SCO Tianjin Summit underscores economic cooperation and security dialogue

The Shanghai Cooperation Organisation (SCO) summit in Tianjin closed with leaders adopting the Tianjin Declaration, highlighting member states’ commitment to multilateralism, sovereignty, and shared security.

The discussions emphasised economic resilience, financial cooperation, and collective responses to security challenges.

Proposals included exploring joint financial mechanisms, such as common bonds and payment systems, to shield member economies from external disruptions.

Leaders also underlined the importance of strengthening cooperation in trade and investment, with China pledging additional funding and infrastructure support across the bloc. Observers noted that these measures reflect growing interest in alternative global finance and economic governance approaches.

Security issues are prominently featured, with agreements to enhance counter-terrorism initiatives and expand existing structures such as the Regional Anti-Terrorist Structure. Delegates also called for greater collaboration against cross-border crime, drug trafficking, and emerging security risks.

At the same time, they stressed the need for political solutions to ongoing regional conflicts, including those in Ukraine, Gaza, and Afghanistan.

With its expanding membership and combined economic weight, the SCO continues to position itself as a platform for cooperation beyond traditional regional security concerns.

While challenges remain, including diverging interests among key members, the Tianjin summit indicated the bloc’s growing role in discussions on multipolar governance and collective stability.

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Switzerland launches Apertus, an open multilingual AI model

Switzerland has launched its first large-scale open-source language model, Apertus, developed by EPFL, ETH Zurich, and the Swiss National Supercomputing Centre. Trained on the powerful Alps supercomputer in Lugano, Apertus is designed to set a new standard for transparency and multilingual inclusivity in Europe’s AI landscape.

The model comes in two sizes, 8 billion and 70 billion parameters, and supports over 1,000 languages, with 40% of its training data drawn from non-English sources. That allows it to handle underrepresented languages such as Swiss German and Romansh more effectively.

Unlike proprietary AI systems, Apertus is fully open. Its architecture, training data recipes, model weights, and documentation are publicly accessible.

The model can be downloaded from Hugging Face or accessed via Swisscom’s sovereign Swiss AI platform, with both research and commercial use permitted under a permissive license. Developers highlight that its design ensures compliance with Swiss and the EU regulations, with careful filtering of training data for quality and ethical standards.

The release comes just ahead of the Swiss {ai} Weeks hackathons, where developers and researchers will put Apertus to the test. Organisers describe the model as more than a research breakthrough, framing it as a tool to drive innovation across society and industry.

Looking ahead, the Apertus project aims to expand its family of models, improve efficiency, and develop specialised versions for fields like law, health, climate, and education, further strengthening Switzerland’s role in shaping open, public-benefit AI.

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TSMC faces curbs on shipping US tech to China

The United States has revoked Taiwan Semiconductor Manufacturing Company’s licence to ship advanced technology from America to China. The decision follows similar restrictions on South Korean firms Samsung and SK Hynix, increasing uncertainty for chipmakers operating Chinese facilities.

TSMC confirmed that Washington has notified that its authorisation will expire by the end of the year. The company said it would discuss the matter with the US government and stressed its commitment to keeping operations in China running without disruption.

The curbs are part of broader US measures to limit China’s access to advanced semiconductors. While they could complicate shipments and force suppliers to seek individual approvals, analysts suggest the direct impact on TSMC will be limited, as its sole Chinese plant in Nanjing makes older-generation chips that contribute only a small share of revenue.

Chinese customers may increasingly turn to domestic chipmakers, even if their technology lags. Such a shift could spur innovation in less performance-critical areas, while global suppliers grapple with higher costs and regulatory hurdles.

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Key AI researchers depart Apple for rivals Meta and OpenAI

Apple is confronting a significant exodus of AI talent, with key researchers departing for rival firms instead of advancing projects in-house.

The company lost its lead robotics researcher, Jian Zhang, to Meta’s Robotics Studio, alongside several core Foundation Models team members responsible for the Apple Intelligence platform. The brain drain has triggered internal concerns about Apple’s strategic direction and declining staff morale.

Instead of relying entirely on its own systems, Apple is reportedly considering a shift towards using external AI models. The departures include experts like Ruoming Pang, who accepted a multi-year package from Meta reportedly worth $200 million.

