Thailand launches crypto sandbox to boost tourism

Thailand has launched a digital asset sandbox to attract high-spending, tech-savvy tourists by enabling seamless cryptocurrency payments. The initiative lets foreign visitors convert digital assets to Thai baht and spend them using local e-money platforms.

The Securities and Exchange Commission, the Bank of Thailand, and other agencies oversee the regulatory sandbox. It aims to simplify payments from street vendors to luxury retailers, eliminating currency conversion friction and card fees.

Authorities plan to focus on merchant education, compliance, and cybersecurity to support the programme’s success.

The move aligns with Thailand’s broader strategy to become a regional digital finance and blockchain innovation hub. Recent policies include a five-year capital gains tax exemption on crypto sales through local exchanges.

The sandbox could attract fintech firms and blockchain events, signalling Thailand’s ambition to lead in digital asset adoption while maintaining regulatory safeguards.

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EU Commission accuses Temu of failing DSA checks

The European Commission has accused Temu of breaching the Digital Services Act by failing to assess and address the sale of illegal or dangerous products.

The accusation follows months of investigation and a review of a required risk report submitted by Temu, which the Commission found too vague.

A mystery shopping exercise by the EU uncovered unsafe toys and electronics on the platform, raising concerns over consumer safety.

Additional parts of the probe are ongoing, including scrutiny of Temu’s use of addictive designs, algorithmic transparency and product recommendations.

Temu now has a few weeks to respond to the preliminary findings, though no final deadline has been given. Under the DSA, confirmed violations could result in fines of up to 6% of a company’s global turnover.

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AI bands rise as real musicians struggle to compete

AI is quickly transforming the music industry, with AI-generated bands now drawing millions of plays on platforms like Spotify.

While these acts may sound like traditional musicians, they are entirely digital creations. Streaming services rarely label AI music clearly, and the producers behind these tracks often remain anonymous and unreachable. Human artists, meanwhile, are quietly watching their workload dry up.

Music professionals are beginning to express concern. Composer Leo Sidran believes AI is already taking work away from creators like him, noting that many former clients now rely on AI-generated solutions instead of original compositions.

Unlike previous tech innovations, which empowered musicians, AI risks erasing job opportunities entirely, according to Berklee College of Music professor George Howard, who warns it could become a zero-sum game.

AI music is especially popular for passive listening—background tracks for everyday life. In contrast, real musicians still hold value among fans who engage more actively with music.

However, AI is cheap, fast, and royalty-free, making it attractive to publishers and advertisers. From film soundtracks to playlists filled with faceless artists, synthetic sound is rapidly replacing human creativity in many commercial spaces.

Experts urge musicians to double down on what makes them unique instead of mimicking trends that AI can easily replicate. Live performance remains one of the few areas where AI has yet to gain traction. Until synthetic bands take the stage, artists may still find refuge in concerts and personal connection with fans.

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Google brings AI Mode to UK search results

Google has officially introduced its AI Mode to UK users, calling it the most advanced version of its search engine.

Instead of listing web links, the feature provides direct, human-like answers to queries. It allows users to follow up with more detailed questions or multimedia inputs such as voice and images. The update aims to keep pace with the rising trend of longer, more conversational search phrases.

The tool first launched in the US and uses a ‘query fan-out’ method, breaking down complex questions into multiple search threads to create a combined answer from different sources.

While Google claims this will result in more meaningful site visits, marketers and publishers are worried about a growing trend known as ‘zero-click searches’, where users find what they need without clicking external links.

Research already shows a steep drop in engagement. Data from the Pew Research Centre reveals that only 8% of users click a link when AI summaries are present, nearly half the rate of traditional search pages. Experts warn that without adjusting strategies, many online brands risk becoming invisible.

Instead of relying solely on classic SEO tactics, businesses are being urged to adopt Generative Engine Optimisation. Using tools like schema markup, GEO focuses on conversational content, visual media, and context-aware formatting.

With nearly half of UK users engaging with AI search daily, adapting to these shifts may prove essential for maintaining visibility and sales.

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Microsoft adds AI Copilot Mode to Edge browser

Microsoft has launched Copilot Mode in its Edge browser, adding AI features to streamline online activity.

Instead of switching between tabs or manually comparing information, users can ask Copilot to complete tasks, search for content, and make suggestions. The tool is available for PC and Mac users and opens in a side panel, letting people interact with it while still viewing the original page.

Copilot can help with everyday tasks such as writing content, preparing grocery lists, and scheduling appointments. It works across multiple tabs if the user permits, enabling comparisons like hotel or flight prices in a single command.

Voice input is also supported, making it easier for those with limited mobility or less familiarity with AI tools to interact naturally.

