Development Archives | Page 344 of 541 | Digital Watch Observatory

Opera brings AI assistant to Opera Mini on Android

Opera, the Norway-based browser maker, has announced the rollout of its AI assistant, Aria, to Opera Mini users on Android. The move represents a strategic effort to bring advanced AI capabilities to users with low-end devices and limited data access, rather than confining such tools to high-spec platforms.

Aria allows users to access up-to-date information, generate images, and learn about a range of topics using a blend of models from OpenAI and Google.

Since its 2005 launch, Opera Mini has been known for saving data during browsing, and Opera claims that the inclusion of Aria won’t compromise that advantage nor increase the app’s size.

It makes the AI assistant more accessible for users in regions where data efficiency is critical, instead of making them choose between smart features and performance.

Opera has long partnered with telecom providers in Africa to offer free data to Opera Mini users. However, last year, it had to end its programme in Kenya due to regulatory restrictions around ads on browser bookmark tiles.

Despite such challenges, Opera Mini has surpassed a billion downloads on Android and now serves more than 100 million users globally.

Alongside this update, Opera continues testing new AI functions, including features that let users manage tabs using natural language and tools that assist with task completion.

An effort like this reflects the company’s ambition to embed AI more deeply into everyday browsing instead of limiting innovation to its main browser.

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Siri AI overhaul delayed until 2026

Apple has revealed plans to use real user data, in a privacy-preserving way, to improve its AI models. The company has acknowledged that synthetic data alone is not producing reliable results, particularly in training large language models that power tools like Writing Tools and notification summaries.

To address this, Apple will compare AI-generated content with real emails from users who have opted in to share Device Analytics. The sampled emails remain on the user’s device, with only a signal sent to Apple about which AI-generated message most closely matches real-world usage.

The move reflects broader efforts to boost the performance of Apple Intelligence, a suite of features that includes message recaps and content summaries.

Apple has faced internal criticism over slow progress, particularly with Siri, which is now seen as falling behind competitors like Google Gemini and Samsung’s Galaxy AI. The tech giant recently confirmed that meaningful AI updates for Siri won’t arrive until 2026, despite earlier promises of a rollout later this year.

In a rare leadership shakeup, Apple CEO Tim Cook removed AI chief John Giannandrea from overseeing Siri after delays were labelled ‘ugly and embarrassing’ by senior executives.

The responsibility for Siri’s future has been handed to Mike Rockwell, the creator of Vision Pro, who now reports directly to software chief Craig Federighi. Giannandrea will continue to lead Apple’s other AI initiatives.

For more information on these topics, visit diplomacy.edu.

Elon Musk’s Grok moves closer to ChatGPT

Grok, the AI chatbot from Elon Musk’s xAI, is reportedly gaining a memory feature that allows it to recall previous conversations, bringing it in line with rivals like ChatGPT and Google Gemini.

The feature, spotted by users in the web app, appears as a ‘Personalise with Memories’ toggle in settings and promises to help Grok retain useful context across chats. Users will have the ability to manage what Grok remembers and delete memories when needed, a growing standard in user-controlled AI tools.

The memory update is part of a broader wave of improvements rolling out to Grok, which aims to evolve from a novelty chatbot into a serious digital assistant.

Vision support for voice mode is in development, allowing users to point their camera at objects and receive spoken analysis, while image editing tools are being enhanced to allow stylistic changes to uploaded pictures.

Grok is also preparing to integrate with Google Drive and introduce a new collaborative ‘Workspaces’ feature for larger projects.

These upgrades arrive ahead of the expected release of Grok 3.5, with version 4 planned by year’s end. While the chatbot has carved a niche with its sarcastic tone, xAI appears to be refocusing Grok on practical tasks and creative support.

Whether it can rival the maturity and coherence of more established competitors remains to be seen, but Grok is clearly evolving — and now, it finally remembers who you are.

For more information on these topics, visit diplomacy.edu.

Quantum breakthrough could be just years away

Most quantum professionals believe that quantum utility — the point at which quantum computers outperform classical machines in solving real-world problems — could be reached within the next decade.

According to a new survey by Economist Impact, 83% of global experts expect quantum utility to arrive in ten years or less, with one-third predicting it will happen in as little as one to five years.

Optimism aligns with some industry roadmaps, such as Finnish startup IQM, which is targeting quantum utility as early as next year.

