Brazil has postponed discussions on its upcoming cryptocurrency tax framework until after the October 2026 presidential elections, signalling a cautious political approach to digital asset regulation.
Finance officials aim to avoid introducing contentious fiscal measures during an election cycle, despite earlier plans to launch a public consultation later this year.
Recent tax reforms have already marked a significant shift in Brazil’s crypto policy. A flat 17.5% tax on capital gains was introduced in June 2025, replacing earlier exemptions for smaller transactions.
Previous rules allowed tax-free monthly sales up to 35,000 Brazilian real, while higher volumes were subject to progressive rates. Banco Central do Brasil classified stablecoin transfers as foreign exchange, making them subject to standard currency tax rules.
Authorities are considering broader crypto taxes, including on assets used for international payments. Alignment with the Crypto-Asset Reporting Framework also remains on the agenda, indicating a move towards tighter oversight and global regulatory coordination.
Strong adoption highlights the policy’s importance, with Brazil leading Latin America and ranking among the world’s top crypto markets. Regional data shows a surge in adoption, strengthening Brazil’s role in the global digital asset market.
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Members of the European Parliament are calling for more rapid progress in implementing the bloc’s digital competition framework, with particular focus on the Digital Markets Act.
In a recent resolution, lawmakers urged the European Commission to ensure timely and effective enforcement of the rules designed to regulate large online platforms. The legislation aims to address concerns around market dominance and promote fair competition across the digital economy.
The discussions reflect ongoing concerns that delays in enforcement could undermine the framework’s effectiveness, particularly as major technology companies continue to expand their influence. Platforms such as Google, Apple and Meta are among those expected to comply with the new obligations.
At the same time, policymakers are balancing regulatory oversight with the need to maintain innovation and competitiveness. The debate forms part of a broader effort in the EU to strengthen digital governance and reinforce the region’s position in global technology markets.
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A University of Essex robotics project designed to automate crop harvesting has won the Best Research Project (Industry Collaboration) award at the 2026 UKRI AI & Robotics Research Awards.
The Sustainable smArt Robotic Agriculture (SARA) project was developed in collaboration with industry partners Wilkin and Sons, JEPCO, and GyroPlant, and addresses three interconnected challenges: food security, labour shortages, and sustainability.
Central to the project is the development of low-cost AgriRobotics systems capable of adapting to different crops, tasks, and growing environments, automating repetitive, labour-intensive farm work whilst reducing wastage, carbon footprint, and dependence on increasingly scarce agricultural labour.
The team delivered a live strawberry-harvesting demonstration at the Innovate UK Robotics Industry Showcase in March, an event aligned with UKRI’s announcement of a £52 million competition for Robotics Adoption Hubs.
Building on the project’s success, lead researchers Professor Klaus McDonald-Maier and Dr Vishwanathan Mohan have launched a spinout company, Versatile RobotX, to accelerate the commercialisation of the technology and extend its global impact.
The SARA project previously won the Best Demonstration category at the same awards in 2025.
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A growing number of individuals worldwide are participating in a new digital economy built around supplying data for AI systems.
Through platforms such as Kled AI and Silencio, users upload videos, audio recordings and personal interactions in exchange for payment, contributing to the development of increasingly sophisticated AI models.
Such a trend reflects a broader shift in the AI industry, where demand for high-quality human-generated data is rising as traditional web-based sources become more limited.
Researchers suggest that human data remains essential for improving system performance and modelling behaviour beyond existing datasets. As a result, data marketplaces have emerged as an alternative supply mechanism.
Economic considerations often shape participation. In regions facing limited employment opportunities or currency instability, earning income in global currencies can provide a meaningful financial incentive.
At the same time, similar practices are expanding in higher-income countries, where individuals seek supplementary income streams amid rising living costs.
However, the model introduces complex trade-offs.
Contributors may grant extensive usage rights over their data, sometimes on a long-term or irreversible basis. Experts note that such arrangements can reduce control over how personal information is reused, including in contexts not initially anticipated.
Concerns also extend to issues such as data security, transparency and the potential for misuse in areas including synthetic media and identity replication.
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OpenAI will begin rolling out ChatGPT ads to Free and Go users in the United States in the coming weeks, marking a significant shift in how the company monetises its flagship AI product.
The ads will be shown to logged-in adult users on lower-tier plans, while paid subscriptions, including Plus, Pro, Business, Enterprise, and Education, will remain ad-free. The rollout in the US positions ChatGPT ads as a tiered feature, separating premium experiences from ad-supported access.
To support the initiative, OpenAI has integrated advertising technology firm Criteo into its pilot programme, enabling ad buying and more targeted placements. Advertisers are reportedly being offered entry commitments ranging from $50,000 to $100,000, reflecting early efforts to build a structured advertising marketplace.
The company has also launched a dedicated advertiser page that presents ChatGPT as a platform for reaching users during active research and decision-making. ChatGPT ads are being framed as part of conversational discovery, with OpenAI advising brands to provide multiple variations of creative content to improve performance.
The rollout comes as OpenAI seeks to diversify revenue amid rising compute costs and intensifying competition. Alongside subscriptions and API services, ChatGPT ads are expected to play an increasingly important role in supporting the platform’s long-term business model.
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Microsoft is scaling back the presence of Copilot across Windows 11, signalling a shift toward a more selective and user-focused approach to AI integration.
Microsoft said it will reduce Copilot features in several built-in applications, including Photos, Widgets, Notepad and the Snipping Tool. The company described the move as part of a broader effort to integrate AI only where it delivers clear value to users.
The decision follows growing concerns about ‘AI bloat’ and user trust, with recent research indicating rising scepticism around AI. Microsoft is responding by prioritising more practical and reliable use cases rather than widespread deployment.
