Capacity development Archives | Page 289 of 345

Duffy criticises Verizon over FAA contract delays

US Transportation Secretary Sean Duffy criticised Verizon on Tuesday for delays in its $2.4 billion, 15-year contract with the Federal Aviation Administration (FAA), saying the company is ‘not moving fast enough.’

As the FAA works to upgrade ageing air traffic control systems, Duffy stressed the need for multiple companies to contribute to the effort, adding that the American public ‘can’t wait 10 or 12 years’ for improvements.

Verizon defended its progress, stating it is actively working with FAA technology teams and is open to collaborating with other firms offering complementary services.

Meanwhile, SpaceX’s Starlink denied reports that it aims to take over the FAA contract, saying it could be a partial solution but has no plans to replace Verizon’s role.

The FAA has been testing Starlink terminals in Alaska to improve weather data access, while the Government Accountability Office warns that one-third of US air traffic control systems are outdated and unsustainable.

Some Democrats have suggested shifting the FAA contract to Starlink due to Elon Musk’s ties to Donald Trump, but no official decisions have been made.

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ICBC unveils $11 billion innovation fund

China’s Industrial and Commercial Bank (ICBC), the world’s largest commercial lender by assets, has launched an 80 billion yuan ($11.04 billion) technology and innovation fund to bolster the private sector.

The state-owned bank announced that the fund will focus on ‘hard technology’ fields such as semiconductors and advanced manufacturing rather than ‘soft’ technology like internet services.

ICBC chairman Liao Lin emphasised that the initiative aligns with central leadership directives, aiming to turn supportive policies into tangible benefits for private enterprises. The bank described the fund as ‘patient capital,’ indicating a long-term investment strategy rather than a rush for quick profits.

The launch follows China’s recent policy priorities for 2025, unveiled at its annual parliamentary meeting, which stress boosting consumption and achieving technological advances amid ongoing tensions with the US.

Additionally, the government plans to establish a state-backed fund to raise 1 trillion yuan from private investment to support technology startups.

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Trump administration ends support for cybersecurity projects

The Trump administration has cut funding for two key cybersecurity initiatives, including one supporting election security, sparking concerns over potential vulnerabilities in future US elections.

The Cybersecurity and Infrastructure Security Agency (CISA) announced it would end around $10 million in annual funding to the non-profit Center for Internet Security, which manages election-related cybersecurity programmes.

However, this move comes as part of a broader review of CISA’s election-related work, during which over a dozen staff members were placed on administrative leave.

The decision follows another controversial step by the administration to dismantle an FBI task force that investigated foreign influence in US elections.

Critics warn that reducing government involvement in election security weakens safeguards against interference, with Larry Norden from the Brennan Center for Justice calling the cuts a serious risk for state and local election officials.

The National Association of Secretaries of State is now seeking clarification on CISA’s decision and its wider implications.

CISA has faced Republican criticism in recent years for its role in countering misinformation related to the 2020 election and the coronavirus pandemic. However, previous leadership maintained that the agency’s work was limited to assisting states in identifying and addressing misinformation.

While CISA argues the funding cuts will streamline its focus on critical security areas, concerns remain over the potential impact on election integrity and cybersecurity protections across local and state governments.

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Xpeng plans major investment in humanoid robots

Chinese electric vehicle maker Xpeng is making a long-term push into humanoid robots, with potential investments reaching up to 100 billion yuan ($13.8 billion), according to CEO He Xiaopeng. Speaking at the annual parliamentary session, He described the company’s current investment as conservative but signalled a willingness to scale up significantly over the next two decades. Xpeng, which entered the humanoid robotics sector in 2020, unveiled its Iron humanoid robot last November, positioning it as a rival to Tesla’s Bot.

Chinese automakers are increasingly venturing into robotics, encouraged by policymakers aiming for breakthroughs in the field. Stellantis-backed Leapmotor has also joined the race, forming a robotics team to develop machines for industrial applications such as factory assembly lines. CEO Zhu Jiangming stated that these robots are intended to enhance efficiency by replacing human labour in production processes.