However, there’s still little consensus on the timeline. While Google’s CEO Sundar Pichai recently suggested practically useful quantum computers could be five to ten years away, Nvidia’s Jensen Huang believes it may take at least 15 years — a remark that briefly shook confidence in quantum stocks.

Industry confusion over terms like ‘quantum utility,’ ‘advantage,’ and ‘supremacy’ only adds to the uncertainty, highlighting the need for clearer communication and better public understanding.

Despite the buzz, major challenges remain. Over 80% of professionals cite technical barriers, especially error correction, as a major hurdle.

A further 75% point to a lack of skilled talent in the field. While misconceptions about quantum computing are seen as slowing progress, the real bottlenecks lie in engineering and workforce development.

If these can be overcome, quantum computing could revolutionise sectors from pharmaceuticals and materials science to finance and cybersecurity — with profound implications, both promising and perilous.

For more information on these topics, visit diplomacy.edu.

Samsung brings AI-powered service tool to India

Samsung, already the leading home appliance brand in India by volume, is now enhancing its after-sales service with an AI-powered support tool.

The tech company from South Korea has introduced the Home Appliances Remote Management (HRM) tool, designed to improve service speed, accuracy, and overall customer experience instead of sticking with traditional support methods.

The HRM tool allows customer care teams to remotely diagnose and resolve issues in Samsung smart appliances connected via SmartThings. If a problem can be fixed remotely, staff will ask for the user’s consent before taking control of the device.

If the issue can be solved by the customer, step-by-step instructions are provided instead of sending a technician straight away.

When neither of these options applies, the issue is forwarded directly to service technicians with full diagnostics already completed, cutting down the time spent on-site.

The new system reduces the need for in-home visits, shortens waiting times, and increases the uptime of appliances instead of leaving users waiting unnecessarily.

SmartThings also plays a proactive role by automatically detecting issues and offering solutions before customers even need to call.

Samsung India’s Vice President for Customer Satisfaction, Sunil Cutinha, noted that the tool significantly streamlines service, boosts maintenance efficiency, and helps ensure timely product support for users across the country.

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Nvidia brings AI supercomputer production to the US

Nvidia is shifting its AI supercomputer manufacturing operations to the United States for the first time, instead of relying on a globally dispersed supply chain.

In partnership with industry giants such as TSMC, Foxconn, and Wistron, the company is establishing large-scale facilities to produce its advanced Blackwell chips in Arizona and complete supercomputers in Texas. Production is expected to reach full scale within 12 to 15 months.

Over a million square feet of manufacturing space has been commissioned, with key roles also played by packaging and testing firms Amkor and SPIL.

The move reflects Nvidia’s ambition to create up to half a trillion dollars in AI infrastructure within the next four years, while boosting supply chain resilience and growing its US-based operations instead of expanding solely abroad.

These AI supercomputers are designed to power new, highly specialised data centres known as ‘AI factories,’ capable of handling vast AI workloads.

Nvidia’s investment is expected to support the construction of dozens of such facilities, generating hundreds of thousands of jobs and securing long-term economic value.

To enhance efficiency, Nvidia will apply its own AI, robotics, and simulation tools across these projects, using Omniverse to model factory operations virtually and Isaac GR00T to develop robots that automate production.

According to CEO Jensen Huang, bringing manufacturing home strengthens supply chains and better positions the company to meet the surging global demand for AI computing power.

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Zhipu AI launches free agent to rival DeepSeek

Chinese AI startup Zhipu AI has introduced a free AI agent, AutoGLM Rumination, aimed at assisting users with tasks such as web browsing, travel planning, and drafting research reports.

The product was unveiled by CEO Zhang Peng at an event in Beijing, where he highlighted the agent’s use of the company’s proprietary models—GLM-Z1-Air for reasoning and GLM-4-Air-0414 as the foundation.

According to Zhipu, the new GLM-Z1-Air model outperforms DeepSeek’s R1 in both speed and resource efficiency. The launch reflects growing momentum in China’s AI sector, where companies are increasingly focusing on cost-effective solutions to meet rising demand.

AutoGLM Rumination stands out in a competitive landscape by being freely accessible through Zhipu’s official website and mobile app, unlike rival offerings such as Manus’ subscription-only AI agent. The company positions this move as part of a broader strategy to expand access and adoption.

Founded in 2019 as a spinoff from Tsinghua University, Zhipu has developed the GLM model series and claims its GLM4 has surpassed OpenAI’s GPT-4 on several evaluation benchmarks.