Microsoft notes that Copilot Mode remains experimental, but users can still set it as the default. It supports conversational prompts, dynamic interactions like turning recipes vegan, and even measurements or language translations, all without losing browser position.

Users may eventually provide login or history access for more advanced tasks, although full consent and clear notifications will be required.

With growing reliance on digital assistants, Microsoft’s move puts Edge in direct competition with other AI-enabled browsers. As more AI tools become embedded in everyday software, the company expects Copilot to evolve rapidly and suggest next steps to help users pick up where they left off.

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Ray-Ban Meta leads smart glasses market growth

Sales of the Ray-Ban Meta smart glasses have more than tripled in the first half of 2025, cementing Meta’s dominance in the growing AI wearables market.

While Apple remains quiet on a possible launch of its own AI glasses, Meta and its partner EssilorLuxottica continue to expand their lead. The eyewear giant revealed a 200% rise in Ray-Ban Meta sales, with second-quarter revenue up by over 7% compared to last year.

Smart glasses still represent a small part of both companies’ revenue, yet expectations are rising fast. In June, the firms announced a new model – Oakley AI performance glasses – which they hope will match the success of the Ray-Ban line.

Francesco Milleri, EssilorLuxottica’s CEO, stated they expect a ‘very fast ramp-up’ of the Oakley Meta model.

Meta’s Ray-Ban glasses have been on the market for nearly two years, but recent updates have added live translation features and visual recognition that allows the glasses to interpret scenes in real time.

A version with an integrated display is rumoured to launch later in 2025, and Meta is also developing a high-end model called Orion.

Apple, meanwhile, appears more focused on mixed reality, with reports of a second-generation Vision Pro and Samsung’s Project Moohan, which may follow a similar route. But in the space of everyday wearable AI, Meta currently stands alone—at least until the competition decides to enter the arena.

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Chrome update brings AI shopping summaries to US users

Google has updated its Chrome browser to include AI-generated summaries of online stores, aimed at helping shoppers in the US make more informed buying decisions.

Instead of manually searching through reviews, users can now click an icon next to the web address to see a summary of a shop’s performance across key areas like product quality, pricing, returns, and customer service.

The feature is currently available only in English and is limited to desktop users.

The summaries are generated from a range of trusted review platforms, including Trustpilot, Bazaarvoice, Bizrate Insights, and others. Google says that the tool will offer a more efficient and secure online shopping experience.

It also helps the tech giant better compete with Amazon, which has already rolled out AI tools for product comparisons, fit suggestions, and ratings analysis. The move forms part of Google’s wider push to turn Chrome into a more powerful e-commerce assistant.

The company is also integrating AI tools like the Gemini assistant and developing agentic AI systems that can carry out tasks in the browser on a user’s behalf.

At the same time, Chrome faces fresh competition from AI-first browsers such as Perplexity’s Comet, Opera Neon, and a possible entry from OpenAI.

By adding AI-powered features directly into Chrome, Google hopes to future-proof its browser while strengthening its position in online retail.

As rivals begin to build intelligent browsers from the ground up, Google is reimagining how Chrome can serve users beyond simple search and browsing.

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Tech giants back Trump’s AI deregulation plan amid public concern over societal impacts

Donald Trump recently hosted an AI summit in Washington, titled ‘Winning the AI Race,’ geared towards a deregulated atmosphere for AI innovation. Key figures from the tech industry, including Nvidia’s CEO Jensen Huang and Palantir’s CTO Shyam Sankar, attended the event.

Co-hosted by the Hill and Valley Forum and the Silicon Valley All-in Podcast, the summit was a platform for Trump to introduce his ‘AI Action Plan‘, comprised of three executive orders focusing on deregulation. Trump’s objective is to dismantle regulatory restrictions he perceives as obstacles to innovation, aiming to re-establish the US as a leader in AI exportation globally.

The executive orders announced target the elimination of ‘ideological dogmas such as diversity, equity, and inclusion (DEI)’ in AI models developed by federally funded companies. Additionally, one order promotes exporting US-developed AI technologies internationally, while another seeks to lessen environmental restrictions and speed up approvals for energy-intensive data centres.

These measures are seen as reversing the Biden administration’s policies, which stressed the importance of safety and security in AI development. Technology giants Apple, Meta, Amazon, and Alphabet have shown significant support for Trump’s initiatives, contributing to his inauguration fund and engaging with him at his Mar-a-Lago estate. Leaders like OpenAI’s Sam Altman and Nvidia’s Jensen Huang have also pledged substantial investments in US AI infrastructure.

Despite this backing, over 100 groups, including labour, environmental, civil rights, and academic organisations, have voiced their opposition through a ‘People’s AI action plan’. These groups warn of the potential risks of unregulated AI, which they fear could undermine civil liberties, equality, and environmental safeguards.

