Development

WordPress.com integrates AI assistant into its editing workflow

Major updates to AI tooling are reshaping website creation as WordPress.com brings an integrated assistant directly into its editor.

The new system works within each site rather than relying on external chat windows, allowing users to adjust layouts, create content, and modify designs in real time. The tool is available to customers on Business and Commerce plans, although activation requires a manual opt-in.

The assistant appears across several core areas of the platform. Inside the editor, it can refine writing, modify styles, translate text and generate new sections with simple instructions.

In the Media Library, you can create new images or apply targeted edits through the platform’s in-house Nano Banana models, eliminating the need for separate subscriptions. Block notes provide an additional way to request suggestions, checks, or link-based context directly within each page.

The updates aim to make site building faster and more efficient by keeping all AI interactions within the existing workflow. Users who prefer a manual experience can ignore the feature entirely, since the assistant remains inactive unless deliberately enabled.

WordPress.com also notes that the system works best with block themes, although image tools are still available for classic themes.

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Rising DRAM prices push memory to the centre of AI strategy

The cost of running AI systems is shifting towards memory rather than compute, as the price of DRAM has risen sharply over the past year. Efficient memory orchestration is now becoming a critical factor in keeping inference costs under control, particularly for large-scale deployments.

Analysts such as Doug O’Laughlin and Val Bercovici of Weka note that prompt caching is turning into a complex field.

Anthropic has expanded its caching guidance for Claude, with detailed tiers that determine how long data remains hot and how much can be saved through careful planning. The structure enables significant efficiency gains, though each additional token can displace previously cached content.

The growing complexity reflects a broader shift in AI architecture. Memory is being treated as a valuable and scarce resource, with optimisation required at multiple layers of the stack.

Startups such as Tensormesh are already working on cache optimisation tools, while hyperscalers are examining how best to balance DRAM and high-bandwidth memory across their data centres.

Better orchestration should reduce the number of tokens required for queries, and models are becoming more efficient at processing those tokens. As costs fall, applications that are currently uneconomical may become commercially viable.

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China boosts AI leadership with major model launches ahead of Lunar New Year

Leading Chinese AI developers have unveiled a series of advanced models ahead of the Lunar New Year, strengthening the country’s position in the global AI sector.

Major firms such as Alibaba, ByteDance, and Zhipu AI introduced new systems designed to support more sophisticated agents, faster workflows and broader multimedia understanding.

Industry observers also expect an imminent release from DeepSeek, whose previous model disrupted global markets last year.

Alibaba’s Qwen 3.5 model provides improved multilingual support across text, images and video while enabling rapid AI agent deployment instead of slower generation pipelines.

ByteDance followed up with updates to its Doubao chatbot and the second version of its image-to-video tool, SeeDance, which has drawn copyright concerns from the Motion Picture Association due to the ease with which users can recreate protected material.

Zhipu AI expanded the landscape further with GLM-5, an open-source model built for long-context reasoning, coding tasks, and multi-step planning. The company highlighted the model’s reliance on Huawei hardware as part of China’s efforts to strengthen domestic semiconductor resilience.

Meanwhile, excitement continues to build for DeepSeek’s fourth-generation system, expected to follow the widespread adoption and market turbulence associated with its V3 model.

Authorities across parts of Europe have restricted the use of DeepSeek models in public institutions because of data security and cybersecurity concerns.

Even so, the rapid pace of development in China suggests intensifying competition in the design of agent-focused systems capable of managing complex digital tasks without constant human oversight.

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Report warns of widening 5G capability gap

A new study by network analytics firm Ookla finds that while global 5G coverage gaps are narrowing, a deeper divide is emerging in network capabilities, with Europe falling behind. The report argues that the real competition is no longer about basic rollout, but about how effectively countries deploy advanced standalone (SA) 5G networks to support innovation, industry, and high-performance services.