In March, Zhipu secured major government-backed investment, including a 300 million yuan (US$41.5 million) contribution from Chengdu.

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Meta to use EU user data for AI training amid scrutiny

Meta Platforms has announced it will begin using public posts, comments, and user interactions with its AI tools to train its AI models in the EU, instead of limiting training data to existing US-based inputs.

The move follows the recent European rollout of Meta AI, which had been delayed since June 2024 due to data privacy concerns raised by regulators. The company said EU users of Facebook and Instagram would receive notifications outlining how their data may be used, along with a link to opt out.

Meta clarified that while questions posed to its AI and public content from adult users may be used, private messages and data from under-18s would be excluded from training.

Instead of expanding quietly, the company is now making its plans public in an attempt to meet the EU’s transparency expectations.

The shift comes after Meta paused its original launch last year at the request of Ireland’s Data Protection Commission, which expressed concerns about using social media content for AI development. The move also drew criticism from advocacy group NOYB, which has urged regulators to intervene more decisively.

Meta joins a growing list of tech firms under scrutiny in Europe. Ireland’s privacy watchdog is already investigating Elon Musk’s X and Google for similar practices involving personal data use in AI model training.

Instead of treating such probes as isolated incidents, the EU appears to be setting a precedent that could reshape how global companies handle user data in AI development.

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X faces EU probe over AI data use

Elon Musk’s X platform is under formal investigation by the Irish Data Protection Commission over its alleged use of public posts from EU users to train the Grok AI chatbot.

The probe is centred on whether X Internet Unlimited Company, the platform’s newly renamed Irish entity, has adhered to key GDPR principles while sharing publicly accessible data, like posts and interactions, with its affiliate xAI, which develops the chatbot.

Concerns have grown over the lack of explicit user consent, especially as other tech giants such as Meta signal similar data usage plans.

A move like this is part of a wider regulatory push in the EU to hold AI developers accountable instead of allowing unchecked experimentation. Experts note that many AI firms have deployed tools under a ‘build first, ask later’ mindset, an approach at odds with Europe’s strict data laws.

Should regulators conclude that public data still requires user consent, it could force a dramatic shift in how AI models are developed, not just in Europe but around the world.

Enterprises are now treading carefully. The investigation into X is already affecting AI adoption across the continent, with legal and reputational risks weighing heavily on decision-makers.

In one case, a Nordic bank halted its AI rollout midstream after its legal team couldn’t confirm whether European data had been used without proper disclosure. Instead of pushing ahead, the project was rebuilt using fully documented, EU-based training data.

The consequences could stretch far beyond the EU. Ireland’s probe might become a global benchmark for how governments view user consent in the age of data scraping and machine learning.

Instead of enforcement being region-specific, this investigation could inspire similar actions from regulators in places like Singapore and Canada. As AI continues to evolve, companies may have no choice but to adopt more transparent practices or face a rising tide of legal scrutiny.

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TheStage AI makes neural network optimisation easy

In a move set to ease one of the most stubborn hurdles in AI development, Delaware-based startup TheStage AI has secured $4.5 million to launch its Automatic NNs Analyzer (ANNA).

Instead of requiring months of manual fine-tuning, ANNA allows developers to optimise AI models in hours, cutting deployment costs by up to five times. The technology is designed to simplify a process that has remained inaccessible to all but the largest tech firms, often limited by expensive GPU infrastructure.

TheStage AI’s system automatically compresses and refines models using techniques like quantisation and pruning, adapting them to various hardware environments without locking users into proprietary platforms.

Instead of focusing on cloud-based deployment, their models, called ‘Elastic models’, can run anywhere from smartphones to on-premise GPUs. This gives startups and enterprises a cost-effective way to adjust quality and speed with a simple interface, akin to choosing video resolution on streaming platforms.

Backed by notable investors including Mehreen Malik and Atlantic Labs, and already used by companies like Recraft.ai, the startup addresses a growing need as demand shifts from AI training to real-time inference.

Unlike competitors acquired by larger corporations and tied to specific ecosystems, TheStage AI takes a dual-market approach, helping both app developers and AI researchers. Their strategy supports scale without complexity, effectively making AI optimisation available to teams of any size.

Founded by a group of PhD holders with experience at Huawei, the team combines deep academic roots with practical industry application.

By offering a tool that streamlines deployment instead of complicating it, TheStage AI hopes to enable broader use of generative AI technologies in sectors where performance and cost have long been limiting factors.

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