Artificial intelligence

China announces mandatory AI labelling requirements

Chinese authorities have announced new regulations requiring AI-generated content to be clearly labelled, with the rules set to take effect on 1 September 2025. Officials said the move aims to ensure transparency and support the ‘healthy development’ of AI.

The decision follows global discussions on the risks associated with AI-generated media, including misinformation and deepfakes.

By mandating labelling, China seeks to enhance accountability and distinguish AI-created content from human-generated material.

The new rules reflect the government’s ongoing efforts to regulate emerging technologies while maintaining control over digital information.

With AI playing an increasing role in content creation, policymakers worldwide are considering similar measures.

China’s regulations are expected to influence international approaches to AI governance as other nations evaluate their own strategies for handling AI-generated content.

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Chinese hedge funds boost AI for competitive edge

China’s hedge fund industry is undergoing a transformative shift, spurred by High-Flyer’s integration of AI in its trading strategies. The multi-billion-dollar fund not only uses AI to enhance its portfolio but also created DeepSeek, a game-changing LLM that has disrupted the dominance of Western AI firms like those in Silicon Valley.

The breakthrough has ignited an AI arms race among Chinese asset managers, including firms like Baiont Quant, Wizard Quant, and Mingshi Investment Management, as they rush to incorporate AI into their investment workflows.

AI-powered trading has gained momentum, with many hedge funds now using AI to process market data and generate trading signals based on investor risk profiles. As competition for “alpha” (outperformance) intensifies, the demand for AI talent is surging.

Companies like Wizard Quant and Mingshi are actively recruiting top AI engineers, and even mutual funds, such as China Merchants Fund, have adopted DeepSeek to boost their efficiency. The open-source model has democratised access to AI, lowering the entry barrier for smaller Chinese funds, which had previously been unable to compete with their Western counterparts due to high costs.

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Dapr integrates AI agent support for developers

Dapr, the open-source microservices runtime introduced by Microsoft in 2019, has added new capabilities to support AI agents, broadening its appeal to developers creating scalable distributed applications.

Initially designed to simplify microservice-based app development, Dapr’s new functionality builds on its existing concept of virtual actors, making it easier to incorporate AI agents into systems.

The newly launched Dapr Agents offer developers a framework to efficiently run AI agents at scale with statefulness, making it ideal for applications involving large language models (LLMs).

However, this update allows seamless integration with popular AI providers, such as AWS Bedrock, OpenAI, and Hugging Face. Developers also benefit from Dapr’s orchestration and resource-efficient model, ensuring agents can spin up quickly when needed and retain state after tasks are completed.

Dapr Agents currently support Python, with plans for .NET and other languages like Java and Go coming soon.

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The role of AI in precision farming for wine production

AI is making its mark in the wine industry, with vineyards across California adopting cutting-edge technology to optimise crop production.

One notable example is Napa Valley farmer Tom Gamble, who has integrated an autonomous tractor equipped with AI sensors to map his vineyard.

These AI-powered machines gather data that allows farmers to make more informed decisions about water use, fertilizer application, and pest control, improving efficiency and sustainability.

AI’s influence extends beyond tractors. Companies like John Deere in the US have developed AI-driven technologies that help vineyard managers apply materials more precisely, reducing waste and environmental impact.

Smart irrigation systems, for example, can monitor water use and even shut off in case of leaks, making vineyards more water-efficient.

Despite concerns about the cost of adopting such technology, particularly for smaller, family-run vineyards, AI offers a way to streamline operations and adapt to changing environmental conditions.

While AI is enhancing wine production, it also aids in managing crop health and predicting yields. By analysing images and soil data, AI systems can detect early signs of disease or nutrient deficiencies, helping farmers take preventive action before issues escalate.

However, this technology allows vineyards to make smarter decisions, ultimately improving the quality and consistency of their wine production.

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Meta faces lawsuit in France over copyrighted AI training data

Leading French publishers and authors have filed a lawsuit against Meta, alleging the tech giant used their copyrighted content to train its artificial intelligence systems without permission.

The National Publishing Union (SNE), the National Union of Authors and Composers (SNAC), and the Society of Men of Letters (SGDL) argue that Meta’s actions constitute significant copyright infringement and economic ‘parasitism.’ The complaint was lodged earlier this week in a Paris court.

This lawsuit is the first of its kind in France but follows a wave of similar actions in the US, where authors and visual artists are challenging the use of their works by companies like Meta to train AI models.

As the issue of AI-generated content continues to grow, these legal actions highlight the mounting concerns over how tech companies utilise vast amounts of copyrighted material without compensation or consent from creators.

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AI-driven robotics set for growth with Google’s latest models

Google has introduced two new AI models designed specifically for robotics, building on its Gemini 2.0 technology. The launch aims to support the rapidly advancing robotics industry, which is increasingly benefiting from AI improvements.

The first model, Gemini Robotics, enables robots to generate physical actions as outputs, while the second, Gemini Robotics-ER, enhances spatial awareness and reasoning abilities for developers.

The move follows a significant AI breakthrough by robotics startup Figure AI, which recently ended its collaboration with OpenAI.

Google has tested its Gemini Robotics model on its bi-arm robotics platform, ALOHA 2, and believes the technology can be adapted for complex applications, such as Apptronik’s Apollo robot.

Investment in robotics is accelerating, with Apptronik securing $350 million in funding last month, including backing from Google.

