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 round was led by ClearSky, with backing from Phoenix Financial, Glilot Capital Partners, SentinelOne, Hanaco Ventures, and others, bringing the company’s total funding to $84 million in just over two years.
Since emerging from stealth in early 2023, Guardz has built a global presence, partnering with hundreds of MSPs to secure thousands of small and mid-sized businesses.
With the new capital, the company aims to accelerate go-to-market efforts and enhance its platform with more automation, compliance tools, and cyber insurance capabilities.
The Guardz platform integrates threat protection across identities, email, endpoints, cloud, and data into a single engine. Combining AI-driven automation with human-led Managed Detection and Response (MDR), it provides 24/7 monitoring and rapid response to threats.
Seamless integrations with Microsoft 365 and Google Workspace allow MSPs to pre-emptively detect suspicious activity and respond in real time.
‘Our goal is to empower MSPs with enterprise-grade security tools to protect the global economy’s most vulnerable targets — small and mid-sized businesses,’ said Guardz CEO and co-founder Dor Eisner. ‘This funding allows us to further that mission and help businesses thrive in a secure environment.’
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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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OpenAI has rolled out its most advanced AI model yet, o3-Pro, delivering significant improvements in reasoning and task complexity while introducing steep price reductions.
The model is now available to ChatGPT Pro and Team users, with Enterprise and Education access coming next week. Developers can also access it via OpenAI’s API.
O3-Pro is designed for high-performance use across technology, education, and science sectors. It supports advanced capabilities such as web browsing, code execution, file analysis, and memory retention during conversations.
Despite these upgrades, pricing has been reduced drastically—87% lower than o1-Pro—costing just $20 per million input tokens and $80 per million output tokens. The base o3 model has also seen an 80% price cut.
Evaluators consistently rated o3-Pro higher than previous models for clarity, instruction-following, and accuracy, with standout results in benchmarks like AIME 2024 and GPQA Diamond, where it beat Google’s Gemini 2.5 Pro and Claude 4 Opus, respectively.
Although the model lacks image generation and Canvas support, its reasoning capabilities mark a major step forward in OpenAI’s AI offerings.
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Meta Platforms is set to acquire a 49 percent stake in Scale AI for nearly $15 billion, marking its largest-ever deal.
CEO Mark Zuckerberg sees The agreement as a significant move to accelerate Meta’s push into AI instead of relying solely on in-house development.
Scale AI, founded in 2016, supplies curated training data to major players such as OpenAI, Google, Microsoft and Meta. The company expects to more than double its revenue in 2025 to around $2 billion.
Once the deal is finalised, Scale AI CEO Alexandr Wang is expected to join Meta’s new AI team focused on developing artificial general intelligence (AGI).
The effort aligns with Meta’s broader AI plans, including capital expenditure of up to $65 billion in 2025 to expand its AI infrastructure instead of falling behind rivals in the AI race.
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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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