Can AI replace therapists?

With mental health waitlists at record highs and many struggling to access affordable therapy, some are turning to AI chatbots for support.

Kelly, who waited months for NHS therapy, found solace in character.ai bots, describing them as always available, judgment-free companions. ‘It was like a cheerleader,’ she says, noting how bots helped her cope with anxiety and heartbreak.

But despite emotional benefits for some, AI chatbots are not without serious risks. Character.ai is facing a lawsuit from the mother of a 14-year-old who died by suicide after reportedly forming a harmful relationship with an AI character.

Other bots, like one from the National Eating Disorder Association, were shut down after giving dangerous advice.

Even so, demand is high. In April 2024 alone, 426,000 mental health referrals were made in England, and over a million people are still waiting for care. Apps like Wysa, used by 30 NHS services, aim to fill the gap by offering CBT-based self-help tools and crisis support.

Experts warn, however, that chatbots lack context, emotional intuition, and safeguarding. Professor Hamed Haddadi calls them ‘inexperienced therapists’ that may agree too easily or misunderstand users.

Ethicists like Dr Paula Boddington point to bias and cultural gaps in the AI training data. And privacy is a looming concern: ‘You’re not entirely sure how your data is being used,’ says psychologist Ian MacRae.

Still, users like Nicholas, who lives with autism and depression, say AI has helped when no one else was available. ‘It was so empathetic,’ he recalls, describing how Wysa comforted him during a night of crisis.

A Dartmouth study found AI users saw a 51% drop in depressive symptoms, but even its authors stress bots can’t replace human therapists. Most experts agree AI tools may serve as temporary relief or early intervention—but not as long-term substitutes.

As John, another user, puts it: ‘It’s a stopgap. When nothing else is there, you clutch at straws.’

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Met Office and Microsoft debut AI-ready forecasting system

The UK’s Met Office has launched a new supercomputer designed to significantly improve weather and climate forecasting accuracy. Operated via Microsoft’s Azure cloud platform, it is the world’s first cloud-based supercomputer dedicated solely to weather and climate science.

Capable of performing 60 quadrillion calculations per second—more than four times faster than its predecessor—the system is expected to enhance 14-day forecasts, improve rainfall predictions, and offer better data for sectors like aviation and energy.

The infrastructure, split across two data centres in southern England, runs entirely on renewable energy. Originally announced in 2020 with a £1.2 billion UK government investment, the project faced delays due to COVID-19 and global supply chain disruptions.

Despite recent cyberattacks on UK institutions, Met Office officials say the new system has robust security and represents a major technological upgrade.

The Met Office also says the new system will support AI integration and provide better insights into climate change-related events, such as floods and wildfires.

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AI at 45W: Neuchips showcases energy-saving chips for LLMs

As global energy demand surges alongside AI growth, Neuchips is stepping up with energy-efficient solutions that deliver high performance while reducing power consumption.

The company will showcase its latest innovations at COMPUTEX 2025, including its Viper series AI accelerator cards, capable of running a 14-billion parameter model at just 45 watts — roughly the same power as a standard light bulb.

The announcement follows an International Energy Agency (IEA) report projecting that electricity demand from AI-powered data centers will more than quadruple by 2030. Neuchips CEO Ken Lau emphasised that power-efficient AI is now a necessity, not a luxury.

Neuchips’ hardware supports models like Mistral Small 3, Llama 3.3, and Gemma 3, offering offline LLM inference that enhances data privacy. Its solutions are compatible with both Intel and AMD CPUs, and run on Ubuntu and Windows.

The company is expanding its reach through several key partnerships. With Taiwan’s National Center for High-performance Computing (NCHC), Neuchips is delivering energy-efficient AI to the cloud while ensuring data security and cost efficiency.

Collaborating with MAPLE LEAF INFORMATION AND TECHNOLOGY and Vecow, the company offers compact AI systems that operate without requiring additional power infrastructure.

