Wikipedia has paused a controversial trial of AI-generated article summaries following intense backlash from its community of volunteer editors.
The Wikimedia Foundation had planned a two-week opt-in test for mobile users using summaries produced by Aya, an open-weight AI model developed by Cohere.
However, the reaction from editors was swift and overwhelmingly negative. The discussion page became flooded with objections, with contributors arguing that such summaries risked undermining the site’s reputation for neutrality and accuracy.
Some expressed concerns that inserting AI content would override Wikipedia’s long-standing collaborative approach by effectively installing a single, unverifiable voice atop articles.
Editors warned that AI-generated summaries lacked proper sourcing and could compromise the site’s credibility. Recent AI blunders by other tech giants, including Google’s glue-on-pizza mishap and Apple’s false death alert, were cited as cautionary examples of reputational risk.
For many, the possibility of similar errors appearing on Wikipedia was unacceptable.
Marshall Miller of the Wikimedia Foundation acknowledged the misstep in communication and confirmed the project’s suspension.
While the Foundation remains interested in exploring AI to improve accessibility, it has committed to ensuring any future implementation involves direct participation from the Wikipedia community.
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What began as a company powering 3D games in the 1990s has evolved into the backbone of the global AI revolution. Nvidia, once best known for its Riva TNT2 chips in consumer graphics cards like the Elsa Erazor III, now sits at the centre of scientific computing, defence, and national-scale innovation.
While gaming remains part of its identity—with record revenue of $3.8 billion in Q1 FY2026—it now accounts for less than 9% of Nvidia’s $44.1 billion total revenue. The company’s trajectory reflects its founder Jensen Huang’s ambition to lead beyond the gaming space, targeting AI, supercomputing, and global infrastructure.
Recent announcements reinforce this shift. Huang joined UK Prime Minister Sir Keir Starmer to open London Tech Week, affirming Nvidia’s commitment to launch an AI lab in the UK, as the government commits £1 billion to AI compute by 2030.
Nvidia also revealed its Rubin-Vera superchip will power Germany’s ‘Blue Lion’ supercomputer, and its Grace Hopper platform is at the heart of Jupiter—Europe’s first exascale AI system, located at the Jülich Supercomputing Centre.
Nvidia’s presence now spans continents and disciplines, from powering national research to driving breakthroughs in climate modelling, quantum computing, and structural biology.
‘AI will supercharge scientific discovery and industrial innovation,’ said Huang. And with systems like Jupiter poised to run a quintillion operations per second, the company’s growth story is far from over.
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Global R&D spending now exceeds $2 trillion a year, yet many companies still rely on intuition rather than evidence to shape innovation strategies—often at great cost.
TechNext, co-founded by Anuraag Singh and MIT’s Prof. Christopher L. Magee, aims to change that with a newly patented system that delivers data-driven forecasts for technology performance.
Built on large-scale empirical datasets and proprietary algorithms, the system enables organisations to anticipate which technologies are likely to improve most rapidly.
‘R&D has become one of the fastest-growing expenses for companies, yet most decisions still rely on intuition rather than data,’ said Singh. ‘We have been flying blind’
The tool has already drawn attention from major stakeholders, including the United States Air Force, multinational firms, VCs, and think tanks.
By quantifying the future of technologies—from autonomous vehicle perception systems to clean energy infrastructure—TechNext promises to help decision-makers avoid expensive dead ends and focus on long-term winners.
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The UK government has unveiled new guidance for schools that promotes the use of AI to reduce teacher workloads and increase face-to-face time with pupils.
The Department for Education (DfE) says AI could take over time-consuming administrative tasks such as lesson planning, report writing, and email drafting—allowing educators to focus more on classroom teaching.
The guidance, aimed at schools and colleges in the UK, highlights how AI can assist with formative assessments like quizzes and low-stakes feedback, while stressing that teachers must verify outputs for accuracy and data safety.
It also recommends using only school-approved tools and limits AI use to tasks that support rather than replace teaching expertise.
Education unions welcomed the move but said investment is needed to make it work. Leaders from the NAHT and ASCL praised AI’s potential to ease pressure on staff and help address recruitment issues, but warned that schools require proper infrastructure and training.
Education Secretary Bridget Phillipson said the plan will free teachers to deliver more personalised support, adding: ‘We’re putting cutting-edge AI tools into the hands of our brilliant teachers to enhance how our children learn and develop.’
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In a new blog post titled The Gentle Singularity, OpenAI CEO Sam Altman predicted that AI systems capable of producing ‘novel insights’ may arrive as early as 2026.
While Altman’s essay blends optimism with caution, it subtly signals the company’s next central ambition — creating AI that goes beyond repeating existing knowledge and begins generating original ideas instead of mimicking human reasoning.
Altman’s comments echo a broader industry trend. Researchers are already using OpenAI’s recent o3 and o4-mini models to generate new hypotheses. Competitors like Google, Anthropic and FutureHouse are also shifting their focus towards scientific discovery.
