AliExpress agrees to binding EU rules on data and transparency

AliExpress has agreed to legally binding commitments with the European Commission to comply with the Digital Services Act (DSA). These cover six key areas, including recommender systems, advertising transparency, and researcher data access.

The announcement on 18 June marks only the second case where a major platform, following TikTok, has formally committed to specific changes under the DSA.

The platform promised greater transparency in its recommendation algorithms, user opt-out from personalisation, and clearer information on product rankings. It also committed to allowing researchers access to publicly available platform data through APIs and customised requests.

However, the lack of clear definitions around terms such as ‘systemic risk’ and ‘public data’ may limit practical oversight.

AliExpress has also established an internal monitoring team to ensure implementation of these commitments. Yet experts argue that without measurable benchmarks and external verification, internal monitoring may not be enough to guarantee meaningful compliance or accountability.

The Commission, meanwhile, is continuing its investigation into the platform’s role in the distribution of illegal products.

These commitments reflect the EU’s broader enforcement strategy under the DSA, aiming to establish transparency and accountability across digital platforms. The agreement is a positive start but highlights the need for stronger oversight and clearer definitions for lasting impact.

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AI model predicts sudden cardiac death more accurately

A new AI tool developed by researchers at Johns Hopkins University has shown promise in predicting sudden cardiac death among people with hypertrophic cardiomyopathy (HCM), outperforming existing clinical tools.

The model, known as MAARS (Multimodal AI for ventricular Arrhythmia Risk Stratification), uses a combination of medical records, cardiac MRI scans, and imaging reports to assess individual patient risk more accurately.

In early trials, MAARS achieved an AUC (area under the curve) score of 0.89 internally and 0.81 in external validation — both significantly higher than traditional risk calculators recommended by American and European guidelines.

The improvement is attributed to its ability to interpret raw cardiac MRI data, particularly scans enhanced with gadolinium, which are often overlooked in standard assessments.

While the tool has the potential to personalise care and reduce unnecessary defibrillator implants, researchers caution that the study was limited to small cohorts from Johns Hopkins and North Carolina’s Sanger Heart & Vascular Institute.

They also acknowledged that MAARS’s reliance on large and complex datasets may pose challenges for widespread clinical use.

Nevertheless, the research team believes MAARS could mark a shift in managing HCM, the most common inherited heart condition.

By identifying hidden patterns in imaging and medical histories, the AI model may protect patients more effectively, especially younger individuals who remain at risk yet receive no benefit from current interventions.

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TikTok struggles to stop the spread of hateful AI videos

Google’s Veo 3 video generator has enabled a new wave of racist AI content to spread across TikTok, despite both platforms having strict policies banning hate speech.

According to MediaMatters, several TikTok accounts have shared AI-generated videos promoting antisemitic and anti-Black stereotypes, many of which still circulated widely before being removed.

These short, highly realistic videos often included offensive depictions, and the visible ‘Veo’ watermark confirmed their origin from Google’s model.

While both TikTok and Google officially prohibit the creation and distribution of hateful material, enforcement has been patchy. TikTok claims to use both automated systems and human moderators, yet the overwhelming volume of uploads appears to have delayed action.

Although TikTok says it banned over half the accounts before MediaMatters’ findings were published, harmful videos still managed to reach large audiences.

Google also maintains a Prohibited Use Policy banning hate-driven content. However, Veo 3’s advanced realism and difficulty detecting coded prompts make it easier for users to bypass safeguards.

Testing by reporters suggests the model is more permissive than previous iterations, raising concerns about its ability to filter out offensive material before it is created.

With Google planning to integrate Veo 3 into YouTube Shorts, concerns are rising that harmful content may soon flood other platforms. TikTok and Google appear to lack the enforcement capacity to keep pace with the abuse of generative AI.

Despite strict rules on paper, both companies are struggling to prevent their technology from fuelling racist narratives at scale.

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DeepSeek gains business traction despite security risks

Chinese AI company DeepSeek is gaining traction in global markets despite growing concerns about national security.