According to the findings, North America and leading Asian markets have moved more decisively toward full standalone 5G architectures, achieving faster speeds and improved responsiveness. Gulf Cooperation Council countries have also advanced rapidly, with the region described as a 5G SA performance leader in 2025, delivering median download speeds reportedly more than five times higher than those in Europe.

Europe, by contrast, is characterised as lagging due to slow commercialisation, fragmented device ecosystems, and uneven tariff structures. While some countries, such as Spain, are cited as positive examples, the broader region risks losing ground as others accelerate deployment of 5G Advanced technologies, including enhanced spectrum use and more sophisticated network optimisation tools.

The report highlights national policy frameworks as a decisive factor in 5G competitiveness. Spectrum allocation strategies, infrastructure investment rules, and regulatory innovation are seen as equally important as technical upgrades. The findings come as the European Union advances its proposed Digital Networks Act, which has drawn mixed reactions from industry stakeholders concerned about investment conditions.

Beyond deployment, Ookla stresses that simply launching standalone 5G does not guarantee strong performance. Advanced optimisation strategies, such as cloud-native network design, deeper virtualisation, and improved spectrum efficiency, are key to unlocking the technology’s full potential. Enterprise adoption, initially slow under earlier non-standalone models, is now showing signs of growth, particularly in markets offering network slicing services.

The study concludes that decisions made in the next two years will be critical for long-term digital competitiveness. As 5G increasingly intersects with national AI strategies, industrial policy, and digital sovereignty agendas, countries that treat standalone networks as a strategic priority may gain a structural advantage, while others risk seeing the gap widen further as the transition toward 6G approaches.

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New AI innovation hub aims to position Ethiopia as regional leader

Ethiopia has launched a new Artificial Intelligence University Innovation Pod in Addis Ababa, marking a significant step in its ambition to become Africa’s leading AI hub.

The Ethiopian Artificial Intelligence Institute leads the initiative in partnership with Addis Ababa University and the UN Development Programme, under the latter’s Timbuktoo Initiative.

Officials say the centre is designed to strengthen national AI capacity, promote homegrown technological solutions and build a sustainable innovation ecosystem. The AI UniPod will support university students, researchers and start-ups working on advanced digital technologies, with a focus on transforming young people from job seekers into technology creators.

The Ethiopian Artificial Intelligence Institute highlighted recent achievements, including patented tools for breast cancer diagnosis and coffee seed identification, as evidence of the country’s growing technological capability. Leaders described the new facility as a shift from ambition to practical implementation of AI.

Data sovereignty was emphasised as a central pillar of the strategy. Authorities argued that control over digital infrastructure and data resources is essential for national sovereignty, particularly as AI becomes embedded in economic and public systems.

The government views the AI UniPod as a long-term platform for innovation, aimed not only at Ethiopia but also at the wider African continent.

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Parliament halts built-in AI tools on tablets and other devices over data risks

The European Parliament has disabled built-in AI features on tablets issued to lawmakers, citing cybersecurity and data protection risks. An internal email states that writing assistants, summarisation tools, and enhanced virtual assistants were turned off after security assessments.

Officials said some AI functions on tablets rely on cloud processing for tasks that could be handled locally, potentially transmitting data off the device. A review is underway to clarify how much information may be shared with service providers.

Only pre-installed AI tools were affected, while third-party apps remain available. Lawmakers were advised to review AI settings on personal devices, limit app permissions, and avoid exposing work emails or documents to AI systems.

The step reflects wider European concerns about digital sovereignty and reliance on overseas technology providers. US legislation, such as the Cloud Act, allows authorities to access data held by American companies, raising cross-border data protection questions.

Debate over AI security is intensifying as institutions weigh innovation against the risks of remote processing and granular data access. Parliament’s move signals growing caution around handling sensitive information in cloud-based AI environments.

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From Milan-Cortina to factory floors, AI powers Zhejiang manufacturing

As Chinese skater Sun Long stood on the Milan-Cortina Winter Olympics podium, the vivid red of his uniform reflected more than national pride. It also highlighted AI’s expanding role in China’s textile manufacturing.

