Capacity development Archives | Page 2 of 302

Data centres drive LG’s integrated AI infrastructure push

AI infrastructure is becoming a central battleground for growth, with LG Group accelerating its push into AI data centres and energy storage systems under its ‘One LG’ strategy.

The initiative brings together key affiliates to deliver integrated solutions for AI data centres. LG Electronics provides cooling systems, LG Energy Solution handles power infrastructure, including ESS and UPS, while LG Uplus and LG CNS oversee design, construction, and operations.

The strategy comes as global demand for AI data centres surges, driven by energy-intensive workloads and rising electricity constraints. Expanding storage capacity has become critical, with the US expected to add over 24 gigawatts of energy storage capacity in 2026 alone.

LG Electronics is focusing on advanced cooling technologies, including large air-cooled chillers and liquid-cooling systems, to manage the intense heat generated by GPU-intensive AI workloads. The company has also expanded into immersion cooling through partnerships, aiming to achieve efficiency gains in next-generation facilities.

Meanwhile, LG Energy Solution is strengthening its role in power infrastructure, scaling ESS production across North America, and securing major contracts. Through integrated battery and software solutions, the company is positioning itself to meet growing demand for stable, high-capacity energy systems supporting AI operations.

On the networking side, LG Uplus is developing low-latency infrastructure and AI-driven data centre management systems to optimise performance and energy use in real time. Together, these efforts highlight LG’s ambition to become a full-stack provider in the rapidly expanding AI data centre ecosystem.

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NVIDIA Isaac powers generalist specialist robots at scale

A new class of robots is emerging, combining broad adaptability with task-specific precision as developers move toward generalist specialist systems. Within this shift, NVIDIA Isaac is enabling integrated workflows that connect data generation, simulation, training, and deployment across robotics pipelines.

NVIDIA Isaac unifies robotics development across these stages, integrating cloud-to-robot workflows that allow developers to build, test, and scale systems more efficiently across both real and simulated environments.

A key driver is the growing reliance on synthetic data, which allows developers to simulate rare or hazardous scenarios that are difficult to capture in the real world. NVIDIA Isaac supports this through tools such as Omniverse-based simulation and teleoperation pipelines, helping convert real-world signals into scalable training datasets and accelerating development cycles.

The platform also enables advanced robot training using reasoning vision-language-action models, which allow machines to perceive, interpret, and act across complex environments. With frameworks like Isaac Lab and integrated physics engines, NVIDIA Isaac enables robots to train across thousands of parallel simulations, significantly reducing time, cost, and risk compared to real-world training.

Once trained, NVIDIA Isaac supports deployment across edge AI systems, including the Jetson platform, while maintaining consistency between simulation and real-world performance. Combined with modular workflows and open frameworks, the platform is positioning itself as a core foundation for scalable, next-generation robotics.

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AI standards and regulation struggle to keep pace with global innovation

Global efforts to regulate AI are accelerating, but innovation continues to outpace formal rules. Policymakers and industry leaders are increasingly turning to standards to help bridge compliance gaps.

At the AI Standards Hub Global Summit, experts highlighted how technical standards support responsible AI development. These tools are seen as essential for scaling AI safely while regulatory frameworks continue to evolve.

Differences across regions remain significant, with the EU relying on formal regulation and the US leaning on flexible standards. This fragmented landscape is raising concerns over compliance costs and barriers to cross-border deployment.

Experts stress that standards must evolve alongside AI while aligning with global frameworks and enforcement efforts. Without coordination, inconsistencies could limit innovation and weaken trust in AI systems.

Calls are growing for shared definitions, measurable benchmarks and stronger international cooperation. Stakeholders argue that aligning standards with regulation will be critical for future AI governance.

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Workplace adoption of AI varies widely in the EU

Generative AI is becoming increasingly common in Europe, with around a third of people using the tools in 2025. Fewer than half of these users apply AI professionally, leaving workplace adoption at just 15%.

Usage varies greatly across the continent. Norway recorded the highest rate at 35.4%, followed closely by Switzerland at 34.4%. Northern and Western European nations generally lead, while Eastern and Southeastern countries report much lower rates, with Hungary at only 1.3%.

Among the EU’s largest economies, France and Spain have the highest workplace AI use, at 18.4% and 17.9%, respectively, while Germany is slightly above average at 15.8%, and Italy lags at 8%. Experts note that adoption depends on skills, trust, governance, and the structure of national economies.

The gap between personal and professional AI use highlights growth potential. As AI agents continue spreading across workplaces, adoption rates are expected to rise, particularly in industries suited to generative AI, such as ICT, research, media, and knowledge-based sectors.

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Meta’s metaverse collapses as Horizon Worlds shuts down on Quest

Meta will shut down Horizon Worlds on its Quest headsets, ending its flagship virtual reality (VR) platform and marking a clear retreat from its metaverse ambitions. The app will be removed from the Quest store on 31 March and discontinued in VR by 15 June, continuing only as a mobile service.

