Perplexity CEO Aravind Srinivas said AI companies that generate the most economic value from the least amount of computing power will be best positioned to succeed as competition intensifies across the sector. Speaking to CNBC’s Elaine Yu, Srinivas argued that maximizing “token value per watt per user” will become a key metric for evaluating AI businesses.

Balancing Accuracy, Latency, Cost And Privacy

Srinivas explained that every AI token, the basic unit of data processed by a model, consumes energy. Companies that can optimize the relationship between energy use and economic output, he said, will have a significant advantage. “Whoever is able to maximize this particular objective by balancing accuracy, latency, cost, privacy and intelligence really will win in the long term,” Srinivas said. His comments reflect a growing focus within the AI industry on efficiency as companies face rising infrastructure and computing costs.

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Advancing Agentic AI With A Platform-Agnostic Approach

Perplexity continues to expand its work in agentic AI, systems designed to complete complex tasks rather than respond to individual prompts. In February, the company introduced Perplexity Computer, an AI agent capable of handling multi-step tasks over extended periods. While Perplexity develops its own models, its products also incorporate technology from companies including Anthropic.

The company recently launched Personal Computer, an orchestration layer that routes queries to the most appropriate processing resource. Srinivas described the shift as a move toward bringing more AI capabilities directly onto personal devices rather than relying exclusively on centralized data centres. According to Srinivas, this approach can reduce energy consumption while improving privacy and security.

Integration Across Leading Platforms And Growing Competition

Personal Computer is currently available on Apple’s Mac devices and is expected to expand to Microsoft’s Windows platform. The system is designed to work across applications, including Word and Outlook. The strategy also differentiates Perplexity from competitors such as OpenAI, Anthropic and Google, which are building increasingly integrated AI ecosystems around their own models and platforms.

Despite rapid growth among rivals, Srinivas said Perplexity’s focus remains on creating a system that works across different models, chips and operating systems. “We believe we’re building the most versatile operating system by making it work across different models, chips, and operating systems,” he said.

Future Outlook: Sustainable And Enduring Advantage

Perplexity’s approach allows the company to incorporate advances from multiple AI providers rather than relying on a single model ecosystem. The strategy has coincided with strong business growth. According to Srinivas, the company’s annualized revenue has tripled since the beginning of the year. As competition intensifies across the AI sector, efficiency, infrastructure costs and cross-platform integration are becoming increasingly important factors for companies seeking to scale their products and services.

Geopolitical Shocks And Market Realities

The global shipping sector is confronting an increasingly stark disconnect between ambitious political targets and economic realities. Amid rising energy demand, geopolitical instability and the scarcity of industrial-scale alternative fuels, the journey toward net zero emissions is becoming more complex and protracted.

Critical Insights From The Capital Link Maritime Leaders Summit

During the 10th Capital Link Maritime Leaders Summit in Athens, held on June 1 as part of Posidonia 2026, leading Greek shipowners argued that shipping is becoming increasingly influenced by geopolitical developments rather than traditional market dynamics. Particular attention was given to the Strait of Hormuz, one of the world’s most important energy corridors, following recent disruptions that have renewed concerns about energy security and global trade flows.

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Energy Security Vs. Environmental Commitments

Shipping Minister Vassilis Kikilias said countries with strong maritime sectors should play a more active role in shaping the future of global shipping policy rather than simply following decisions made elsewhere. The balance between energy security and environmental targets remained a central theme throughout the discussions. Nikolas Tsakos, President and CEO of Tsakos Energy Navigation Ltd, described the period since 2019 as a succession of disruptions, including the pandemic and geopolitical conflicts, that have created ongoing uncertainty for the industry.

Scaling Infrastructure To Meet Ambitious Goals

The debate also pivoted to the challenges of aligning fast-evolving regulatory mandates with the existing energy and infrastructure landscape. The IMO Net-Zero Framework, now postponed until November 2026, has left many stakeholders in a holding pattern. Shipowners remain cautious, as the fuels, bunkering networks and port infrastructures necessary for a sustainable transition are not yet available at the required scale. As Polys Hadjioannou, CEO of Safe Bulkers Inc, pointed out, even investments in alternative fuels such as methanol are constrained by current limitations in available infrastructure.