While government bans remain in place across several countries, businesses are turning to DeepSeek’s models for low cost and firm performance, often ranking just behind OpenAI’s ChatGPT and Google’s Gemini in traffic and market share.

DeepSeek’s appeal lies in its efficiency. With advanced engineering techniques like its ‘mixture-of-experts’ system, the company has reduced computing costs by activating fewer parameters without a noticeable drop in performance.

Training costs have reportedly been as low as $5.6 million — a fraction of what rivals like Anthropic spend. As a result, DeepSeek’s models are now available across major platforms, including AWS, Azure, Google Cloud, and even open-source repositories like GitHub and Hugging Face.

However, the way DeepSeek is accessed matters. While companies can safely self-host the models in private environments, using the mobile app or website means sending data to Chinese servers, a key reason for widespread bans on public-sector use.

Individual consumers often lack the technical control enterprises enjoy, making their data more vulnerable to foreign access.

Despite the political tension, demand continues to grow. US firms are exploring DeepSeek as a cost-saving alternative, and its models are being deployed in industries from telecoms to finance.

Even Perplexity, an American AI firm, has used DeepSeek R1 to power a research tool hosted entirely on Western servers. DeepSeek’s open-source edge and rapid technical progress are helping it close the gap with much larger AI competitors — quietly but significantly.

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Meta’s AI chatbots are designed to initiate conversations and enhance user engagement

Meta is training AI-powered chatbots that can remember previous conversations, send personalised follow-up messages, and actively re-engage users without needing a prompt.

Internal documents show that the company aims to keep users interacting longer across platforms like Instagram and Facebook by making bots more proactive and human-like.

Under the project code-named ‘Omni’, contractors from the firm Alignerr are helping train these AI agents using detailed personality profiles and memory-based conversations.

These bots are developed through Meta’s AI Studio — a no-code platform launched in 2024 that lets users build customised digital personas, from chefs and designers to fictional characters. Only after a user initiates a conversation can a bot send one follow-up, and that too within a 14-day window.

Bots must match their assigned personality and reference earlier interactions, offering relevant and light-hearted responses while avoiding emotionally charged or sensitive topics unless the user brings them up. Meta says the feature is being tested and rolled out gradually.

The company hopes it will not only improve user retention but also serve as a response to what CEO Mark Zuckerberg calls the ‘loneliness epidemic’.

With revenue from generative AI tools projected to reach up to $3 billion in 2025, Meta’s focus on more prolonged and engaging chatbot interactions appears to be as strategic as social.

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X to test AI-generated Community Notes

X, the social platform formerly known as Twitter, is preparing to test a new feature allowing AI chatbots to generate Community Notes.

These notes, a user-driven fact-checking system expanded under Elon Musk, are meant to provide context on misleading or ambiguous posts, such as AI-generated videos or political claims.

The pilot will enable AI systems like Grok or third-party large language models to submit notes via API. Each AI-generated comment will be treated the same as a human-written one, undergoing the same vetting process to ensure reliability.

However, concerns remain about AI’s tendency to hallucinate, where it may generate inaccurate or fabricated information instead of grounded fact-checks.

A recent research paper by the X Community Notes team suggests that AI and humans should collaborate, with people offering reinforcement learning feedback and acting as the final layer of review. The aim is to help users think more critically, not replace human judgment with machine output.

Still, risks persist. Over-reliance on AI, particularly models prone to excessive helpfulness rather than accuracy, could lead to incorrect notes slipping through.

There are also fears that human raters could become overwhelmed by a flood of AI submissions, reducing the overall quality of the system. X intends to trial the system over the coming weeks before any wider rollout.

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Croatia turns bus stops into AI-powered health stations

Croatia has introduced a groundbreaking public health campaign that uses AI and interactive billboards to tackle undiagnosed spinal issues. The initiative, led by Croatia Poliklinika, has provided over 100,000 free posture screenings and reached nearly 78% of the country’s population.