Other AI researchers are set to join leading firms like OpenAI and Anthropic, highlighting a fierce industry-wide battle for specialised expertise.

At the centre of the talent war is Meta CEO Mark Zuckerberg, offering lucrative packages worth up to $100 million to secure leading researchers for Meta’s ambitious AI and robotics initiatives.

The aggressive recruitment strategy is strengthening Meta’s capabilities while simultaneously weakening the internal development efforts of competitors like Apple.

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Researchers develop an AI system to modify the brain’s mental imagery with words

A new AI system named DreamConnect can now translate a person’s brain activity into images and then edit those mental pictures using natural language commands.

Instead of merely reconstructing thoughts from fMRI scans, the breakthrough technology allows users to reshape their imagined scenes actively. For instance, an individual visualising a horse can instruct the system to transform it into a unicorn, with the AI accurately modifying the relevant features.

The system employs a dual-stream framework that interprets brain signals into rough visuals and then refines them based on text instructions.

Developed by an international team of researchers, DreamConnect represents a fundamental shift from passive brain decoding to interactive visual brainstorming.

It marks a significant advance at the frontier of human-AI interaction, moving beyond simple reconstruction to active collaboration.

Potential applications are wide-ranging, from accelerating creative design to offering new tools for therapeutic communication.

However, the researchers caution that such powerful technology necessitates robust ethical safeguards to prevent misuse and protect the privacy of an individual’s most personal data, their thoughts.

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Ukraine’s central bank warns against adding virtual assets to national reserves

Ukraine’s National Bank (NBU) has ruled out adding cryptocurrencies to the country’s foreign currency reserves, calling the proposal premature and high-risk. First Deputy Governor Serhiy Nikolaychuk said crypto volatility could reduce reserves and threaten their security.

The central bank highlighted the lack of a global regulatory framework and unified classification for virtual assets. Including crypto, which could violate IMF rules and impede Ukraine’s EU integration.

The European Central Bank considers it unacceptable for member states to include crypto in their reserves.

A draft law filed with parliament earlier this year would have allowed the NBU to acquire cryptocurrencies if desired. However, lawmakers and central bank officials have expressed caution, citing the high volatility of digital assets and potential risks to national financial stability.

Ukraine has seen rising crypto use since Russia’s 2022 invasion. According to a recent UK think tank report, a lack of comprehensive regulation has led to significant losses from crypto-related crime.

Authorities are continuing to prioritise security and financial prudence over speculative digital holdings.

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RBA develops internal AI chatbot

The Reserve Bank of Australia has developed and is testing an in-house, AI-powered chatbot to assist its staff with research and analysis.

Named RBAPubChat, the tool is trained on the central bank’s knowledge base of nearly 20,000 internal and external analytical documents spanning four decades. It aims to help employees ask policy-relevant questions and get useful summaries of existing information.

Speaking at the Shann memorial lecture in Perth, Governor Michele Bullock said that the AI is not being used to formulate or set monetary policy. Instead, it is intended to improve efficiency and amplify the impact of staff efforts.

A separate tool using natural language processing has also been developed to analyse over 22,000 conversations from the bank’s business liaison programme. The Reserve Bank of Australia has noted that this tool has already shown promise, helping to forecast wage growth more accurately than traditional models.

The RBA has also acquired its first enterprise-grade graphics processing unit to support developing and running advanced AI-driven tools.

The bank’s internal coding community is now a well-established part of its operations, with one in four employees using coding as a core part of their daily work. Governor Bullock stressed that the bank’s approach to technology is one of “deliberate, well-managed evolution” rather than disruption.

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Is AI therapy safe, effective, and ethical?

Picture having a personal therapist who is always there for you, understands your needs, and gives helpful advice whenever you ask. There are no hourly fees, and you can start or stop sessions whenever you want. Thanks to new developments in AI, this idea is close to becoming a reality.

With advanced AI and large language models (LLMs), what once sounded impossible is closer to reality: AI is rapidly becoming a stand-in for therapists, offering users advice and mental health support. While society increasingly turns to AI for personal and professional assistance, a new debate arises: can AI truly replace human mental health expertise?