The Imperative For Operational Efficiency

While long-term infrastructure solutions continue to develop, some industry leaders are focusing on operational measures that can be implemented immediately. Ioanna Procopiou, CEO of Sea Traders SA and Prominence Maritime SA, said improvements in vessel performance and the use of digital tools could significantly reduce emissions while broader structural challenges are addressed. According to Procopiou, operational improvements alone could lower emissions by as much as 40%.

Looking Ahead

Discussions at the summit highlighted the challenge of balancing environmental targets with energy security, commercial realities and evolving geopolitical risks. Industry leaders argued that progress toward decarbonisation will depend not only on regulation, but also on the development of fuels, infrastructure and technologies capable of supporting the sector’s long-term transition.

TechCrunch and VivaTech 2026 have announced a partnership focused on discussions around artificial intelligence, European technology policy, and startup innovation.

The collaboration also includes the VivaTech Innovation of the Year competition, with the winning startup receiving an opportunity to pitch on stage in Paris and secure a place in the Startup Battlefield 200 ahead of TechCrunch Disrupt 2026, scheduled for October 13-15 in San Francisco.

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Europe’s Vision For A New Era Of Artificial Intelligence

Artificial intelligence discussions are often framed around competition between the United States and China. Organizers say VivaTech 2026 will highlight Europe’s approach, which places greater emphasis on industrial competitiveness, regulation, and technological sovereignty.

Differences between the regions have become more pronounced as AI adoption accelerates. While U.S. companies continue investing in larger and more capable models, European policymakers have focused on frameworks related to transparency, data privacy, and infrastructure development. Supporters argue that regulatory oversight can support long-term growth, while critics say stricter rules could slow innovation.

Analyzing Europe’s Unique AI Strategy

Europe’s AI ecosystem has developed alongside established industries, including manufacturing, logistics, healthcare, cybersecurity, and energy. Many European companies are deploying AI within regulated environments where compliance, reliability, and operational requirements play a significant role. As a result, AI adoption in Europe has often focused on industrial and enterprise applications rather than consumer-facing platforms.

Established industrial sectors also provide opportunities for AI deployment across large-scale systems and infrastructure. Organizations operating in these industries often require solutions that meet regulatory standards while supporting operational efficiency and long-term implementation.

This combination of industrial expertise, regulatory oversight, and enterprise adoption has helped shape a distinct approach to AI development across Europe.

Engage In The Future Of AI At VivaTech 2026

VivaTech 2026 will take place in Paris from June 17-20 and will feature founders, investors, corporate executives, and policymakers discussing AI development and regulation. Applications for Startup Battlefield remain open until June 8, while registration for the conference is currently available.

Anthropic is expanding access to Project Glasswing, its AI-based vulnerability detection initiative, to approximately 150 additional organizations across more than 15 countries.

Expanding Global Cybersecurity Efforts

The expansion follows an initial deployment involving 50 organizations, including U.S. government agencies. Project Glasswing is designed to help identify software vulnerabilities in sectors where cybersecurity risks can have significant operational consequences. Participating organizations operate across industries, including energy, water, healthcare, communications, and hardware.

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Leveraging Advanced AI For Critical Infrastructure

Project Glasswing is powered by Claude Mythos, Anthropic’s latest AI model for cybersecurity applications. According to the company, the model has identified thousands of previously unknown software vulnerabilities during testing and early deployments. Anthropic says the initiative focuses on protecting critical infrastructure and software systems used by public and private organizations.

Market Developments And IPO Prospects

The expansion arrives on the heels of Anthropic filing confidentially for an initial public offering following a monumental $65 billion funding round that propelled the company’s valuation to nearly $1 trillion. This dual motion, broadening the scope of Project Glasswing while preparing for an IPO, positions Anthropic at the forefront of cybersecurity innovation, even as market competitors accelerate their own initiatives.

Rising Competition And Industry Implications

The broader industry landscape is witnessing heightened activity, with rivals such as OpenAI rolling out their own cybersecurity-focused models like GPT-5.5-Cyber. Through Project Glasswing, Anthropic is expanding partnerships with organizations responsible for maintaining critical software and infrastructure systems.

The initiative reflects growing industry interest in applying AI models to cybersecurity challenges across both public and private sectors.

Apple shipped 1.1 million MacBook Neo units in the quarter ended March, according to IDC data, despite the device being available for only the final three weeks of the period.