Horizon Worlds, launched in 2021, was central to Meta’s rebranding from Facebook and its vision of a fully immersive virtual environment. Despite billions in investment and high-profile partnerships, the platform failed to attract a large user base and struggled with design limitations and weak engagement.

Reality Labs, the division behind the metaverse push, has accumulated nearly $80 billion in losses since 2020, including more than $6 billion in a single quarter. Recent layoffs affecting around 10 percent of the VR workforce, along with the shutdown of related projects, underscore a broader pullback.

Competition and shifting priorities have accelerated the decline. Rival platforms such as VRChat maintained stronger communities, while Meta increasingly redirected resources toward AI and hardware, including its Ray-Ban smart glasses.

Although Meta says it remains committed to VR, the closure of Horizon Worlds signals a strategic reset. The company is repositioning its future around AI-driven products, marking a decisive shift away from its earlier metaverse vision.

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UAE advances AI native vision for future 6G networks

UAE operator e& (formerly Etisalat) has partnered with Khalifa University to outline a new vision for AI-native 6G networks. Their joint whitepaper presents a framework in which intelligence is embedded at the core of the network architecture rather than added as a feature.

The proposal introduces a dedicated AI plane alongside existing network layers to enable continuous learning and automation. This approach supports sensing, reasoning and autonomous decision-making across radio, core and edge systems.

The framework includes distributed AI agents, digital twin integration and closed-loop automation models. It is designed to support multi-vendor environments while enabling scalable and coordinated intelligence across networks.

Five core pillars underpin the model, including AI frameworks, cloud-edge computing and sustainability-focused design. Together, these elements position 6G as a cognitive infrastructure capable of predictive optimisation and advanced service delivery.

The whitepaper also defines measurable performance indicators such as latency, learning accuracy and energy efficiency. The initiative aims to contribute to global standards while strengthening the UAE’s role in shaping future telecom systems.

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Growing investment and energy plans reshape Armenia’s AI future

Armenia’s recent technology announcements are helping to form a clearer national AI strategy with stronger coordination. A memorandum with the US on semiconductors and AI now appears to be moving beyond symbolic commitment into action.

Momentum has accelerated with plans to expand a large-scale AI factory backed by significant investment. The project is estimated at around $4 billion and includes tens of thousands of advanced GPUs to support large-scale development.

The initiative is already entering construction, marking a shift from concept to execution in a short timeframe. Officials have described a broader vision of building a network of AI factories across the country.

Energy planning is becoming central, with discussions around deploying a small modular nuclear reactor to meet demand. Stable and scalable power is considered essential for sustaining long-term AI infrastructure growth.

Efforts are also targeting the wider ecosystem through a Virtual AI Institute and planned GPU access for startups. These steps aim to strengthen research capacity and ensure local participation in the country’s AI expansion.

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UK opens supercomputing access to boost AI startups

Britain is opening access to its national AI Research Resource to support domestic AI development. Startups and spinouts can now use supercomputers previously reserved for frontier research.

The AIRR combines infrastructure from government, universities and leading technology firms. It provides the computing power needed to train models and run complex simulations.

Access will be worth around £20 million per year for participating companies. Officials say reducing compute barriers will help startups move faster from prototype to product.

The government’s Sovereign AI Unit, backed by up to £500 million, will also support long-term growth. The programme targets areas including advanced models, scientific discovery and trustworthy AI systems.

Concerns remain over regulatory alignment with the EU’s stricter AI rules. Tensions could shape whether the UK maintains a more flexible environment for innovation.

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South Korea seeks support for global AI hub

South Korea is seeking international support for a proposed global AI hub to advance cooperation on technology and governance. The initiative was discussed during talks with Switzerland’s leadership.

Officials in Switzerland met with South Korea’s prime minister to strengthen bilateral ties and support the project. The programme is intended to promote collaboration on AI rules, education and innovation.

The government of South Korea has also engaged several UN agencies to support the initiative. Agreements outline cooperation to help establish the hub and expand global dialogue on AI development.

Leaders in South Korea say the country aims to contribute its strong information technology capabilities to the project. The initiative reflects broader efforts to position the nation as a key player in global AI policy and innovation.

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MIT advances wireless sensing with generative AI

Researchers at MIT have developed a new approach that combines generative AI with wireless signals to detect objects hidden behind obstacles. The system uses Wi-Fi-like millimetre wave signals to build partial reconstructions and then completes missing details with AI.

Traditional methods struggled with limited visibility due to how signals reflect off surfaces, often leaving large portions of objects undetected. The new technique, Wave-Former, uses generative AI to fill missing data, improving reconstruction accuracy by nearly 20%.

An extended system, called RISE, takes the concept further by mapping entire indoor environments. By analysing reflected signals from human movement, the system reconstructs room layouts using a single stationary radar, removing the need for mobile sensors.

Applications range from warehouse automation to smart home robotics, where understanding hidden objects and human positions is critical. Unlike camera-based systems, the technology also preserves privacy, marking a significant step forward in wireless sensing capabilities.

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