Capacity development

UAE’s EDGE Group unveils AI Accelerator to power defence and tech

EDGE Group, a global leader in advanced technology and defence, has launched the Group AI Accelerator, a new Centre of Excellence (COE) focused on accelerating AI-driven innovation across its portfolio and facilities.

The initiative is part of EDGE’s broader strategy to support the UAE’s ambitions of becoming a high-tech global hub.

The Group AI Accelerator will develop and integrate AI projects to enhance core engineering capabilities and business services. It will also incubate UAE talent and advance the country’s knowledge-based economy.

Dr. Chaouki Kasmi, EDGE’s President of Technology & Innovation, said the initiative will ‘enable the prompt adoption of AI technologies’ and foster ‘positive disruption’ across key programmes.

Overseen by EDGE’s Technology & Innovation Cluster, the COE will be guided by a steering committee of local and global experts. Engineering and business excellence working groups will lead AI skunkworks projects, R&D in machine learning, and digital transformation efforts.

EDGE’s latest move builds on its commitment to operational excellence and positions the UAE at the forefront of AI and Industry 4.0 development.

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China launches first AI satellites in orbital supercomputer network

China has launched the first 12 satellites in a planned network of 2,800 that will function as an orbiting supercomputer, according to Space News.

Developed by ADA Space in partnership with Zhijiang Laboratory and Neijang High-Tech Zone, the satellites can process their own data instead of relying on Earth-based stations, thanks to onboard AI models.

Each satellite runs an 8-billion parameter AI model capable of 744 tera operations per second, with the group already achieving 5 peta operations per second in total. The long-term goal is a constellation that can reach 1,000 POPS.

The network uses high-speed laser links to communicate and shares 30 terabytes of data between satellites. The current batch also carries scientific tools, such as an X-ray detector for studying gamma-ray bursts, and can generate 3D digital twin data for uses like disaster response or virtual tourism.

The space-based computing approach is designed to overcome Earth-based limitations like bandwidth and ground station availability, which means less than 10% of satellite data typically reaches the surface.

Experts say space supercomputers could reduce energy use by relying on solar power and dissipating heat into space. The EU and the US may follow China’s lead, as interest in orbital data centres grows.

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Researchers believe AI transparency is within reach by 2027

Top AI researchers admit they still do not fully understand how generative AI models work. Unlike traditional software that follows predefined logic, gen AI models learn to generate responses independently, creating a challenge for developers trying to interpret their decision-making processes.

Dario Amodei, co-founder of Anthropic, described this lack of understanding as unprecedented in tech history. Mechanistic interpretability — a growing academic field — aims to reverse engineer how gen AI models arrive at outputs.

Experts compare the challenge to understanding the human brain, but note that, unlike biology, every digital ‘neuron’ in AI is visible.

Companies like Goodfire are developing tools to map AI reasoning steps and correct errors, helping prevent harmful use or deception. Boston University professor Mark Crovella says interest is surging due to the practical and intellectual appeal of interpreting AI’s inner logic.

Researchers believe the ability to reliably detect biases or intentions within AI models could be achieved within a few years.

This transparency could open the door to AI applications in critical fields like security, and give firms a major competitive edge. Understanding how these systems work is increasingly seen as vital for global tech leadership and public safety.

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JMA to test AI-enhanced weather forecasting

The Japan Meteorological Agency (JMA) is exploring the use of AI to improve the accuracy of weather forecasts, with a particular focus on deep learning technologies, according to a source familiar with the plans.

A dedicated team was launched in April to begin developing the infrastructure and tools needed to integrate AI with JMA’s existing numerical weather prediction models. The goal is to combine traditional simulations with AI-generated forecasts based on historical weather data.

If implemented, AI systems could identify weather patterns more efficiently and enhance forecasts for variables such as rainfall and temperature. The technology may also offer improved accuracy in predicting extreme weather events like typhoons.

Currently, the JMA relies on supercomputers to simulate future atmospheric conditions based on observational data. Human forecasters then review the outputs, applying expert judgment before issuing final forecasts and alerts. Even with AI integration, human oversight will remain a core part of the process.

In addition to forecasting, the agency is also considering AI for processing data from the Himawari-10 satellite, which is expected to launch in fiscal 2029.

An official announcement outlining further AI integration measures is anticipated in June.

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UK workers struggle to keep up with AI

AI is reshaping the UK workplace, but many employees feel unprepared to keep pace, according to a major new study by Henley Business School.

While 56% of full-time professionals expressed optimism about AI’s potential, 61% admitted they were overwhelmed by how quickly the technology is evolving.

The research surveyed over 4,500 people across nearly 30 sectors, offering what experts call a clear snapshot of AI’s uneven integration into British industries.

Professor Keiichi Nakata, director of AI at The World of Work Institute, said workers are willing to embrace AI, but often lack the training and guidance to do so effectively.

Instead of empowering staff through hands-on learning and clear internal policies, many companies are leaving their workforce under-supported.

Nearly a quarter of respondents said their employers were failing to provide sufficient help, while three in five said they would use AI more if proper training were available.

Professor Nakata argued that AI has the power to simplify tasks, remove repetitive duties, and free up time for more meaningful work.

But he warned that without better support, businesses risk missing out on what could be a transformative force for both productivity and employee satisfaction.

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AlphaEvolve by DeepMind automates code optimisation and discovers new algorithms

Google’s DeepMind has introduced AlphaEvolve, a new AI-powered coding agent designed to autonomously discover and optimise computer algorithms.

Built on large language models and evolutionary techniques, AlphaEvolve aims to assist experts across mathematics, engineering, and computer science by improving existing solutions and generating new ones.

