Meta Platforms has acquired Manus, a Singapore-based developer of general-purpose AI agents, as part of its continued push to expand artificial intelligence capabilities. The deal underscores Meta’s strategy of acquiring specialised AI firms to accelerate product development.
Manus, founded in China before relocating to Singapore, develops AI agents capable of performing tasks such as market research, coding, and data analysis. The company said it reached more than $100 million in annualised revenue within eight months of launch and was serving millions of users worldwide.
Meta said the acquisition will help integrate advanced automation into its consumer and enterprise offerings, including the Meta AI assistant. Manus will continue operating its subscription service, and its employees will join Meta’s teams.
Financial terms were not disclosed, but media reports valued the deal at more than $2 billion. Manus had been seeking funding at a similar valuation before being approached by Meta and had recently raised capital from international investors.
The acquisition follows a series of AI-focused deals by Meta, including investments in Scale AI and AI device start-ups. Analysts say the move highlights intensifying competition among major technology firms to secure AI talent and capabilities.
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Protecting AI agents from manipulation has become a top priority for OpenAI after rolling out a major security upgrade to ChatGPT Atlas.
The browser-based agent now includes stronger safeguards against prompt injection attacks, where hidden instructions inside emails, documents or webpages attempt to redirect the agent’s behaviour instead of following the user’s commands.
Prompt injection poses a unique risk because Atlas can carry out actions that a person would normally perform inside a browser. A malicious email or webpage could attempt to trigger data exposure, unauthorised transactions or file deletion.
Criminals exploit the fact that agents process large volumes of content across an almost unlimited online surface.
OpenAI has developed an automated red-team framework that uses reinforcement learning to simulate sophisticated attackers.
When fresh attack patterns are discovered, the models behind Atlas are retrained so that resistance is built into the agent rather than added afterwards. Monitoring and safety controls are also updated using real attack traces.
These new protections are already live for all Atlas users. OpenAI advises people to limit logged-in access where possible, check confirmation prompts carefully and give agents well-scoped tasks instead of broad instructions.
The company argues that proactive defence is essential as agentic AI becomes more capable and widely deployed.
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Researchers are warning that AI chatbots may treat dialect speakers unfairly instead of engaging with them neutrally. Studies across English and German dialects found that large language models often attach negative stereotypes or misunderstand everyday expressions, leading to discriminatory replies.
A study in Germany tested ten language models using dialects such as Bavarian and Kölsch. The systems repeatedly described dialect speakers as uneducated or angry, and the bias became stronger when the dialect was explicitly identified.
Similar findings emerged elsewhere, including UK council services and AI shopping assistants that struggled with African American English.
Experts argue that such patterns risk amplifying social inequality as governments and businesses rely more heavily on AI. One Indian job applicant even saw a chatbot change his surname to reflect a higher caste, showing how linguistic bias can intersect with social hierarchy instead of challenging it.
Developers are now exploring customised AI models trained with local language data so systems can respond accurately without reinforcing stereotypes.
Researchers say bias can be tuned out of AI if handled responsibly, which could help protect dialect speakers rather than marginalise them.
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These rapidly produced AI videos aim to grab attention but make it harder for traditional creators to gain visibility. Analysis of top trending channels shows Spain leads in AI slop subscribers with 20.22 million, while South Korea’s channels have amassed 8.45 billion views.
India’s Bandar Apna Dost is the most-viewed AI slop channel, earning an estimated $4.25 million annually and showing the profit potential of mass AI-generated content.
The prevalence of AI slop and brainrot has sparked debates over creativity, ethics, and advertiser confidence. YouTube CEO Neal Mohan calls generative AI transformative, but rising automated videos raise concerns over quality and brand safety.
Researchers warn that repeated exposure to AI-generated content can distort perception and contribute to information overload. Some AI content earns artistic respect, but much normalises low-quality videos, making it harder for users to tell meaningful content from repetitive or misleading material.
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SoftBank Group has agreed to acquire DigitalBridge for $4 billion, strengthening its global digital infrastructure capabilities. The move aims to scale data centres, connectivity, and edge networks to support next-generation AI services.
The acquisition aligns with SoftBank’s mission to develop Artificial Super Intelligence (ASI), providing the compute power and connectivity needed to deploy AI at scale.
DigitalBridge’s global portfolio of data centres, cell towers, fibre networks, and edge infrastructure will enhance SoftBank’s ability to finance and operate these assets worldwide.
