Tech
Uzbekistan to Produce Humanoid Robots in Partnership with South Korea
Uzbekistan has signed an agreement with South Korea’s ROBOTIS to launch humanoid robot production, marking a major step in its high-tech ambitions. At the same time, students across the country are learning robotics and programming, gaining skills that could prepare them for careers in the emerging industry.
The agreement, signed between the UzElTechSanoat Association and ROBOTIS, sets out plans to establish humanoid robot production within Uzbekistan, develop manufacturing infrastructure, and train specialists for the growing robotics sector. ROBOTIS, known for its humanoid platforms and smart robotic actuators, will support the creation of technological foundations and help prepare a workforce capable of designing and operating advanced robotic systems.
The initiative forms part of Uzbekistan’s broader push to build a domestic innovation ecosystem, combining industrial cooperation with education. Early exposure to robotics and programming is at the heart of this strategy.
In a robotics classroom, 12-year-old Mirkomil Shodiev demonstrates the impact of these programs. Using an EVO-3 educational robotics kit, he assembles and programs his own robot, controlling its movements through lines of code. “This was created by me,” he says. “You connect it to a computer, write code, and it performs tasks using the motor.”
Mirkomil began IT classes four months ago, learning Scratch and now studying Python, a programming language widely used in web development, automation, and robotics. He hopes to build websites and earn money in the future, reflecting the growing importance of digital skills in Uzbekistan’s economy.
The government’s Digital Uzbekistan-2030 strategy is expanding nationwide training in programming and digital skills. IT education centres and specialised academies are growing to meet rising demand for technology careers. At the Robot Academy, where Mirkomil studies, students aged eight to fifteen gain hands-on experience in programming, robotics, and engineering. “Our students create scientific projects, develop games, and build Telegram bots,” says teacher Navruz Shaydullayev. “Programming helps develop their thinking, logic, and intellectual abilities.”
Classroom projects emphasize translating digital commands into physical movement, a key principle behind robotics and industrial automation. Students learn to design, assemble, and control machines independently, building skills that can directly feed into the country’s industrial ambitions.
The partnership with ROBOTIS will extend these educational initiatives into the workforce, providing training for engineers, programmers, and technicians in humanoid robotics. Officials hope the program will strengthen Uzbekistan’s technological competitiveness and create highly skilled jobs in a fast-growing global sector.
For students like Mirkomil, the future is already taking shape. “In the future, I want to continue in this field,” he says. “After finishing the courses, I would like to study in Tashkent as well.” As Uzbekistan prepares to manufacture humanoid robots, classrooms across the country are quietly training the people who may one day build them.
Tech
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Tech
Study Says EU Regulations Are Slowing Rollout of Advanced AI Models
A new study by Governance.AI has found that European Union regulations are delaying the rollout of advanced artificial intelligence models, with technology companies increasingly pointing to the bloc’s regulatory framework as a key obstacle to launching new AI products in Europe.
The report examined 375 large language models (LLMs) released between June 2018 and May 2026, comparing their availability across the United States, the European Union and the United Kingdom. According to the findings, at least 11 percent of advanced AI model releases were either delayed or never launched in the EU compared with the United States. In the UK, the figure stood at 7 percent.
Researchers said they identified 68 cases in which AI models experienced delays or were withheld from specific markets. Regulatory factors were cited as the primary reason in 56 of those cases, making them the most common cause of restricted availability.
The study reviewed releases from major AI developers, including Meta, Google, OpenAI and Anthropic. Meta recorded the highest proportion of delayed or unavailable releases, with 26 percent of its AI models delayed or withheld in the EU and 15 percent in the UK. Anthropic’s Claude 3 Opus was highlighted as one example, with its web application arriving in the EU 71 days later than in the United States.
According to the report, data protection rules have emerged as the biggest regulatory hurdle, particularly for AI systems capable of processing images, audio and real-time video rather than text alone.
The researchers argued that uncertainty surrounding the application of the General Data Protection Regulation (GDPR) to AI model training and deployment has created additional challenges for developers. They also said enforcement of data protection rules has generally been stricter within the EU than in the UK, despite both jurisdictions sharing similar legal foundations following the adoption of the GDPR before Britain’s exit from the bloc.
The report noted that the full impact of newer legislation, including the Digital Markets Act, which began taking effect in 2023, and the Artificial Intelligence Act, adopted in 2024, has yet to be fully reflected in the data.
At the same time, the European Union is reviewing proposals aimed at making data rules more practical for AI development through its Digital Omnibus initiative. Lawmakers are also considering changes to copyright legislation and the AI Act’s copyright provisions to strengthen protections for creators, measures that researchers say could affect future AI model availability if implemented too strictly.
John Lidiard, a UK AI policy researcher and one of the report’s authors, said policymakers should consider the impact that regulatory barriers can have on businesses and consumers seeking access to the latest AI technologies. He said balancing innovation with effective oversight would remain a key challenge as governments continue to develop AI regulations.
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