Anthropic introduces powerful and transformative voice mode for Claude Code

Anthropic has introduced a voice mode capability for Claude Code, its AI coding assistant for developers. The feature enables users to interact with the system through spoken commands, marking a step toward more conversational and hands-free coding workflows.

Voice interaction allows developers to execute programming tasks using natural language. By activating voice mode, users can verbally request actions, reflecting a broader shift toward intuitive human-AI collaboration in software development.

The rollout is currently limited, with voice mode available to a small percentage of users before wider deployment. Technical details remain unclear, including potential usage limits and whether external voice AI providers contributed to the feature’s development.

The update builds on Anthropic’s earlier integration of voice interaction in its Claude chatbot. This expansion suggests a wider strategy to embed voice interfaces across AI tools and enhance multimodal interaction experiences.

Competition in AI coding assistants continues to intensify, with multiple technology companies developing similar tools. Within this environment, Claude Code has gained strong adoption and a growing market presence among developers.

User growth and revenue indicators highlight the growing momentum of Anthropic’s AI ecosystem. The company also experienced heightened public visibility following its decision to restrict certain military uses of its AI systems, contributing to a surge in app popularity.

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How AI training data is influencing what users believe

A new Yale study, published in PNAS Nexus, has found that AI chatbots can subtly shift users’ social and political opinions, even when asked for factual information and with no intent to persuade.

Researchers tested nearly 1,912 participants, comparing responses to AI-generated summaries of historical events with those to Wikipedia entries, and found measurable differences in opinion.

The culprit, researchers say, is ‘latent bias’, ideological leanings embedded in the data used to train large language models that subtly colour the framing of otherwise accurate responses.

Default summaries generated by GPT-4o consistently nudged readers towards more liberal opinions compared to Wikipedia entries, even without any deliberate prompting.

Senior author Daniel Karell warned that whilst the effects are modest in isolation, they could compound significantly for users who regularly consult chatbots for information.

Unlike Wikipedia, which makes its editorial process transparent, AI development remains largely opaque, giving the companies behind these models an unacknowledged ability to shape public opinion.

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AI models favour Bitcoin over fiat in landmark study

A new study from the Bitcoin Policy Institute, testing 36 AI models across more than 9,000 responses, found that AI agents overwhelmingly prefer Bitcoin over other forms of money.

Bitcoin was the most frequently selected monetary instrument overall, chosen in 48.3% of all responses, whilst almost 91% of responses favoured some form of digital currency over traditional fiat, with no model ranking fiat as its top overall preference.

The preference for Bitcoin was especially pronounced in long-term savings scenarios, where 79.1% of AI responses chose it as the best way to preserve purchasing power over multi-year horizons. For payments and cross-border transfers, however, stablecoins edged ahead, selected in 53.2% of responses compared to Bitcoin’s 36%.

The Bitcoin Policy Institute acknowledged that the study’s methodology had limitations, noting that scenario framing may have influenced results and that the models’ preferences reflect patterns in training data rather than real-world adoption.

Anthropic models showed the strongest Bitcoin preference at 68%, compared to 43% for Google, 39% for xAI, and 26% for OpenAI.

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Crypto exchanges face strict 2027 reserve rules under new Brazil framework

Brazil’s central bank has introduced a regulatory framework requiring licensed crypto exchanges to prove asset sufficiency daily starting on 1 January 2027. The measures align digital asset intermediaries with banking standards on capital management, accounting, and data protection.

Under the rules, exchanges must submit daily attestations confirming that platforms hold adequate fiat and token reserves. Supervisors will review the reports to ensure companies can cover operational, liquidity, and cybersecurity risks while protecting customer balances.

The framework also mandates strict segregation of company and client assets. Exchanges must maintain separate accounts for customer fiat and digital holdings to prevent commingling of funds and improve transparency for regulators.

Platforms operating in Brazil will also be required to follow a specialised accounting manual for digital assets. Standardised rules for classification, valuation, and impairment aim to ensure financial statements clearly reflect exposures across regulated entities.

Authorities will expand oversight of cross-border transfers handled by domestic crypto exchanges. Platforms must report the origins of transactions and the blockchain pathways they follow. The central bank said the framework aims to strengthen resilience and protect customer funds.

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OneTrust’s new CEO outlines AI governance ambitions

OneTrust has entered a new leadership phase in the US after appointing John Heyman as chief executive, replacing founder Kabir Barday. Barday will remain on the board in an advisory role as the US-based compliance technology firm continues to push into AI governance.

John Heyman said organisations across the US and globally are rapidly integrating AI into daily operations. Companies deploying large numbers of AI agents increasingly need tools to manage risk, data use and regulatory compliance.

OneTrust believes demand for governance technology will grow as AI systems multiply inside businesses in the US and worldwide. John Heyman described a future where automated monitoring tools oversee AI agents operating within company systems.

Leadership at OneTrust in the US aims to build systems that track how AI agents collect and share data while maintaining enterprise control. Growing adoption of AI in the US and globally continues to drive demand for responsible governance platforms.

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Santander and Mastercard complete Europe’s first AI agent payment

Spanish banking giant Banco Santander and Mastercard have completed what they describe as Europe’s first live end-to-end payment executed by an AI agent. The pilot combined Santander’s live payments infrastructure with Mastercard Agent Pay to enable autonomous, permission-based transactions.