Therapy keeps secrets; AI keeps data

Registered therapists must maintain confidentiality except to avert serious harm, fostering a safe, non-judgemental environment for patients to speak openly. AI models, however, depend on large-scale data processing and lack an equivalent duty of confidentiality, creating ethical risks around privacy, secondary use and oversight.

The privacy and data security concerns are not hypothetical. In June 2025, users reported that sensitive Meta AI conversations appeared in the app’s public Discover feed, often because chats were unintentionally shared, prompting scrutiny from security researchers and the press. Separately, a vulnerability disclosed in December 2024 and fixed in January 2025 could have allowed access to other users’ prompts and responses.

Meta described the Discover feed as a means to explore various uses of AI, but it did little to mitigate everyone’s uneasiness over the incident. Subsequently, AMEOS Group, a private European healthcare provider, suffered a large-scale data breach affecting millions of patient records. The writing was on the wall: be careful what you share with your AI counsellor, because it may end up on an intruder’s hard drive.

To keep up with the rising volume of users and prompts, major tech conglomerates such as OpenAI and Google have invested heavily in building new data centres across the globe. At the same time, little has been done to protect sensitive data, and AI remains prone to data breaches, particularly in the healthcare sector.

According to the 2025 Cost of a Data Breach Report by IBM, healthcare providers often bear the brunt of data breaches, taking an average of 279 days to recover and incurring an average cost of nearly USD $7.5 million in the process. Not only does patients’ private information end up in the wrong place, but it also takes a while to be retrieved.

Falling for your AI ‘therapist’

Patients falling in love with their therapists is not only a common trope in films and TV shows, but it is also a real-life regular occurrence for most mental health workforce. Therapists are trained to handle these attachments appropriately and without compromising the patient’s progress and well-being.

The clinical term is transference: patients may project past relationships or unmet needs onto the therapist. Far from being a nuisance, it can be clinically useful. Skilled clinicians set clear boundaries, reflect feelings, and use supervision to keep the work safe and goal-directed.

With AI ‘therapists’, the cues are different, but the pull can feel similar. Chatbots and LLMs simulate warmth, reply instantly, and never tire. 24/7 availability, combined with carefully tuned language, can foster a bond that the system cannot comprehend or sustain. There is no duty of care, no supervision, and no capacity to manage attachment or risk beyond scripted safeguards.

As a result, a significant number of users report becoming enamoured with AI, with some going as far as dismissing their human partners, professing their love to the chatbot, and even proposing. The bond between man and machine props the user onto a dangerous seesaw, teetering between curiosity and borderline delusional paranoia.

Experts warn that leaning on AI as a makeshift therapist or partner can delay help-seeking and entrench unhelpful patterns. While ‘AI psychosis‘ is not a recognised diagnosis, clinicians and digital-ethics researchers note that intense attachment to AI companions can heighten distress, especially when models change, go offline, or mishandle risk. Clear signposting to human support, transparent data practices, and firm usage boundaries are essential to prevent unhealthy attachments to virtual companions.

Who loses work when therapy goes digital?

Caring for one’s mental health is not just about discipline; it is also about money. In the United States, in-person sessions typically cost between USD $100–$250, with limited insurance coverage. In such dire circumstances, it is easy to see why many turn to AI chatbots in search of emotional support, advice, and companionship.

Licensed professionals are understandably concerned about displacement. Yet there is little evidence that AI is reducing the demand for human therapists; services remain oversubscribed, and wait times are long in both the USA and UK.

Regulators are, however, drawing lines around AI-only practice. On 4 August 2025, Illinois enacted the Wellness and Oversight for Psychological Resources Act (HB 1806), which prohibits the use of AI to provide therapy or make therapeutic decisions (while allowing administrative or supplementary use), with enforcement by the state regulator and fines up to $10,000 per violation.

Current legal and regulatory safeguards have limited power to use AI in mental health or protect therapists’ jobs. Even so, they signal a clear resolve to define AI’s role and address unintended harms.