Xpeng’s CEO suggested that automakers could invest between 1-2 billion yuan per year in developing and deploying humanoid robots in real-world scenarios. As the industry shifts towards automation, carmakers are betting that advanced robotics will play a crucial role in future manufacturing and mobility solutions.

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Chinese investors turn to AI for stock market edge

Chinese retail investors are rapidly embracing AI tools like DeepSeek to navigate the stock market, marking a striking shift from last year’s government crackdown on computer-driven quantitative trading.

Online courses and packed training rooms reflect a growing eagerness among small-time traders to use AI-powered models, with many seeing them as essential in the digital age.

DeepSeek, developed by a hedge fund in Hangzhou, has not only boosted Chinese stocks but also reshaped perceptions of the country’s $700 billion hedge fund industry.

Despite the initial backlash against quant funds, which were previously blamed for market volatility, investors are now paying thousands of yuan to attend AI trading seminars.

Social media is flooded with courses teaching traders how to use DeepSeek to analyse companies, pick stocks, and even code their own trading strategies.

While major US funds like BlackRock and Renaissance Technologies have long used AI for investments, DeepSeek’s open-source model makes these tools accessible to China’s smaller asset managers and individual traders.

Financial institutions are also adapting to the AI-driven shift. Brokers are rushing to integrate AI models into their platforms, with industry leaders predicting a complete transformation in how Chinese investors make decisions.

Many now seek trading advice from DeepSeek instead of human wealth managers, reflecting a deep trust in the technology. However, experts warn that AI models still have limitations and could create market risks, especially if large numbers of traders act on the same signals.

While some remain cautious about AI’s role in investing, DeepSeek has undeniably changed public attitudes towards quant fund managers.

Many now view them as contributors to market efficiency rather than as culprits behind retail losses. As China’s stock market continues to evolve, AI looks set to play an increasingly dominant role in shaping investor behaviour.

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Meta has developed an AI chip to cut reliance on Nvidia, Reuters reports

Meta, the owner of Facebook, Instagram, and WhatsApp, is testing its first in-house chip designed for training AI systems, sources told Reuters.

The social media giant has started a limited rollout of the chip, planning to scale up production if testing delivers positive results. The move represents a crucial step in Meta’s strategy to lessen dependence on external suppliers like Nvidia and lower substantial infrastructure costs.

The company has projected expenses between $114 billion and $119 billion for 2025, with up to $65 billion dedicated to AI infrastructure.

The chip, part of Meta’s Meta Training and Inference Accelerator (MTIA) series, is a dedicated AI accelerator, meaning it is specifically designed for AI tasks rather than general processing. This could make it more power-efficient than traditional GPUs.

Meta is collaborating with Taiwan-based chip manufacturer TSMC to produce the new hardware. The test phase follows Meta’s first ‘tape-out’ of the chip, a crucial milestone in silicon development where an initial design is sent to a chip factory.

However, this process is costly and time-consuming, with no guarantee of success, and any failure would require repeating the tape-out step.

Meta has previously faced setbacks in its custom chip development, including scrapping an earlier version of an inference chip after poor test results. However, the company has since used another MTIA chip for AI-powered recommendations on Facebook and Instagram.

The new training chip aims to first enhance recommendation systems before expanding to generative AI applications like the chatbot Meta AI.

Meta executives hope to implement their own chips for AI training by 2026, although the company continues to be one of Nvidia’s biggest customers, investing heavily in GPUs for its AI operations.

The development comes as AI researchers increasingly question whether scaling up large language models by adding more computing power will continue to drive progress. The recent emergence of more efficient AI models, such as those from Chinese startup DeepSeek, has intensified these debates.

While Nvidia remains a dominant force in AI hardware, fluctuating investor confidence and broader market concerns have caused turbulence in the company’s stock value.

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New York MTA partners with Google to detect track problems

The Metropolitan Transportation Authority (MTA) in New York City has partnered with Google Public Sector on a pilot program designed to detect track defects before they cause significant disruptions. Using Google Pixel smartphones retrofitted onto subway cars, the system captured millions of sensor readings, GPS locations, and hours of audio to identify potential problems. The project aimed to improve the efficiency of the MTA’s response to track issues, potentially saving time and money while reducing delays for passengers.