Early Sales Momentum

MacBook Neo launched in early March and began shipping at scale in April. IDC data indicate that the device reached 1.1 million units shipped during its first quarter on the market. Early sales figures suggest strong initial demand for Apple’s newest notebook model.

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Broadening The Mac Ecosystem

Apple introduced the MacBook Neo with a starting price of $599, making it one of the company’s most affordable notebook offerings. Features include an aluminium chassis and a 13-inch Liquid Retina display. To reach a lower price point, Apple opted for an A18 Pro chip and 8GB of base memory. The company says the product is designed to attract first-time Mac buyers and expand its customer base.

Global Demand And Market Impact

According to IDC Associate Vice President Navkendar Singh, demand for the MacBook Neo has been particularly strong in the United States and India, where supply constraints have affected availability. The U.S. market accounted for 44% of shipments during the March quarter. In India, Apple shipped nearly 18,000 units, according to IDC data. Launch of the MacBook Neo comes as notebook manufacturers face changing consumer demand and higher prices across parts of the PC market.

Competitive Pressure And Strategic Shifts

Pricing of the Neo has added pressure in the entry-level notebook segment. Dell recently introduced a new XPS 13 model with a starting price of $699. During a recent earnings call, Apple CEO Tim Cook said the company recorded a record number of new Mac customers following the launch. IDC Associate Vice President Navkendar Singh and Counterpoint Research Analyst David Naranjo estimate that the MacBook Neo could help Apple increase its share of the $400-$699 notebook segment from about 2% to 15%.

A Pivotal Moment For Apple

With the MacBook Neo, Apple is targeting a broader customer base through a lower-priced notebook that retains features associated with the Mac lineup.

U.S. President Donald Trump on Tuesday signed an executive order requiring artificial intelligence companies to provide federal authorities with early access to certain advanced AI models before their public release.

Benchmarking Advancements In AI Technology

According to the executive order published by the White House, the administration will establish a voluntary benchmarking process to evaluate a model’s advanced cyber capabilities and determine whether it qualifies as a “covered frontier model.” Under the framework, federal authorities may receive access to eligible models up to 30 days before their broader release to assess their capabilities.

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Trusted Partnerships And Pre-Market Access

The order also calls for the designation of “trusted partners” that will receive access to evaluated models during the review process. At the same time, the directive states that it does not introduce mandatory government licensing, preclearance, or permitting requirements for the development or distribution of AI models.

Market Implications And Emerging Competition

The order comes as major AI companies pursue expansion and public market opportunities. AI startup Anthropic recently confidentially filed for an initial public offering with the U.S. Securities and Exchange Commission. OpenAI is also preparing for a potential public offering later this year. Meanwhile, SpaceX’s AI venture xAI has emerged as another major competitor in the sector, with reports suggesting the company could reach a valuation exceeding $1 trillion.

Trump signed the order privately after a planned ceremony with technology executives was postponed.

Agentic AI can book your flight and reorder your coffee. But fashion shopping runs on browsing, inspiration, and bodies that don’t come in standard sizes. That combination is proving far harder for autonomous agents to crack.

The Promise Meets Its Hardest Category

Late last year, we covered how agentic commerce is reshaping global transactions. The illustration was crisp: tell an AI to find the cheapest red-eye flight from Singapore to Tokyo under $500, and it searches, compares, books, and pays. Done. The entire purchase happens inside a single conversation.

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Flights are standardized products. A seat is a seat. A price is a price. The agent’s job is clear, the criteria measurable, the outcome binary. But what happens when the AI agent needs to buy you a dress for a wedding in Mykonos?

Fashion is where agentic commerce runs into a wall. And the reasons go deeper than most industry commentary acknowledges.

Fashion Is A Browsing Category, Not A Searching Category

When someone shops for electronics, they typically know the product. “Samsung Galaxy S26, 256GB, best price.” The intent is specific, the comparison is numerical, and an AI agent can handle it without breaking a sweat.

Fashion works differently. Most consumers don’t know what they want when they start shopping for clothes. They browse. They scroll. They stumble onto a jacket they didn’t know existed and suddenly rethink the entire outfit. This isn’t a flaw in how people shop. It’s the point.

Academic research confirms what anyone who has ever spent 40 minutes on a fashion app already knows: online clothing shopping is dominated by what researchers call “diversive exploration” — browsing for enjoyment and discovery, distinct from goal-directed search. The behavior is hedonic, not utilitarian. People don’t just want the product. They want the process.