The change also aligns with earlier adjustments to Copilot plans, including shelving some system-level integrations and delaying features such as Windows Recall due to privacy and security concerns. Even after launch, vulnerabilities in Recall have continued to surface, reinforcing the need for caution.
Beyond AI, Microsoft is introducing several usability improvements to Windows 11. These include allowing users to reposition the taskbar, enhancing File Explorer performance, refining Widgets, and giving users greater control over system updates.
The update signals a broader recalibration, as Microsoft balances innovation with user expectations, aiming to deliver AI features that are both useful and trusted within everyday computing environments.
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A new wave of AI development is increasingly relying on real-world human behaviour, with DoorDash moving to tap its gig workforce to generate training data for robotics systems.
DoorDash has launched a standalone app called Tasks, allowing couriers to earn money by recording themselves performing everyday activities such as folding clothes, washing dishes or making a bed. The collected data is used to train AI and robotics models to understand physical environments and human interactions better.
The move reflects a broader shift in AI training, where companies are seeking physical, real-world data rather than relying solely on text and images. Such data is essential for building systems capable of performing tasks in dynamic environments, including humanoid robots and autonomous machines.
Other companies are pursuing similar strategies. Uber and Instawork have tested gig-based data-collection models, while robotics startups are using wearable devices, such as gloves and head-mounted cameras, to capture detailed motion data for training.
The Tasks app is currently being rolled out as a pilot, with DoorDash planning to expand the types of available assignments over time. Some tasks may also be integrated into the main Dasher app, including activities that support navigation or assist autonomous delivery systems.
As competition intensifies, access to large-scale physical data is becoming a critical advantage. DoorDash’s approach highlights how gig-economy platforms are increasingly integrated into the development of next-generation AI systems.
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AI adoption is accelerating across UK businesses, with 78% now using the technology in some capacity, rising to 85% among mid-sized organisations. A further 14% are exploring or planning implementation by 2026, reflecting the continued momentum behind AI adoption.
Despite widespread use, tangible results remain limited. Just 31% of UK businesses report a positive return on investment, while 18% say their AI initiatives have failed to deliver expected benefits. Another 16% indicate it is still too early to assess outcomes, highlighting the long lead times often associated with AI deployments.
A major issue lies in defining success. Only 41% of organisations using AI say they have a clear understanding of what success looks like, suggesting that AI adoption is often not matched by clear strategic planning, even among mid-sized firms, the most active adopters; fewer than half can articulate measurable goals.
The findings suggest that rapid uptake has outpaced organisational readiness. Many businesses are deploying AI tools without defining how they fit into workflows, what decisions they are meant to support, or whether the goal is efficiency, cost reduction, or growth.
For AI adoption to translate into real business value, companies will need stronger governance, clearer objectives, and measurable success criteria. Without that foundation, AI risks remaining an expensive experiment rather than a driver of long-term transformation.
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A shift toward consolidation is underway, with OpenAI planning to merge its ChatGPT app, Codex platform and browser into a single desktop ‘superapp’ designed to simplify the user experience.
OpenAI said the move aims to streamline its product ecosystem after a period of rapid expansion that resulted in multiple standalone tools. The company is now prioritising a more unified approach, particularly as it intensifies competition with rivals such as Anthropic in enterprise and developer markets.
The planned superapp will focus heavily on ‘agentic’ AI capabilities, enabling systems to operate autonomously across tasks such as writing software, analysing data and managing workflows. The goal is to create a central platform where AI can act as a collaborative assistant across the full productivity stack.
Internal leadership changes are also supporting the transition. Chief of Applications Fidji Simo will oversee the initiative, working alongside President Greg Brockman, as the company restructures teams to align around a single core product. Executives have emphasised the need to reduce fragmentation and improve product quality.
The shift comes as OpenAI faces increasing pressure from competitors that have gained traction with enterprise customers. Anthropic, in particular, has seen success with its developer-focused offerings, prompting OpenAI to refocus on business users and revenue growth.
Over the coming months, the company plans to expand Codex with broader productivity features before integrating ChatGPT and its browser into the unified platform. While the mobile ChatGPT app will remain separate, the broader strategy signals a move toward a more cohesive and scalable AI ecosystem.
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An ambitious target to generate $100 billion in annual cloud and AI revenue within five years has been set, as Alibaba seeks to counter slowing growth in its once-dominant e-commerce business.
The push follows a sharp deterioration in financial performance, with quarterly earnings plunging and revenue growth missing expectations. The results underscore growing urgency within the company to extract meaningful returns from its AI investments, which have so far required heavy capital outlays.
Central to the strategy is a shift toward monetisation, with the rollout of agentic AI services such as Wukong and price increases of up to 34% across cloud and storage products. Alibaba is positioning its AI and cloud division as its primary growth engine, aiming to replicate the momentum seen in recent quarters, when AI-related revenues expanded by triple digits.
However, competitive pressures are intensifying. Domestic rivals including Tencent are leveraging vast ecosystems such as WeChat to gain an advantage in agentic AI, while a new wave of players like DeepSeek, MiniMax and Zhipu are offering low-cost, open-source models that compress margins across the industry.
At the same time, Alibaba faces structural challenges beyond AI. Core businesses such as e-commerce and food delivery remain under pressure from aggressive competition, while rising operational costs – subsidies and promotions to attract users – continue to weigh on profitability.
Leadership uncertainty and ongoing restructuring add further complexity. With major investment commitments exceeding $50 billion and increasing competition from both domestic and global players, Alibaba’s ability to execute on its AI strategy will be critical in determining whether it can sustain long-term growth and regain market confidence.
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