Google has patched a high-severity flaw in its Chrome browser with the release of version 139, addressing vulnerability CVE-2025-9132 in the V8 JavaScript engine.
The out-of-bounds write issue was discovered by Big Sleep AI, a tool built by Google DeepMind and Project Zero to automate vulnerability detection in real-world software.
Chrome 139 updates (Windows/macOS: 139.0.7258.138/.139, Linux: 139.0.7258.138) are now rolling out to users. Google has not confirmed whether the flaw is being actively exploited.
Users are strongly advised to install the latest update to ensure protection, as V8 powers both JavaScript and WebAssembly within Chrome.
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A new study reveals that prominent AI models now show a marked preference for AI‑generated content over that created by humans.
Tests involving GPT‑3.5, GPT-4 and Llama 3.1 demonstrated a consistent bias, with models selecting AI‑authored text significantly more often than human‑written equivalents.
Researchers warn this tendency could marginalise human creativity, especially in fields like education, hiring and the arts, where original thought is crucial.
There are concerns that such bias may arise not by accident but by design flaws embedded within the development of these systems.
Policymakers and developers are urged to tackle this bias head‑on to ensure future AI complements rather than replaces human contribution.
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Google Translate may soon evolve into a full-featured language learning tool, introducing AI-powered lessons rivalling apps like Duolingo.
The latest Translate app release recently uncovered a hidden feature called Practice. It enables users to take part in interactive learning scenarios.
Early tests allow learners to choose languages such as Spanish and French, then engage with situational exercises from beginner to advanced levels.
The tool personalises lessons using AI, adapting difficulty and content based on a user’s goals, such as preparing for specific trips.
Users can track progress, receive daily practice reminders, and customise prompts for listening and speaking drills through a dedicated settings panel.
The feature resembles gamified learning apps and may join Google’s premium AI offerings, though pricing and launch plans remain unconfirmed.
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Meta is launching a research lab focused on superintelligence, led by Scale AI founder Alexandr Wang, in an attempt to regain ground in the global AI race.
Mark Zuckerberg is reportedly in talks to invest billions into Scale, reflecting strong confidence in Wang’s data-driven approach and industry influence.
While Meta’s past efforts with its Llama models gained traction, its latest release, Llama 4, failed to meet expectations and drew criticism.
Wang’s appointment arrives during an ongoing talent exodus from Meta, with several senior AI researchers departing for rivals or founding startups.
The new lab is separate from Meta’s existing FAIR division, led by Yann LeCun, who has dismissed the idea of chasing superintelligence. Meta’s partnership with Scale mirrors deals by Microsoft, Amazon, and Google, aiming to secure top AI talent without formal acquisitions.
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A new study from Arizona State University researchers suggests that chain-of-thought reasoning in large language models (LLMs) is closer to pattern matching than accurate logical inference. The findings challenge assumptions about human-like intelligence in these systems.
The researchers used a data distribution lens to examine where chain-of-thought fails, testing models on new tasks, different reasoning lengths, and altered prompt formats. Across all cases, performance degraded sharply outside familiar training structures.
Their framework, DataAlchemy, showed that models replicate training patterns rather than reason abstractly. Failures could be patched quickly through fine-tuning on small new datasets, but this reinforced the pattern-matching theory.
The paper warns developers against relying on chain-of-thought reasoning for high-stakes domains, emphasising the risks of fluent but flawed rationale. It urges practitioners to implement rigorous out-of-distribution testing and treat fine-tuning as a limited patch.
The researchers argue that applications can remain effective for enterprise use by systematically mapping a model’s boundaries and aligning them with predictable tasks. Targeted fine-tuning then becomes a tool for precision rather than broad generalisation.
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Databricks has secured a fresh funding round that pushes its valuation beyond $100bn, cementing its place among the world’s most valuable private tech firms. The Series K deal marks a sharp rise from the company’s $62bn figure in late 2024 and underscores investor confidence in its long-term AI strategy.
The new capital will accelerate Databricks’ global expansion, fuel acquisitions in the AI space, and support product innovation. Upcoming launches include Agent Bricks, a platform for enterprise-grade AI agents, and Lakebase, a new operational database that extends the company’s ecosystem.