Google’s AI models are designed for various types of robots, from humanoid machines to industrial units used in factories and warehouses.

Industry experts believe AI-focused robotics models will help startups reduce costs and bring products to market faster. Google has a long history in robotics, having acquired Boston Dynamics in 2013 before selling it to SoftBank four years later.

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AI demand drives record power sector deals

The US power industry is experiencing a surge in mergers and acquisitions (M&A) as record demand for electricity, particularly from AI-driven data centres, fuels heightened interest in power generation assets.

Industry experts predict 2025 will be a bumper year for such deals, with assets in high demand due to massive projections for future consumption. Notable transactions, such as Constellation Energy’s $16.4 billion acquisition of Calpine, highlight the sector’s boom in early 2025.

Private equity firms, pension funds, and other institutional investors are rapidly deploying capital into the power sector, with over $330 billion in capital waiting to be invested in infrastructure.

Many of these firms are targeting not only operational companies but also firms that manufacture energy equipment, positioning themselves to profit from the ongoing expansion of the power grid to meet AI-related demand.

While the US M&A frenzy contrasts with a broader slowdown in the market, the momentum in the power sector is expected to continue.

Challenges such as material shortages and regulatory uncertainties, particularly surrounding tariffs on essential materials, may impact future projects.

However, the increasing value of power infrastructure makes these challenges more manageable for investors keen to tap into the growing market.

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EU draft AI code faces industry pushback

The tech industry remains concerned about a newly released draft of the Code of Practice on General-Purpose Artificial Intelligence (GPAI), which aims to help AI providers comply with the EU‘s AI Act.

The proposed rules, which cover transparency, copyright, risk assessment, and mitigation, have sparked significant debate, especially among copyright holders and publishers.

Industry representatives argue that the draft still presents serious issues, particularly regarding copyright obligations and external risk assessments, which they believe could hinder innovation.

Tech lobby groups, such as the CCIA and DOT Europe, have expressed dissatisfaction with the latest draft, highlighting that it continues to impose burdensome requirements beyond the scope of the original AI Act.

Notably, the mandatory third-party risk assessments both before and after deployment remain a point of contention. Despite some improvements in the new version, these provisions are seen as unnecessary and potentially damaging to the industry.

Copyright concerns remain central, with organisations like News Media Europe warning that the draft still fails to respect copyright law. They argue that AI companies should not be merely expected to make ‘best efforts’ not to use content without proper authorisation.

Additionally, the draft is criticised for failing to fully address fundamental rights risks, which, according to experts, should be a primary concern for AI model providers.

The draft is open for feedback until 30 March, with the final version expected to be released in May. However, the European Commission’s ability to formalise the Code under the AI Act, which comes into full effect in 2027, remains uncertain.

Meanwhile, the issue of copyright and AI is also being closely examined by the European Parliament.

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Intel appoints new CEO to compete in AI chip market

Intel has appointed tech industry veteran Lip-Bu Tan as its chief executive, aiming to revitalise the struggling chipmaker as it falls behind in the AI race.

Tan, set to take over next week, told employees that overcoming Intel’s challenges would not be easy but reaffirmed his commitment to an engineering-first approach.

Following the announcement, Intel’s shares surged by more than 10 per cent in after-market trading.

Once a dominant force in the semiconductor industry, Intel has been outpaced by Taiwan Semiconductor Manufacturing Co (TSMC) and Samsung Electronics, which lead in made-to-order chip production.

It also lags behind Nvidia, which has emerged as the top AI chip provider. Tan replaces Pat Gelsinger, who was ousted last year after the board lost confidence in his turnaround efforts, which included cutting 15,000 jobs and delaying chipmaking projects.

Tan, previously head of Cadence Design Systems, pledged to restore Intel’s reputation by taking calculated risks to outmanoeuvre competitors.

He intends to continue the company’s plan to manufacture chips for other firms, directly challenging TSMC. However, analysts remain cautious, questioning whether Intel will split its foundry and chip design businesses or prove its ability to deliver cutting-edge technology.

Intel also faces a growing battle in AI, where Nvidia dominates the data centre chip market. Analysts warn that without a compelling AI strategy, Intel could struggle to regain investor confidence.

Tan, however, remains optimistic, vowing to transform Intel into a world-class chipmaker while ensuring customer satisfaction.

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Google enhances Gemini AI with smarter personalisation

Google has announced an update to its Gemini AI assistant, enhancing personalisation to better anticipate user needs and deliver responses that feel more like those of a personal assistant.

The feature, initially available on desktop before rolling out to mobile, allows Gemini to offer tailored recommendations, such as travel ideas, based on search history and, in the future, data from apps like Photos and YouTube.

Users can opt in to the new personalisation features, sharing details like dietary preferences or past conversations to refine responses further.

Google assures that users must explicitly grant permission for Gemini to access search history and other services, and they can disconnect at any time.

However, this level of contextual awareness could give Google an advantage over competitors like ChatGPT by leveraging its vast ecosystem of user data.

The update signals a shift in how users interact with AI, bringing it closer to traditional search while raising questions for publishers and SEO professionals.

As Gemini increasingly provides direct, personalised answers, it may reduce the need for users to visit external websites. While currently experimental, the potential for Google to push broader adoption of AI-driven personalisation could reshape digital content discovery and search behaviour in the future.

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