They argue that public welfare should not be compromised for corporate gains, highlighting the dangers of allowing tech giants to dominate policy-making. That discourse illustrates the divide between industry aspirations and societal consequences.

The tech industry’s influence on AI legislation through lobbying is noteworthy, with a report from Issue One indicating that eight of the largest tech companies spent a collective $36 million on lobbying in 2025 alone. Meta led with $13.8 million, employing 86 lobbyists, while Nvidia and OpenAI saw significant increases in their expenditure compared to previous years. The substantial financial outlay reflects the industry’s vested interest in shaping regulatory frameworks to favour business interests, igniting a debate over the ethical responsibilities of unchecked AI progress.

As tech companies and pro-business entities laud Trump’s deregulation efforts, concerns persist over the societal impacts of such policies.

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AI startup Daydream revolutionises online fashion search

Online shopping for specific items like bridesmaid dresses can be challenging due to overwhelming choices. A new tech startup, Daydream, aims to simplify this. It uses AI to let users search for products by describing them in natural language, making the process easier and more intuitive.

For instance, a user could ask for a ‘revenge dress to wear to a party in Sicily in July,’ or ‘a summer bag to carry to work and cocktails after.’

Daydream, with staff based in New York and San Francisco, represents the latest venture in a growing trend of tech companies utilising AI to streamline and personalise online retail.

Consumer demand for such tools is evident: an Adobe Analytics survey of 5,000 US consumers revealed that 39% had used a generative AI tool for online shopping last year, with 53% planning to do so this year. Daydream faces competition from tech giants already active in this space.

Meta employs AI to facilitate seller listings and to target users with more relevant product advertisements. OpenAI has launched an AI agent capable of shopping across the web for users, and Amazon is trialling a similar feature.

Google has also introduced various AI shopping tools, including automated price tracking, a ‘circle to search’ function for identifying products in photos, and virtual try-on options for clothing.

Despite the formidable competition, Daydream’s CEO, Julie Bornstein, believes her company possesses a deeper understanding of the fashion and retail industries.

Bornstein’s extensive background includes helping build Nordstrom’s website as its vice president of e-commerce in the early 2000s and holding C-suite positions at Sephora and Stitch Fix. In 2018, she co-founded her first AI-powered shopping startup, The Yes, which was sold to Pinterest in 2022.

Bornstein asserts, ‘They don’t have the people, the mindset, the passion to do what needs to be done to make a category like fashion work for AI recommendations.’ She added, ‘Because I’ve been in this space my whole career, I know that having the catalogue with everything and being able to show the right person the right stuff makes shopping easier.’

Daydream has already secured $50 million in its initial funding round, attracting investors such as Google Ventures and model Karlie Kloss, founder of Kode With Klossy. The platform operates as a free, digital personal stylist.

Users can input their desired products using natural language, eliminating the need for complex Boolean search terms, thanks to its AI text recognition technology, or upload an inspiration photo.

Daydream then presents recommendations from over 8,000 brand partners, ranging from budget-friendly Uniqlo to luxury brand Gucci. Users can further refine their search through a chat interface, for example, by requesting more casual or less expensive alternatives.

As users interact more with the platform, it progressively tailors recommendations based on their search history, clicks, and saved items.

When customers are ready to purchase, they are redirected to the respective brand’s website to complete the transaction, with Daydream receiving a 20% commission on the sale.

Unlike many other major e-commerce players, Bornstein is deliberately avoiding ad-based rankings. She aims for products to appear on recommendation pages purely because they are a suitable match for the customer, not due to paid placements.

Bornstein stated, ‘As soon as Amazon started doing paid sponsorships, I’m like, ‘How can I find the real good product?’ She emphasised, ‘We want this to be a thing where we get paid when we show the customer the right thing.’

A recent CNN test of Daydream yielded mixed results. A search for a ‘white, fitted button-up shirt for the office with no pockets’ successfully returned a $145 cotton long-sleeve shirt from Theory that perfectly matched the description.

However, recommendations are not always flawless. A query for a ‘mother of the bride dress for a summer wedding in California’ presented several slinky slip dresses, some in white, alongside more formal styles, appearing more suitable for a bachelorette party.

Bornstein confirmed that the company continuously refined its AI models and gathered user feedback. She noted, ‘We want data on what people are doing so we can focus and learn where we do well and where we don’t.’

Part of this ongoing development involves training the AI to understand nuanced contextual cues, such as the implications of a ‘dress for a trip to Greece in August’ (suggesting hot weather) or an outfit for a ‘black-tie wedding’ (implying formality).