Google’s AlphaEvolve has reportedly devised novel solutions to complex maths problems, while FutureHouse claims to have built AI capable of genuine scientific breakthroughs.
Despite the optimism, experts remain sceptical. Critics argue that AI still struggles to ask meaningful questions, a key ingredient for genuine insight.
Former OpenAI researcher Kenneth Stanley, now leading Lila Sciences, says generating creative hypotheses is a more formidable challenge than agentic behaviour. Whether OpenAI achieves the leap remains uncertain, but Altman’s essay may hint at the company’s next bold step.
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A recent study by Apple researchers exposed significant limitations in the capabilities of advanced AI systems and huge reasoning models (LRMs).
Apple’s team suggested this may point to a fundamental limit in how current AI models scale up to general reasoning.
These models, designed to solve complex problems through step-by-step thinking, experienced what the paper called a ‘complete accuracy collapse’ when faced with high-complexity tasks. Even when given an algorithm that should have ensured success, the models failed to deliver correct solutions.
The study found that LRMs performed well with low- and medium-difficulty tasks but deteriorated sharply as the complexity increased.
Rather than increasing their effort as problems became harder, the models reduced their reasoning paradoxically, leading to complete failure.
Experts, including AI researcher Gary Marcus and University of Surrey’s Andrew Rogoyski in the UK, called the findings alarming and indicative of a potential dead end in current AI development.
The study tested systems from OpenAI, Google, Anthropic and DeepSeek, raising serious questions about how close the industry is to achieving AGI.
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According to new government guidance, teachers in England are now officially encouraged to use AI to reduce administrative tasks. The Department for Education has released training materials that support the use of AI for low-stakes marking and routine parent communication.
The guidance allows AI-generated letters, such as those informing parents about minor issues like head lice outbreaks, and suggests using the technology for quizzes or homework marking.
While the move aims to cut workloads and improve classroom focus, schools are also advised to implement clear policies on appropriate use and ensure manual checks remain in place.
Experts have welcomed the guidance as a step forward but noted concerns about data privacy, budget constraints, and potential misuse.
The guidance comes as UK nations explore AI in education, with Northern Ireland commissioning a study on its impact and Scotland and Wales also advocating its responsible use.
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OpenAI has revealed that its annualised revenue has surged to $10 billion as of June 2025, nearly doubling since December 2024, when it stood at $5.5 billion.
The rapid growth is driven by the widespread adoption of its ChatGPT AI models across consumer and business markets, putting the company on course to meet its earlier goal of $12.7 billion in revenue for the whole year.
The $10 billion figure excludes licensing income from Microsoft, a major investor, and some large one-off contracts, according to an OpenAI spokesperson. Despite recording a loss of about $5 billion last year, OpenAI’s impressive revenue scale places it well ahead of many rivals benefiting from the AI boom.
Other players in the AI space are also seeing strong growth. For instance, Anthropic recently surpassed $3 billion in annualised revenue, driven by startup demand using its code-generation models. Meanwhile, OpenAI plans to raise up to $40 billion in new funding, valuing the company at $300 billion.
Since launching ChatGPT over two years ago, OpenAI has expanded its offerings with various subscription plans and services. The company reported 500 million weekly active users as of March 2025, underscoring its dominant position in the AI market.
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TikTok has announced plans to expand its UK operations significantly, adding over 500 new jobs and investing in a significant new office in London.
Despite ongoing scrutiny from Western governments over data security and alleged ties to the Chinese state, TikTok insists it invests heavily in trust and safety.
The company already employs 2,500 people in the country and will bring its UK workforce to 3,000 by the end of 2025.
The announcement coincides with London Tech Week, where Prime Minister Keir Starmer welcomed major global tech firms to showcase innovation and economic commitment.
TikTok’s UK director, Adam Presser, described the country as the platform’s largest user community in Europe, with over 30 million monthly users.
He emphasised that the company’s growth strategy includes commitments to digital safety and economic support for local creators and entrepreneurs.
Company leaders have reiterated that they aim to create a secure space while supporting the broader economy through innovation and job creation.
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XRobotics, a San Francisco-based startup, is gaining traction in the food tech sector with its compact pizza-making robot, the xPizza Cube. Roughly the size of a washing machine, the machine uses AI to apply sauce, cheese and toppings, producing up to 100 pizzas per hour.
At $1,300 monthly on a three-year lease, it’s designed to fit seamlessly into existing kitchens and support, not replace, staff. Unlike failed predecessors such as Zume, XRobotics has found success by offering assistive rather than disruptive technology.
Their initial, larger model proved impractical, but the current compact version, launched in 2023, now produces 25,000 pizzas each month across an undisclosed number of customer locations. Both small pizzerias and large chains use the robot to cut labour time and improve consistency.
With over 73,000 pizza outlets in the US, XRobotics plans to stay focused on pizza for now. Its founders, self-professed pizza lovers, say customer response has confirmed that a well-targeted tool can significantly impact even the most traditional kitchens.
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