entirely on Intel 18A, the Xeon 6+ processor offers up to 288 E-cores, a 17% IPC uplift, and improved density, throughput, and power efficiency.
It is set to launch in the first half of 2026.
Intel 18A underpins at least three upcoming generations of client and server products, with key innovations including RibbonFET transistors, PowerVia backside power delivery, and Foveros advanced packaging.
Fab 52 further strengthens the company’s US manufacturing leadership, supporting domestic production and strategic supply chain resilience.
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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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The US has approved its first export licences for Nvidia’s advanced AI chips destined for the United Arab Emirates, marking a concrete step in the bilateral AI partnership announced earlier in 2025.
These licences come under the oversight of the US Commerce Department’s Bureau of Industry and Security, aligned with a formal agreement between the two nations signed in May.
In return, the UAE has committed to investing in the United States, making this a two-way deal. The licences do not cover every project yet: some entities, such as the AI firm G42, are currently excluded from the approved shipments.
The UAE sees the move as crucial to its AI push under Vision 2031, particularly for funding data centre expansion and advancing research in robotics and intelligent systems. Nvidia already collaborates with Abu Dhabi’s Technology Innovation Institute (TII) in a joint AI and robotics lab.
Challenges remain. Some US officials cite national security risks, especially given the UAE’s ties and potential technology pathways to third countries.
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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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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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