DigitalBridge will continue to operate independently under CEO Marc Ganzi. The transaction, valued at a 15% premium to its closing share price, is expected to close in the second half of 2026, pending regulatory approval.
SoftBank and DigitalBridge anticipate that the combined resources will accelerate investments in AI infrastructure, supporting the rapid growth of technology companies and fostering the development of advanced AI applications.
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China’s AI industry entered 2025 as a perceived follower but ended the year transformed. Rapid technical progress and commercial milestones reshaped global perceptions of Chinese innovation.
The surprise release of DeepSeek R1 demonstrated strong reasoning performance at unusually low training costs. Open access challenged assumptions about chip dominance and boosted adoption across emerging markets.
State backing and private capital followed quickly, lifting the AI’s sector valuations and supporting embodied intelligence projects. Leading model developers prepared IPO filings, signalling confidence in long term growth.
Chinese firms increasingly prioritised practical deployment, multilingual capability, and service integration. Global expansion now stresses cultural adaptation rather than raw technical benchmarks alone.
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UK outdoor enthusiasts are warned not to rely solely on AI for tide times or weather. Errors recently stranded visitors on Sully Island, showing the limits of unverified information.
Maritime authorities recommend consulting official sources such as the UK Hydrographic Office and Met Office. AI tools may misread tables or local data, making human oversight essential for safety.
Mountain rescue teams report similar issues when inexperienced walkers used AI to plan trips. Even with good equipment, lack of judgement can turn minor errors into dangerous situations.
Practical experience, professional guidance, and verified data remain critical for safe outdoor activities. Relying on AI alone can create serious risks, especially on tidal beaches and challenging mountain routes.
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Filmmakers in India are rapidly adopting AI tools like ChatGPT, Midjourney and Stable Diffusion to create visuals, clone voices, and streamline production processes for both independent and large-scale films.
Low-budget directors now produce nearly entire films independently, reducing costs and production time. Filmmakers use AI to visualise scenes, experiment creatively, and plan sound and effects efficiently.
AI cannot fully capture cultural nuance, emotional depth, or storytelling intuition, so human oversight remains essential. Intellectual property, labour protections, and ethical issues remain unresolved.
Hollywood has resisted AI, with strikes over rights and labour concerns. Indian filmmakers, however, carefully combine AI tools with human creativity to preserve artistic vision and cultural nuance.
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More than 20 percent of videos recommended to new YouTube users are low-quality, attention-driven content commonly referred to as AI slop, according to new research. The findings raise concerns about how recommendation systems shape early user experience on the platform.
Video-editing firm Kapwing analysed 15,000 of YouTube’s top channels across countries worldwide. Researchers identified 278 channels consisting entirely of AI-generated slop, designed primarily to maximise views rather than provide substantive content.
These channels have collectively amassed more than 63 billion views and 221 million subscribers. Kapwing estimates the network generates around $117 million in annual revenue through advertising and engagement.
To test recommendations directly, researchers created a new YouTube account and reviewed its first 500 suggested videos. Of these, 104 were classified as AI slop, with around one third falling into a category described as brainrot content.
Kapwing found that AI slop channels attract large audiences globally, including tens of millions of subscribers in countries such as Spain, Egypt, the United States, and Brazil. Researchers said the scale highlights the growing reach of low-quality AI-generated video content.
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OpenAI has launched GPT-5.2, highlighting improved safety performance in conversations involving mental health. The company said the update strengthens how its models respond to signs of suicide, self-harm, emotional distress, and reliance on the chatbot.
The release follows criticism and legal challenges accusing ChatGPT of contributing to psychosis, paranoia, and delusional thinking in some users. Several cases have highlighted the risks of prolonged emotional engagement with AI systems.
In response to a wrongful death lawsuit involving a US teenager, OpenAI denied responsibility while stating that ChatGPT encouraged the user to seek help. The company also committed to improving responses when users display warning signs of mental health crises.
OpenAI said GPT-5.2 produces fewer undesirable responses in sensitive situations than earlier versions. According to the company, the model scores higher on internal safety tests related to self-harm, emotional reliance, and mental health.
The update builds on OpenAI’s use of a training approach known as safe completion, which aims to balance helpfulness and safety. Detailed performance information has been published in the GPT-5.2 system card.
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