The AI-powered program, called TrackInspect, analyses the sounds and vibrations from the subway to pinpoint areas that could signal defects, such as loose rails or worn joints. Data collected during the pilot, which ran from September 2024 to January 2025, showed that the AI system successfully identified 92% of defect locations found by human inspectors. The system was trained using feedback from MTA inspectors, helping refine its ability to predict track issues.

While the pilot was considered a success, the future of the program remains uncertain due to financial concerns at the MTA. Despite this, the success of the project has sparked interest from other transit systems looking to adopt similar AI-driven technologies to improve infrastructure maintenance and reduce delays. The MTA is now exploring other technological partnerships to enhance its track monitoring and maintenance efforts.

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Nagasaki University launches AI program for medical student training

Nagasaki University in southwestern Japan, in collaboration with a local systems development company, has unveiled a new AI program aimed at enhancing medical student training.

The innovative program allows students to practice interviews with virtual patients on a screen, addressing the growing difficulty of securing simulated patients for training, especially in regional areas facing population declines.

In a demonstration earlier this month, an AI-powered virtual patient exhibited symptoms such as fever and cough, responding appropriately to questions from a medical student.

Scheduled for introduction by March 2026, the technology will allow students to interact with virtual patients of different ages, genders, and symptoms, enhancing their learning experience.

The university plans to enhance the program with scoring and feedback functions to make the training more efficient and improve the quality of learning.

Shinya Kawashiri, an associate professor at the university’s School of Medicine, expressed hope that the system would lead to more effective study methods.

Toru Kobayashi, a professor at the university’s School of Information and Data Sciences, highlighted the program as a groundbreaking initiative in Japan’s medical education landscape.

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NHS looks into Medefer data flaw after security concerns

NHS is investigating allegations that a software flaw at private medical services company Medefer left patient data vulnerable to hacking.

The flaw, discovered in November, affected Medefer’s internal patient record system in the UK, which handles 1,500 NHS referrals monthly.

A software engineer who found the issue believes the vulnerability may have existed for six years, but Medefer denies this claim, stating no data has been compromised.

The engineer discovered that unprotected application programming interfaces (APIs) could have allowed outsiders to access sensitive patient information.

While Medefer has insisted that there is no evidence of any breach, they have commissioned an external security agency to review their systems. The agency confirmed that no breach was found, and the company asserts that the flaw was fixed within 48 hours of being discovered.

Cybersecurity experts have raised concerns about the potential risks posed by the flaw, emphasising that a proper investigation should have been conducted immediately.

Medefer reported the issue to the Information Commissioner’s Office (ICO) and the Care Quality Commission (CQC), both of which found no further action necessary. However, experts suggest that a more thorough response could have been beneficial given the sensitive nature of the data involved.

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China expands university enrolment to boost AI talent

China’s top universities are set to expand undergraduate enrolment to develop talent in key strategic fields, particularly AI.

The move follows the rapid rise of AI startup DeepSeek, which has drawn global attention for producing advanced AI models at a fraction of the usual cost.

The company’s success, largely driven by researchers from elite institutions in China, is seen as a major step in Beijing’s efforts to boost its homegrown STEM workforce.

Peking University announced it would add 150 undergraduate spots in 2025 to focus on national strategic needs, particularly in information science, engineering, and clinical medicine.

Renmin University will expand enrolment by over 100 places, aiming to foster innovation in AI. Meanwhile, Shanghai Jiao Tong University plans to add 150 spots dedicated to emerging technologies such as integrated circuits, biomedicine, and new energy.

This expansion aligns with China’s broader strategy to strengthen its education system and technological capabilities. In January, the government introduced a national action plan to enhance education efficiency and innovation by 2035.

Additionally, authorities plan to introduce AI education in primary and secondary schools to nurture digital skills and scientific curiosity from an early age.

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