In Shaoxing, AI-powered image systems calibrate fabric colours in real time. Factory managers say digital printing has lifted pass rates from about 50% to above 90%, easing longstanding production bottlenecks.

Tyre manufacturing firm Zhongce Rubber Group uses AI to generate multiple 3D designs in minutes. Engineers report shorter development cycles and reduced manual input across research and testing.

Electric vehicle maker Zeekr uses AI visual inspection in its 5G-enabled factory. Officials say tyre verification now takes seconds, helping eliminate assembly errors.

Provincial authorities in China report that large industrial firms are fully digitalized. Zhejiang plans to further integrate AI by 2027, expanding smart factories and industrial intelligence.

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Study says China AI governance not purely state-driven

New research challenges the view that China’s AI controls are solely the product of authoritarian rule, arguing instead that governance emerges from interaction between the state, private sector and society.

A study by Xuechen Chen of Northeastern University London and Lu Xu of Lancaster University argues that China’s AI governance is not purely top-down. Published in the Computer Law & Security Review, it says safeguards are shaped by regulators, companies and social actors, not only the central government.

Chen calls claims that Beijing’s AI oversight is entirely state-driven a ‘stereotypical narrative’. Although the Cyberspace Administration of China leads regulation, firms such as ByteDance and DeepSeek help shape guardrails through self-regulation and commercial strategy.

China was the first country to introduce rules specific to generative AI. Systems must avoid unlawful or vulgar content, and updated legislation strengthens minor protection, limiting children’s online activity and requiring child-friendly device modes.

Market incentives also reinforce compliance. As Chinese AI firms expand globally, consumer expectations and cultural norms encourage content moderation. The study concludes that governance reflects interaction between state authority, market forces and society.

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Hollywood groups challenge ByteDance over Seedance 2.0 copyright concerns

ByteDance is facing scrutiny from Hollywood organisations over its AI video generator Seedance 2.0. Industry groups allege the system uses actors’ likenesses and copyrighted material without permission.

The Motion Picture Association said the tool reflects large-scale unauthorised use of protected works. Chairman Charles Rivkin called on ByteDance to halt what he described as infringing activities that undermine creators’ rights and jobs.

SAG-AFTRA also criticised the platform, citing concerns over the use of members’ voices and images. Screenwriter Rhett Reese warned that rapid AI development could reshape opportunities for creative professionals.

ByteDance acknowledged the concerns and said it would strengthen safeguards to prevent misuse of intellectual property. The company reiterated its commitment to respecting copyright while addressing complaints.

The dispute underscores wider tensions between technological innovation and rights protection as generative AI tools expand. Legal experts say the outcome could influence how AI video systems operate within existing copyright frameworks.

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Qwen3.5 debuts with hybrid architecture and expanded multimodal capabilities

Alibaba has released Qwen3.5-397B-A17B, the first open-weight model in its Qwen3.5 series. Designed as a native vision-language system, it contains 397 billion parameters, though only 17 billion are activated per forward pass to improve efficiency.

The model uses a hybrid architecture that combines sparse mixture-of-experts with linear attention via Gated Delta Networks. According to the company, this design improves inference speed while maintaining strong results across reasoning, coding, and agent benchmarks.

Multilingual coverage expands from 119 to 201 languages and dialects, supported by a 250k vocabulary and larger visual-text pretraining datasets. Alibaba says the model achieves performance comparable to significantly larger predecessors.

A hosted version, Qwen3.5-Plus, is available through Alibaba Cloud Model Studio, with a 1-million-token context window and built-in adaptive tool use. Reinforcement learning environments were scaled to prioritise generalisation across tasks rather than narrow optimisation.

Infrastructure upgrades include an FP8 training pipeline and an asynchronous reinforcement learning framework to improve efficiency and stability. Alibaba positions Qwen3.5 as a base for multimodal agents that support reasoning, search, and coding.

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