Chief executive Ali Ghodsi said the round was oversubscribed, reflecting strong investor demand. He emphasised that businesses can leverage enterprise data to create secure AI apps and agents, noting that this momentum supports Databricks’ growth across 15,000 customers.
The company has also expanded its role in the broader AI ecosystem through partnerships with Microsoft, Google Cloud, Anthropic, SAP, and Palantir. Last year, it opened a European headquarters in London to cement the UK as a key market and strengthen ties with global enterprises.
Databricks has avoided confirming an IPO timeline, though Ghodsi told CNBC that investor appetite surged after fintech Figma’s listing. With Klarna now eyeing a return to New York, Databricks’ soaring valuation highlights how leading AI firms continue to attract capital even as market conditions shift.
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US quantum computing firm Strangeworks has expanded its European presence by acquiring German company Quantagonia. The merger allows organisations to tackle complex planning and optimisation using classical, hybrid, quantum, and quantum-inspired technologies.
Quantagonia, founded in 2021, develops AI-powered, quantum-ready planning tools that combine optimisation, AI, and natural language interfaces. The technology enables experts and non-technical users to solve problems across industries, including life sciences, finance, energy, and logistics.
The acquisition removes barriers to advanced decision-making and opens new go-to-market opportunities in previously underserved sectors.
The combined entity will merge Quantagonia’s solver engine and AI decision-making tools with Strangeworks’ AI and quantum infrastructure. The approach lets enterprises run multiple solvers in parallel and solve problems using natural language without technical expertise.
Strangeworks has strengthened its strategic European foothold, adding to its recent expansion in India and existing operations in the US and APAC. Executives said the merger boosts global growth and broadens access to sophisticated optimisation tools.
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OpenAI chief Sam Altman has warned that the US may be underestimating China’s rapid advancement in AI.
Speaking to CNBC, Altman explained that China’s use of open-source models and its manufacturing capacity may allow it to move faster in some areas of development.
He questioned the effectiveness of export controls, noting that chip restrictions may not be enough to curb long-term innovation. Chinese firms like DeepSeek and MoonshotAI are gaining traction with open-weight models that rival US offerings in cost and capability.
Altman’s comments echo concerns voiced earlier by Nvidia’s CEO, who said firms like Huawei continue to grow despite restrictions.
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TeraWulf has secured a $3.2 billion financial backstop from Google to develop a 160-megawatt data centre at its Lake Mariner site in New York. Google will receive warrants for 32.5 million shares, lifting its stake in TeraWulf to about 14%.
Unlike its existing Bitcoin mining activities, the new deal focuses exclusively on AI and high-performance computing (HPC) workloads. TeraWulf confirmed it will maintain its Bitcoin mining operations but has no plans for expansion in that area.
The pivot reflects a broader trend in the mining industry, where companies increasingly shift capacity toward AI following the April 2024 halving that cut block rewards.
Executives highlighted that while Bitcoin mining offers immediate cash flow and grid flexibility, the long-term growth lies in powering AI and HPC demand. Research from VanEck suggests that if miners redirected just 20% of their power toward AI hosting, the industry could see $13.9 billion in additional annual revenue.
TeraWulf’s leadership said the partnership with Google positions the company as a key player in building next-generation digital infrastructure.
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Google’s upcoming Pixel 10 smartphones are tipped to place AI at the centre of the user experience, with three new features expected to redefine how people use their devices.
While hardware upgrades are anticipated at the Made by Google event, much of the excitement revolves around the AI tools that may debut.
One feature, called Help Me Edit, is designed for Google Photos. Instead of spending time on manual edits, users could describe the change they want, such as altering the colour of a car, and the AI would adjust instantly.
Expanding on the Pixel 9’s generative tools, it promises far greater control and speed.
Another addition, Camera Coach, could offer real-time guidance on photography. Using Google’s Gemini AI, the phone may provide step-by-step advice on framing, lighting, and composition, acting as a digital photography tutor.
Finally, Pixel Sense is rumoured to be a proactive personal assistant that anticipates user needs. Learning patterns from apps such as Gmail and Calendar, it could deliver predictive suggestions and take actions across third-party services, bringing the smartphone closer to a truly adaptive companion.
These features suggest that Google is betting heavily on AI to give the Pixel 10 a competitive edge.
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