Unlike natural language-based models, AlphaEvolve uses automated evaluators and iterative evolution strategies—like mutation and crossover—to refine algorithmic solutions.

DeepMind reports success across several domains, including matrix multiplication, data centre scheduling, chip design, and AI model training.

In one case, AlphaEvolve developed a new method for multiplying 4×4 complex matrices using just 48 scalar multiplications, surpassing a longstanding result from 1969. It also improved job scheduling in Google data centres, recovering an average of 0.7% of global compute resources.

In mathematical tests, AlphaEvolve rediscovered known solutions 75% of the time and improved them in 20% of cases. While experts have praised its potential, researchers also stress the importance of secure deployment and responsible use.

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du and Microsoft launch $544M AI data centre in UAE

Emirates Integrated Telecommunications Company PJSC (du) has partnered with Microsoft to build a 2 billion dirham (US$544.5 million) hyperscale data centre in the UAE, unveiled during Dubai AI Week.

Microsoft will be the facility’s primary tenant, and the project will be delivered in phases. This marks du’s sixth data centre, reinforcing the UAE’s growing status as a regional AI and data infrastructure hub.

The partnership aligns with the UAE’s National Strategy for AI 2031, which aims to generate US$96 billion in economic value by 2030.

Hyperscale data centres like this one are expected to form the backbone of the country’s AI ecosystem, which is projected to reach a value of US$46.33 billion by the same year.

The GCC data centre market is booming, with expected growth from US$3.48 billion in 2024 to US$9.49 billion by 2030. du’s move comes amid a regional race between cloud giants like Google, AWS, and Oracle, as well as local providers including Khazna, Equinix, and Gulf Data Hub.

Sustainability is also a growing focus, with new builds like Khazna’s Ajman facility incorporating energy-efficient cooling for high-performance AI workloads.

As AI-driven transformation accelerates across logistics, finance, and smart cities, the UAE is using these strategic partnerships and infrastructure investments to move from a resource-based economy to a data-driven one.

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Google and Nvidia dominate AI patents

Google has overtaken IBM to lead in generative AI patent filings, according to new data from IFI Claims covering February 2024 to April 2025.

The tech giant has also emerged as a frontrunner in agentic AI patents, sharing the spotlight with Nvidia in both US and international rankings.

Instead of maintaining previous leads, IBM and Microsoft now trail Google and Nvidia, with Intel and several Chinese universities also securing top global positions in agentic AI. This suggests a growing international race to shape the future of autonomous AI systems.

In generative AI, Google maintains the top spot globally, while Chinese firms and institutions dominate six of the ten leading positions. Microsoft, Nvidia, and IBM also rank highly, with the US seeing a 56% surge in generative AI patent applications over the past year.

Within the US, top filers include Capital One, Samsung, Adobe, and Qualcomm.

Meta and OpenAI were notably absent from the top ten. OpenAI has recently increased its patent activity but continues to file defensively instead of focusing on patent volume.

Meta has prioritised open-source contributions rather than pursuing patents. Generative AI now accounts for 17% of all US AI patent activity, with agentic AI making up 7%.

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Trump seals $200 billion UAE AI deal

US President Donald Trump has secured €179 billion ($200 billion) in deals with the United Arab Emirates, capping his Persian Gulf tour with plans for the world’s largest AI campus outside the US.

Located in Abu Dhabi and spanning 10 square miles, the facility will be built by UAE-based firm G42 in partnership with American companies, aimed at boosting regional computing capacity while supporting the Global South.

Instead of focusing solely on energy, Trump’s trip saw investments broaden to include AI, aviation, and industrial sectors. In total, his visit to the Gulf states yielded €1.3 trillion ($1.4 trillion) in investment pledges, including major agreements with Saudi Arabia and Qatar.

Gulf leaders are using AI as a vehicle to diversify their economies, while Trump is turning foreign capital into support for US manufacturing and tech exports.

The UAE deal includes plans to import up to 500,000 Nvidia H100 AI chips annually through 2027, with 20% allocated to G42. US officials, however, continue to express concern over potential Chinese access to advanced American technology.

The US Department of Commerce insists that strict safeguards are in place to prevent any misuse or diversion of AI hardware.

Other agreements include a $14.5 billion aircraft purchase by Etihad Airways from Boeing and GE Aerospace, a $60 billion energy partnership with ADNOC, and aluminium and gallium production deals with Emirates Global Aluminum.

Trump’s push to expand American business influence in the Gulf appears to be paying off, instead of letting China or Europe dominate future AI and industrial markets.

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Meta’s Behemoth AI model faces setback

Meta Platforms has postponed the release of its flagship AI model, known as ‘Behemoth,’ due to internal concerns about its performance, according to a report by the Wall Street Journal.

Instead of launching as planned, engineers are struggling to deliver improvements that would meaningfully advance the model beyond earlier versions.

Behemoth was originally scheduled for release in April to coincide with Meta’s first AI developer conference but was quietly delayed to June. The latest update suggests the launch has now been pushed to autumn or later, as internal doubts grow over whether it is ready for public deployment.

In April, Meta previewed Behemoth under the Llama 4 line, calling it ‘one of the smartest LLMs in the world’ and positioning it as a teaching model for future AI systems. Instead of Behemoth, Meta released Llama 4 Scout and Llama 4 Maverick as the latest iterations in its AI portfolio.

The delay comes amid intense competition in the generative AI space, where rivals like Google, OpenAI, and Anthropic continue advancing their models. Meta appears to be opting for caution instead of rushing an underwhelming product to market.

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