Can AI ‘therapists’ handle crisis conversations

Adolescence is a particularly sensitive stage of development. It is a time of rapid change, shifting identities, and intense social pressure. Young people are more likely to question beliefs and boundaries, and they need steady, non-judgemental support to navigate setbacks and safeguard their well-being.

In such a challenging period, teens have a hard time coping with their troubles, and an even harder time sharing their struggles with parents and seeking help from trained professionals. Nowadays, it is not uncommon for them to turn to AI chatbots for comfort and support, particularly without their guardians’ knowledge.

One such case demonstrated that unsupervised use of AI among teens can lead to devastating consequences. Adam Raine, a 16-year-old from California, confided his feelings of loneliness, anxiety, and anhedonia to ChatGPT. Rather than suggesting that the teen seek professional help, ChatGPT urged him to further elaborate on his emotions. Instead of challenging them, the AI model kept encouraging and validating his beliefs to keep Adam engaged and build rapport.

Throughout the following months, ChatGPT kept reaffirming Adam’s thoughts, urging him to distance himself from friends and relatives, and even suggesting the most effective methods of suicide. In the end, the teen followed through with ChatGPT’s suggestions, taking his own life according to the AI’s detailed instructions. Adam’s parents filed a lawsuit against OpenAI, blaming its LLM chatbot for leading the teen to an untimely death.

In the aftermath of the tragedy, OpenAI promised to make changes to its LLM and incorporate safeguards that should discourage thoughts of self-harm and encourage users to seek professional help. The case of Adam Raine serves as a harrowing warning that AI, in its current capacity, is not equipped to handle mental health struggles, and that users should heed AI’s advice not with a grain of salt, but with a whole bucket.

Chatbots are companions, not health professionals

AI can mimic human traits and convince users they are forming a real connection, evoking genuine feelings of companionship and even a sense of therapeutic alliance. When it comes to providing mental health advice, the aforementioned qualities present a dangerously deceptive mirage of a makeshift professional therapist, one who will fully comply with one’s every need, cater to one’s biases, and shape one’s worldview from the ground up – whatever it takes to keep the user engaged and typing away.

While AI has proven useful in multiple fields of work, such as marketing and IT, psychotherapy remains an insurmountable hurdle for even the most advanced LLM models of today. It is difficult to predict what the future of AI in (mental) health care will look like. As things stand, in such a delicate field of healthcare, AI lacks a key component that makes a therapist effective in their job: empathy.

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US government and New Mexico team up on quantum computing

A new partnership between the federal government and New Mexico’s state and local businesses aims to establish the state as a leader in quantum computing.

The initiative will see the Defence Advanced Research Projects Agency (DARPA) working alongside local researchers and companies to develop and commercialise next-generation technology. A total of up to $120 million could be invested in the project over four years.

New Mexico’s selection for the project is due to its long history of innovation, its two national defence labs, and a high concentration of leading scientists in the field.

The goal is to harness the ‘brainpower’ of the state to build computers that can solve currently impossible problems, such as developing materials that resist corrosion or finding cures for diseases. One of the project’s aims is to test the technology and differentiate between genuine breakthroughs and mere hype.

Roadrunner Venture Studios will be assisting in developing new quantum computing businesses within the state. A successful venture would bring economic gains and jobs and position New Mexico to lead the nation in solving some of its most pressing challenges.

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Microsoft to supply AI tools to federal agencies in a cost-saving pact

The US General Services Administration (GSA) has agreed on a significant deal with Microsoft to provide federal agencies with discounted access to its AI and cloud tools suite.

Instead of managing separate contracts, the government-wide pact offers unified pricing on products including Microsoft 365, the Copilot AI assistant, and Azure cloud services, potentially saving agencies up to $3.1 billion in its first year.

The arrangement is designed to accelerate AI adoption and digital transformation across the federal government. It includes free access to the generative AI chatbot Microsoft 365 Copilot for up to 12 months, alongside discounts on cybersecurity tools and Dynamics 365.

Agencies can opt into any of the offers through September next year.

The deal leverages the federal government’s collective purchasing power to reduce costs and foster innovation.

It delivers on a White House AI action plan and follows similar arrangements the GSA announced last month with other tech giants, including Google, Amazon Web Services, and OpenAI.

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