The numbers back this up. According to McKinsey’s State of Fashion 2026 report, shopping-related searches on generative AI platforms grew 4,700% between 2024 and 2025, with AI supporting “inspiration and product comparison” — especially in fashion, where choice abounds. Consumers are using AI to discover, not to delegate. A separate Bain & Company study from April 2026 found that 44% of US online buyers now start their journey in an LLM or split between AI and traditional search. But in fashion specifically, 46% use AI for “discovering new products and getting inspired,” while usage drops sharply as activities move closer to checkout and payment.

An AI agent can book a flight autonomously because the consumer’s intent is clear. In fashion, the intent is often vague, “something for summer”, or absent: “I’m just looking.” You can’t delegate browsing to an agent. Browsing is the experience.

Even When You Know Exactly What You Want

Suppose a consumer does have a specific goal. They want a pair of Camper Pelotas in size 42. Straightforward enough for an AI agent, right?

Not quite.

A size 42 in Camper is not a size 42 in Nike, which is not a size 42 in Adidas. There is no universal sizing standard in fashion. Every brand calibrates differently, and some brands are inconsistent across their own product lines. An AI agent that confidently orders the “right” size has roughly a coin-flip chance of getting it wrong in certain categories. European fashion return rates hover between 25% and 40%, with size and fit issues accounting for more than half of all returns, according to Statista and European e-commerce industry data. In Germany, the practice of “bracketing”, ordering three sizes of the same item to try at home, pushes online fashion return rates above 44%.

Then there’s the visual dimension. A flat product photo in an AI chat window doesn’t replicate what happens when a consumer sees a shoe alongside ten alternatives on a comparison grid. Context matters. Styling matters. The way a sandal looks next to a linen dress matters. Pinterest’s visual search technology has driven a 387% revenue increase for participating merchants, and visual search users convert at rates 73% higher than text-based searchers, according to industry data tracked by eCommerce Times. Platforms like Spangle are proving that AI-powered visual personalization lifts revenue per visit by up to 50%.

There’s a final paradox. Price comparison absolutely works in fashion — the same branded shoe can differ by 30% across retailers. But consumers also compare across products. “Do I want the Camper or the Clarks?” That requires visual side-by-side browsing, and current AI agents can’t replicate it well. They’re designed to return a result, not to facilitate a process.

The Infrastructure Gap

For AI agents to operate autonomously in fashion, they need structured, real-time data: normalized product attributes, cross-retailer pricing, size mapping, availability signals, and brand reliability scores. This infrastructure barely exists.

Consider how hard this is even in simpler categories. Cyprus’s government-backed e-Kalathi grocery comparison platform launched with the goal of transparent supermarket price tracking. Within months, the Cyprus Consumer Association flagged accuracy problems — pricing inconsistencies, incomplete product coverage, misleading comparisons. And that’s groceries, where a bottle of milk is a bottle of milk.

Fashion is orders of magnitude harder. Product feeds arrive in dozens of incompatible formats. A “navy blue slim-fit cotton shirt” from one retailer might be listed as a “dark blue fitted cotton top” from another — same product, entirely different data. Normalizing that across thousands of products from dozens of retailers requires purpose-built AI pipelines. Stylino, a Cyprus-based fashion price comparison engine, processes feeds from 65+ retailers and uses AI to match and deduplicate over 385,000 products into a single searchable catalogue. Building that kind of data layer took months of custom engineering — and it’s the sort of plumbing that agentic commerce will eventually need to function in fashion.

On the visual side, companies like Aiuta are using AI to generate styled product imagery and virtual try-on experiences, addressing the content bottleneck that currently limits how well any automated system can present fashion to consumers. These building blocks, structured data, visual content, size intelligence, will eventually form the infrastructure layer that agents plug into. But we’re early.

The Likely Sequence

Fashion won’t leap from browsing to fully autonomous purchasing. The transition will happen in stages, and each stage suits a different kind of AI intervention.

First, consumers browse and discover. This is visual, emotional, and social. It won’t be delegated to an agent anytime soon, because delegation defeats the purpose. Second, AI helps compare prices and availability across retailers — this is already happening and provides genuine value. Third, AI monitors price drops, tracks wish lists, and sends alerts when a saved item goes on sale. Useful, but still decision-support rather than decision-making. Fourth, AI executes purchases on known, pre-approved items: reorders, basics, and items the consumer has bought before in the right size.