In partnership with GSH’s ShareGuru SQLPilot, Neuchips is showcasing advanced agentic AI applications for business intelligence and customer service. Additionally, through integration with myLLM’s myPDA platform, Neuchips is enabling hybrid cloud-edge AI deployments using its hardware.

With its efficient AI acceleration chips and strategic collaborations, Neuchips is advancing sustainable AI across edge and data center environments.

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UAE’s EDGE Group unveils AI Accelerator to power defence and tech

EDGE Group, a global leader in advanced technology and defence, has launched the Group AI Accelerator, a new Centre of Excellence (COE) focused on accelerating AI-driven innovation across its portfolio and facilities.

The initiative is part of EDGE’s broader strategy to support the UAE’s ambitions of becoming a high-tech global hub.

The Group AI Accelerator will develop and integrate AI projects to enhance core engineering capabilities and business services. It will also incubate UAE talent and advance the country’s knowledge-based economy.

Dr. Chaouki Kasmi, EDGE’s President of Technology & Innovation, said the initiative will ‘enable the prompt adoption of AI technologies’ and foster ‘positive disruption’ across key programmes.

Overseen by EDGE’s Technology & Innovation Cluster, the COE will be guided by a steering committee of local and global experts. Engineering and business excellence working groups will lead AI skunkworks projects, R&D in machine learning, and digital transformation efforts.

EDGE’s latest move builds on its commitment to operational excellence and positions the UAE at the forefront of AI and Industry 4.0 development.

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China launches first AI satellites in orbital supercomputer network

China has launched the first 12 satellites in a planned network of 2,800 that will function as an orbiting supercomputer, according to Space News.

Developed by ADA Space in partnership with Zhijiang Laboratory and Neijang High-Tech Zone, the satellites can process their own data instead of relying on Earth-based stations, thanks to onboard AI models.

Each satellite runs an 8-billion parameter AI model capable of 744 tera operations per second, with the group already achieving 5 peta operations per second in total. The long-term goal is a constellation that can reach 1,000 POPS.

The network uses high-speed laser links to communicate and shares 30 terabytes of data between satellites. The current batch also carries scientific tools, such as an X-ray detector for studying gamma-ray bursts, and can generate 3D digital twin data for uses like disaster response or virtual tourism.

The space-based computing approach is designed to overcome Earth-based limitations like bandwidth and ground station availability, which means less than 10% of satellite data typically reaches the surface.

Experts say space supercomputers could reduce energy use by relying on solar power and dissipating heat into space. The EU and the US may follow China’s lead, as interest in orbital data centres grows.

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Researchers believe AI transparency is within reach by 2027

Top AI researchers admit they still do not fully understand how generative AI models work. Unlike traditional software that follows predefined logic, gen AI models learn to generate responses independently, creating a challenge for developers trying to interpret their decision-making processes.

Dario Amodei, co-founder of Anthropic, described this lack of understanding as unprecedented in tech history. Mechanistic interpretability — a growing academic field — aims to reverse engineer how gen AI models arrive at outputs.

Experts compare the challenge to understanding the human brain, but note that, unlike biology, every digital ‘neuron’ in AI is visible.

Companies like Goodfire are developing tools to map AI reasoning steps and correct errors, helping prevent harmful use or deception. Boston University professor Mark Crovella says interest is surging due to the practical and intellectual appeal of interpreting AI’s inner logic.

Researchers believe the ability to reliably detect biases or intentions within AI models could be achieved within a few years.

This transparency could open the door to AI applications in critical fields like security, and give firms a major competitive edge. Understanding how these systems work is increasingly seen as vital for global tech leadership and public safety.

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JMA to test AI-enhanced weather forecasting

The Japan Meteorological Agency (JMA) is exploring the use of AI to improve the accuracy of weather forecasts, with a particular focus on deep learning technologies, according to a source familiar with the plans.

A dedicated team was launched in April to begin developing the infrastructure and tools needed to integrate AI with JMA’s existing numerical weather prediction models. The goal is to combine traditional simulations with AI-generated forecasts based on historical weather data.