Daydream’s web version launched publicly last month, and it is currently in beta testing, with plans for an app release in the autumn. Bornstein envisions a future where AI extends beyond shopping, assisting with broader fashion needs like pairing new purchases with existing wardrobe items.

She concluded, ‘This was one of my earliest ideas, but I didn’t know the term (generative AI) and I didn’t know a large language model would be the unlock.’

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Delta Air Lines rolls out AI for personalised airfare

Delta Air Lines is shifting the landscape of airfare by leveraging AI to personalise ticket prices. Moving beyond fixed fares, Delta aims to tailor prices closely to each traveller.

Instead of static prices, the system now analyses customer habits, booking history, and even the time of day to predict an individual’s potential willingness to pay. By the end of the current year, Delta aims to set 20% of its ticket prices using AI dynamically.

The goal represents a significant, sevenfold increase from just twelve months prior. Such a high-tech approach could result in more advantageous deals or elevated costs, depending on a passenger’s unique circumstances and shopping behaviour.

It is crucial to understand how this system operates, Delta’s motivations, and its implications for consumer finances. Traditional ticket pricing has long relied on ‘fare buckets,’ where customers are categorised based on their booking method and timing.

Delta’s new AI ticket pricing system fundamentally shifts away from these static rates. It analyses real-time information to calculate precisely what a specific customer will likely spend on a seat for any given flight.

Glen Hauenstein, Delta’s President, describes this as a complete re-engineering of pricing. He characterises AI as a ‘super analyst’ working continuously, 24/7, to identify the optimal price for every traveller, every time.

The airline has collaborated with Fetcherr, which provides the underlying technological infrastructure and supports other global airlines. Airlines do not adopt advanced, high-tech pricing systems to reduce revenue.

Delta reports that initial results from its AI-driven pricing indicate ‘amazingly favourable’ revenues. The airline believes AI will maximise profits by more accurately aligning fares with each passenger’s willingness to pay.

However, this is determined by a vast array of data inputs, ranging from individual booking history to prevailing market trends. Delta’s core strategy is straightforward: to offer a price available for a specific flight, at a particular time, to you, the individual consumer.

Consumers who have previously observed frequent fluctuations in airfare should now anticipate even greater volatility. Delta’s new system could present a different price to one person compared to another for the same seat, with the calculation performed in real-time by the AI.

Passengers might receive special offers or early discounts if the AI identifies a need to fill seats quickly. However, discerning whether one is securing a ‘fair’ deal becomes significantly more challenging. The displayed price is now a function of what the AI believes an individual will pay, rather than a universal rate applicable to all.

The shift has prompted concerns among some privacy advocates. They worry that such personalised pricing could disadvantage customers who lack the resources or time to search extensively for the most favourable deals.

Consequently, those less able to shop around may be charged the highest prices. Delta has been approached for comment, and a spokesperson stated: ‘There is no fare product Delta has ever used, is testing, or plans to use that targets customers with individualised offers based on personal information or otherwise.

Various market forces have driven the dynamic pricing model used in the global industry for decades, with new tech streamlining this process. Delta always complies with regulations around pricing and disclosures.’

Delta’s openness regarding this significant policy change has attracted considerable national attention. Other airlines are already trialling their AI fare systems, and industry experts widely anticipate that the rest of the sector will soon follow suit.

Nevertheless, privacy advocates and several lawmakers are vocalising strong objections. Critics contend that allowing AI to determine pricing behind the scenes is akin to airlines ‘hacking our brains’ to ascertain the maximum price a customer will accept, as described by Consumer Watchdog.

The legal ramifications of this approach are still unfolding. While price variation based on demand or timing is not novel, the use of AI for ultra-personalised pricing raises uncomfortable questions about potential discrimination and fairness, particularly given prior research suggesting that economically disadvantaged customers frequently receive less favourable deals.

Delta’s AI pricing system personalises every airfare, making each search and price specific to the user. Universal ticket prices are fading as AI analyses booking habits and market conditions. This technology can quickly offer special deals to fill seats or raise prices if demand is detected.

Conversely, the price can increase if the system senses a greater willingness to pay. Shopping around is now an absolute necessity. Utilising a VPN can help outsmart the system by masking location and IP address, which prevents airlines from tracking searches and adjusting prices based on geographic region.

Making quick decisions might result in savings, but procrastination could lead to a price increase. Privacy is paramount; the airline gains insights into a user’s habits with every search. A digital footprint directly influences fares. In essence, consumers now possess both increased power and greater responsibility.

Being astute, flexible, and constantly comparing before purchasing is vital. Delta’s transition to AI-driven ticket pricing significantly shifts how consumers purchase flight tickets.

While offering potential for enhanced flexibility and efficiency, it simultaneously raises substantial questions concerning fairness, privacy, and transparency.

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