Mastercard Agent Pay, launched in April 2025, allows AI agents to initiate and complete payments within predefined consumer limits. The transaction was orchestrated with support from PayOS and integrates Microsoft Azure OpenAI Service and Copilot Studio.

Following the pilot, Santander plans to expand testing and explore new partnerships across agentic commerce use cases. The bank, which manages around €1.84 trillion in assets, is positioning AI as a core driver of innovation.

AI initiatives at Santander are led by chief data and AI officer Ricardo Martín Manjón, hired from BBVA. A strategic partnership with OpenAI has also connected up to 30,000 employees to ChatGPT Enterprise in one of the fastest deployments of its kind.

Global competition in agentic payments is intensifying as Citi, US Bank and Westpac trial Mastercard Agent Pay. Westpac recently completed New Zealand’s first authenticated agentic transaction, while DBS, Visa, Axis Bank and RBL Bank are advancing similar intelligent commerce pilots.

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AI tool from MIT speeds up complex engineering optimisation

MIT researchers have developed a new AI approach that helps engineers solve complex design problems faster, from power grid optimisation to vehicle safety.

The method adapts a foundation model trained on tabular data, enabling high-dimensional optimisation without retraining and significantly speeding up results.

The system uses a foundation model with Bayesian optimisation to pinpoint the variables that most impact outcomes. Focusing on key variables, the model finds top solutions 10 to 100 times faster than existing optimisation methods.

Early tests show the approach excels in costly, time-consuming scenarios like car crash testing and power system design. The technique lowers computational demands and suits large-scale, high-frequency engineering challenges across multiple domains.

Researchers aim to expand the method to even higher-dimensional problems, such as naval ship design, while highlighting the broader potential of foundation models as algorithmic engines in scientific and engineering tools.

Experts see it as a practical step toward making advanced optimisation more accessible in real-world applications.

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Developers gain early access to Gemini 3.1 Flash-Lite

Google’s Gemini 3.1 Flash-Lite has launched in preview for developers via AI Studio and for enterprises through Vertex AI. Designed for high-volume workloads, it promises fast, cost-effective performance while maintaining high-quality outputs.

Priced at just $0.25 per million input tokens and $1.50 per million output tokens, 3.1 Flash-Lite offers 2.5X faster response times and 45% higher output speed than the previous 2.5 Flash model.

Benchmarks show strong performance across reasoning and multimodal tasks, including an Elo score of 1432 on Arena.ai, 86.9% on GPQA Diamond, and 76.8% on MMMU Pro, surpassing some older, larger Gemini models.

The model also provides adaptive intelligence features, allowing developers to adjust how much the AI ‘thinks’ for each task. The model handles both high-frequency tasks, such as translation, and complex tasks, such as interface generation and simulations.

Early-access developers and companies report that 3.1 Flash-Lite handles complex workloads with precision comparable to larger models. Its speed, affordability, and reasoning capabilities make it an attractive choice for scalable, real-time AI applications.

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Chrome moves to rapid releases as Google responds to AI disruption

Google is accelerating Chrome’s release cycle rather than maintaining its long-standing four-week cadence.

From September, users on desktop and mobile platforms will receive new stable versions every two weeks, doubling the frequency of feature milestones across speed, stability and usability. Weekly security updates introduced in 2023 remain unchanged.

The faster pace comes as AI-driven browsers seek a foothold in a market long dominated by Chrome.

Products, such as ChatGPT Atlas and Perplexity’s Comet, embed agentic assistants directly into the browsing experience, automating tasks from summarising pages to scheduling meetings.

Chrome has responded with deeper Gemini integration, including the rollout of autonomous features across its interface.

Google maintains that the accelerated schedule reflects the needs of the evolving web platform, arguing that developers require quicker access to updated tools.

Yet the timing aligns with growing competitive pressure from AI-native browsers, prompting speculation that Chrome’s dominance can no longer be taken for granted.

The shift will begin with Chrome version 153 in beta and stable channels on 8 September 2026. Enterprise administrators and Chromebook users will continue to rely on the eight-week Extended Stable branch, which remains unchanged for organisations that need slower, controlled deployments.

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Ripple expands stablecoin platform for global payments

The money-movement solution Ripple Payments has been expanded to integrate both traditional and digital payment rails. The upgrade strengthens its enterprise-grade platform, enabling custody, collections, and liquidity management while supporting global fintech expansion.

The company emphasised that the platform now processes fiat currencies and stablecoins on a single infrastructure.

Operating in more than 60 major markets, Ripple supports corporate on-chain treasury operations through managed custody and virtual account capabilities.

Recent acquisitions of Palisade and Rail have enhanced custody, treasury automation, virtual accounts, and collections, allowing firms to collect, hold, exchange, and pay out both fiat and stablecoins seamlessly.

The expanded platform offers named virtual accounts and wallet issuance, automated collection flows, fund exchange, and settlement functions. Managed custody supports large-scale wallet issuance, fast transaction signing, and transfers to operating accounts.

Companies can collect fiat and stablecoins in integrated accounts with automated FX conversion and settlement. Ripple highlighted its liquidity management expertise, enabling clients to deploy corporate assets optimally.

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