By converting bus stops into makeshift health stations, the project enables passers-by to receive posture checks via AI-powered digital billboards. The system analyses spine alignment at eight points and offers instant feedback, encouraging users to seek specialist help through a QR code.

The campaign has sparked immediate behavioural change, with 97% of people adjusting their posture during the scan. Since its launch, Croatia has seen a 46% rise in preventive spine check-ups, turning passive advertising spaces into tools for public well-being.

Croatia Poliklinika, which operates nine clinics nationwide, says the project demonstrates how digital infrastructure can reshape healthcare accessibility. The success is being hailed as a model for how technology can redefine public health engagement in everyday spaces.

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Amazon reaches one million warehouse robots

Amazon has reached a major milestone with over one million robots now operating in its warehouses.

The one millionth robot, recently deployed to a facility in Japan, marks 13 years since the tech giant began introducing automation through its acquisition of Kiva Systems in 2012.

The robotic presence is fast approaching parity with Amazon’s human workforce, according to The Wall Street Journal. Robots now assist in around 75% of the company’s global deliveries.

The company continues to upgrade its robotic fleet, recently unveiling Vulcan — a dual-armed model equipped with a suction grip and a sense of touch to handle items more delicately.

Amazon is also introducing DeepFleet, a new generative AI model built using Amazon SageMaker.

Designed to optimise robotic movement within fulfilment centres, DeepFleet is expected to improve fleet speed by 10%. The model is trained on Amazon’s operational data, making it highly tailored to the company’s logistical network.

The expansion comes as Amazon opens next-generation fulfilment centres featuring ten times more robots instead of relying solely on existing warehouse models. The first of these facilities opened in late 2024 in Shreveport, Louisiana, signalling a shift toward even greater automation.

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Pentagon backs $10M deal with AI firm to integrate LLMs across its command centres

Pentagon officials have awarded AI firm Ask Sage a $10 million contract to integrate large language models (LLMs) across all US Combatant Commands, the Joint Staff, and the Office of the Secretary of Defence. The collaboration seeks to harness generative AI to speed up battlefield decision‑making and streamline workflows.

Application benefits include operational planning, logistics, command and control, intelligence, cybersecurity, and weapons development. Ask Sage’s AI‑powered tools will be deployed through the US Army’s LLM workspace, seamlessly linking classified and unclassified networks.

Deployment of these models is expected to support more agile, informed military operations while navigating security and data‑sharing challenges inherent to classified environments. The deal marks a strategic continuation of the Pentagon’s wider AI and digital transformation efforts.

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Cloudflare’s new tool lets publishers charge AI crawlers

Cloudflare, which powers 20% of the web, has launched a new marketplace called Pay per Crawl, aiming to redefine how website owners interact with AI companies.

The platform allows publishers to set a price for AI crawlers to access their content instead of allowing unrestricted scraping or blocking. Website owners can decide to charge a micropayment for each crawl, permit free access, or block crawlers altogether, gaining more control over their material.

Over the past year, Cloudflare introduced tools for publishers to monitor and block AI crawlers, laying the groundwork for the marketplace. Major publishers like Conde Nast, TIME and The Associated Press have joined Cloudflare in blocking AI crawlers by default, supporting a permission-based approach.

The company also now blocks AI bots by default on all new sites, requiring site owners to grant access.

Cloudflare’s data reveals that AI crawlers scrape websites far more aggressively than traditional search engines, often without sending equivalent referral traffic. For example, OpenAI’s crawler scraped sites 1,700 times for every referral, compared to Google’s 14 times.

As AI agents evolve to gather and deliver information directly, it raises challenges for publishers who rely on site visits for revenue.

Pay per Crawl could offer a new business model for publishers in an AI-driven world. Cloudflare envisions a future where AI agents operate with a budget to access quality content programmatically, helping users synthesise information from trusted sources.

For now, both publishers and AI companies need Cloudflare accounts to set crawl rates, with Cloudflare managing payments. The company is also exploring stablecoins as a possible payment method in the future.

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