If implemented, AI systems could identify weather patterns more efficiently and enhance forecasts for variables such as rainfall and temperature. The technology may also offer improved accuracy in predicting extreme weather events like typhoons.

Currently, the JMA relies on supercomputers to simulate future atmospheric conditions based on observational data. Human forecasters then review the outputs, applying expert judgment before issuing final forecasts and alerts. Even with AI integration, human oversight will remain a core part of the process.

In addition to forecasting, the agency is also considering AI for processing data from the Himawari-10 satellite, which is expected to launch in fiscal 2029.

An official announcement outlining further AI integration measures is anticipated in June.

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UK workers struggle to keep up with AI

AI is reshaping the UK workplace, but many employees feel unprepared to keep pace, according to a major new study by Henley Business School.

While 56% of full-time professionals expressed optimism about AI’s potential, 61% admitted they were overwhelmed by how quickly the technology is evolving.

The research surveyed over 4,500 people across nearly 30 sectors, offering what experts call a clear snapshot of AI’s uneven integration into British industries.

Professor Keiichi Nakata, director of AI at The World of Work Institute, said workers are willing to embrace AI, but often lack the training and guidance to do so effectively.

Instead of empowering staff through hands-on learning and clear internal policies, many companies are leaving their workforce under-supported.

Nearly a quarter of respondents said their employers were failing to provide sufficient help, while three in five said they would use AI more if proper training were available.

Professor Nakata argued that AI has the power to simplify tasks, remove repetitive duties, and free up time for more meaningful work.

But he warned that without better support, businesses risk missing out on what could be a transformative force for both productivity and employee satisfaction.

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AlphaEvolve by DeepMind automates code optimisation and discovers new algorithms

Google’s DeepMind has introduced AlphaEvolve, a new AI-powered coding agent designed to autonomously discover and optimise computer algorithms.

Built on large language models and evolutionary techniques, AlphaEvolve aims to assist experts across mathematics, engineering, and computer science by improving existing solutions and generating new ones.

Unlike natural language-based models, AlphaEvolve uses automated evaluators and iterative evolution strategies—like mutation and crossover—to refine algorithmic solutions.

DeepMind reports success across several domains, including matrix multiplication, data centre scheduling, chip design, and AI model training.

In one case, AlphaEvolve developed a new method for multiplying 4×4 complex matrices using just 48 scalar multiplications, surpassing a longstanding result from 1969. It also improved job scheduling in Google data centres, recovering an average of 0.7% of global compute resources.

In mathematical tests, AlphaEvolve rediscovered known solutions 75% of the time and improved them in 20% of cases. While experts have praised its potential, researchers also stress the importance of secure deployment and responsible use.

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du and Microsoft launch $544M AI data centre in UAE

Emirates Integrated Telecommunications Company PJSC (du) has partnered with Microsoft to build a 2 billion dirham (US$544.5 million) hyperscale data centre in the UAE, unveiled during Dubai AI Week.

Microsoft will be the facility’s primary tenant, and the project will be delivered in phases. This marks du’s sixth data centre, reinforcing the UAE’s growing status as a regional AI and data infrastructure hub.

The partnership aligns with the UAE’s National Strategy for AI 2031, which aims to generate US$96 billion in economic value by 2030.

Hyperscale data centres like this one are expected to form the backbone of the country’s AI ecosystem, which is projected to reach a value of US$46.33 billion by the same year.

The GCC data centre market is booming, with expected growth from US$3.48 billion in 2024 to US$9.49 billion by 2030. du’s move comes amid a regional race between cloud giants like Google, AWS, and Oracle, as well as local providers including Khazna, Equinix, and Gulf Data Hub.

Sustainability is also a growing focus, with new builds like Khazna’s Ajman facility incorporating energy-efficient cooling for high-performance AI workloads.

As AI-driven transformation accelerates across logistics, finance, and smart cities, the UAE is using these strategic partnerships and infrastructure investments to move from a resource-based economy to a data-driven one.

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