Only that last step is truly “agentic.” And it applies primarily to commodity fashion: underwear, socks, a replacement white t-shirt, not to the discovery-driven shopping that accounts for most fashion spending. McKinsey’s European agentic commerce research confirms this sequencing: AI is being adopted first as a “decision-support layer, compressing research, comparison, and synthesis,” with usage declining as activities move closer to execution.

Here’s the uncomfortable truth for the agentic commerce narrative: the fitting room is where most fashion decisions actually happen. It’s physical. It’s emotional. Sometimes it involves a friend outside the curtain saying, “absolutely not.” AI agents are exceptional at finding you the cheapest red-eye to Tokyo. They are not standing in that fitting room mirror with you. The agent who wins in fashion won’t be the one who buys for you. It’ll be the one that helps you see better: more options, better prices, smarter comparisons, while you keep making the call.

Overview Of Q1 2026 Trade Dynamics

The European Union recorded a trade surplus of €12.7 billion with non-EU countries in the first quarter of 2026, according to Eurostat. Although the balance remained positive, the surplus narrowed from €23.6 billion in the fourth quarter of 2025, reflecting changes across several key trade categories.

Export Dynamics And Energy Sector Pressures

A weaker surplus in machinery and vehicles weighed on overall trade performance during the quarter. The surplus in that category declined from €39.8 billion in the final quarter of 2025 to €27.8 billion in the first quarter of 2026. At the same time, the EU’s trade deficit in fuel and energy products widened from €64.0 billion to €72.2 billion.

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Structural Shifts In Trade Categories

The shift in the EU’s trade profile is also evident in other manufacturing goods, where the deficit narrowed from -€10.9 billion to -€5.0 billion. Additionally, the trade surplus for miscellaneous unclassified goods increased, rising from €7.2 billion to €11.5 billion. Total exports registered a slight 0.1% decline, marking a fourth consecutive quarter of reduction, a trend influenced by escalating global tariff tensions and disrupted supply routes.

Looking Ahead: Resilience Amid Global Challenges

Conversely, the increase in total imports by 1.7% broke a three-quarter-long trend of decline, showcasing the EU’s growing appeal as a market. This resilient performance follows a challenging period of consecutive trade deficits from late 2021 to mid-2023, when steep energy costs adversely affected manufacturing outputs across the single market.

As the EU navigates evolving global economic pressures, the mixed signals from export and import sectors highlight both challenges and opportunities. With a legacy of adaptability and structural reforms, the bloc continues to fortify its economic stance for the future.

Overview Of Market Dynamics

The Cyprus Consumers Association has unveiled notable fluctuations in consumer goods prices during the latter half of May. Their comprehensive analysis revealed that price adjustments were recorded across 165 products spanning 34 distinct categories, indicating a market characterized by varied pricing dynamics.

Significant Price Increases Across Key Categories

Among the observed trends, significant price increases of up to 9.8% were noted in categories such as sauces and dressings, eggs, soaps, cheeses, yoghurts, tissues, and personal hygiene products. These changes underscore continuing pressure on everyday household goods. For instance, a package of mayonnaise experienced a 9.8% increase, equating to an additional 34 cents overnight, while a pack of 12 eggs saw a 7.4% rise, adding 29 cents to its previous cost.

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Notable Observations And Inconsistencies

While the most substantial absolute increase was observed in infant milk with a rise of 45 cents, this change corresponded to a smaller increase of 2.5% in relative terms. In contrast to the price hikes, the study also recorded 133 instances of price reductions, with an average decrease of 9.4%. This duality of pricing movements raises important questions regarding the underlying market forces that drive both upward and downward adjustments.

Insights And The Path Forward

According to the consumers association, these fluctuations are derived from comparisons between the average product price on a given day and that of the preceding day. The presence of rapid price reversals in some cases suggests that the factors influencing these movements require further scrutiny. As one representative noted, “The big question is why some products are increasing in price while others are decreasing, even though overall market conditions remain largely consistent.”

Commitment To Transparency

The findings, compiled through data from the Ministry of Energy’s e-kalathi platform and the private smart kalathi application, highlight the importance of continuous monitoring. The Cyprus Consumers Association remains committed to tracking these trends and will persist in publishing its findings transparently to better inform both consumers and market stakeholders.