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The unconventional origins of major hotel brands: Travel Weekly

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Christina Jelski

What’s in a name?

I found myself pondering this age-old question during a media dinner hosted by Minor Hotels earlier this month, while listening to Marion Walsh-Hedouin, the group’s global communications director, share details about the Bangkok-based company’s early days.

That included background on the group’s name, which had always struck me as an odd fit for a fast-growing hospitality empire that now spans more than 560 properties across 58 countries. And in an industry where names like Ritz-Carlton and Waldorf Astoria convey luxury and refinement, “Minor” seems understated by comparison.

Minor Hotels’ roots can be traced to 1967, when American-born entrepreneur William Heinecke founded Minor Holdings. That name wasn’t born out of focus groups, a shrewd business plan or a prestigious family surname. Instead, the name came about simply because Heinecke was 17 at the time, so he was literally a minor when he started his business.

Despite choosing branding that essentially advertised his inexperience, Heinecke managed to build a substantial portfolio over nearly six decades, expanding the Minor Hotels fold with brands like Anantara, Avani, NH Hotels, NH Collection and Tivoli. 

The origin story got me thinking about other hotel brands with names of similarly unconventional origins. Take Richard Branson’s Virgin Group, for example. 

When Branson and business partner Nik Powell founded the brand as a mail-order record company in 1970, they landed on the name Virgin “because they were entirely new to business,” according to the company’s website.

Like Heinecke, they had no experience — as well as no shame about making that fact known. But from that humble beginning, Virgin has evolved into a billion-dollar empire spanning airlines, space ventures, hotels and many other industries. 

Naivete, it seems, can be an underrated asset in the hospitality industry. But sometimes, the universe intervenes to save founders from their own worst naming instincts.

Consider Four Seasons Hotels and Resorts, whose founder, Isadore Sharp, originally wanted to call his hotel chain Thunderbird Inn. It would have been a fitting title for the company’s first location, a modest “motor hotel” in downtown Toronto that opened in 1961.

But as fate would have it, that name was already taken. So, a relative suggested the “Four Seasons.”

While Minor and Virgin embraced their inexperience, Four Seasons stumbled into a brand that has come to be synonymous with sophistication, with Sharp declaring that “there was no vision, there was no grand dream” in those early days, according to the company.

The luxury hospitality brand, however, hasn’t forgotten its roots. The name Thunderbird currently graces the employee cafeteria at Four Seasons’ Toronto headquarters, a reminder of what might have been. 

Can you imagine a parallel universe where well-heeled travelers check into the Thunderbird Beverly Hills, or a newlyweds rave about their honeymoon at the Thunderbird George V Paris?

It doesn’t quite have the same ring to it as Four Seasons, does it?

These companies were all able to flourish and become leaders in the industry despite their somewhat humble stories of branding based on youth, inexperience and happy accidents. It may go against conventional corporate wisdom these days, but perhaps the most powerful brand story may be admitting you didn’t really have one to begin with. 



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AI’s last mile just got a supercomputer, courtesy of ASUS and NVIDIA

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They say that the most difficult part of transportation planning is last-mile delivery. A network of warehouses and trucks can bring products within a mile of almost all customers, but logistical challenges and costs add up quickly in the process of delivering those goods to the right doors at the right time.

There’s a similar pattern in the AI space. Massive data center installations have empowered astonishing cloud-based AI services, but many researchers, developers, and data scientists need the power of an AI supercomputer to travel that last mile. They need machines that offer the convenience and space-saving design of a desktop PC but go well above and beyond the capabilities of consumer-grade hardware, especially when it comes to available GPU memory.

Enter a new class of AI desktop supercomputers, powered by ASUS and NVIDIA.

The upcoming ASUS AI supercomputer lineup, spearheaded by the ASUS ExpertCenter Pro ET900N G3 desktop PC and ASUS Ascent GX10 mini-PC, wield the latest NVIDIA Grace Blackwell superchips to deliver astounding performance in AI workflows. For those who need local, private supercomputing resources, but for whom a data center or rack server installation isn’t feasible, these systems provide a transformative opportunity to seize the capabilities of AI.

Scaling up memory to meet the parameter count of large AI models

A key piece of the puzzle for accelerating locally run AI workloads is available GPU memory. If a given model doesn’t fit into local memory, it may run very slowly, or it may not run at all. The 32GB of VRAM provided by the highest-end NVIDIA consumer-grade graphics card on the market, the NVIDIA GeForce RTX 5090, is sufficient for many smaller models. But scaling up your system’s VRAM to handle models with even more parameters isn’t necessarily a straightforward affair.

Multi-GPU systems are a feasible solution for some users, but others have been looking for a solution that’s designed specifically for the needs of AI workflows. By equipping the Ascent GX10 and ExpertCenter Pro ET900N G3 with large single pools of coherent system memory, we’re able to put astonishing quantities of memory at your fingertips. The Ascent GX10 wields four times as much GPU memory as a GeForce RTX 5090, while the ExpertCenter Pro ET900N G3 offers up to 784GB — over twice as much GPU memory as a workstation equipped with four NVIDIA RTX PRO™ 6000 GPUs.

AI supercomputer performance in a desktop PC form factor

Designed from the ground up for AI workflows, the ASUS ExpertCenter Pro ET900N G3 will be one of the first pioneers in a new class of computers, based on the NVIDIA DGX station.

This system is powered by the NVIDIA GB300 Grace Blackwell Ultra Desktop Superchip. Featuring an NVIDIA Blackwell Ultra GPU and an NVIDIA Grace CPU connected via the NVIDIA® NVLink®-C2C interconnect, this superchip provides a slice of data center performance in a desktop workstation. Even more so than today’s high-end desktop systems, the ExpertCenter Pro ET900N G3 ensures that businesses and researchers can develop and run large-scale AI training and inference workloads thanks to up to 784GB of large coherent memory.

It all runs on the NVIDIA AI Software Stack including NVIDIA DGX OS, a customized installation of Ubuntu Linux purpose-built for optimized performance in AI, machine learning, and analytics applications, with the ability to easily scale across multiple NVIDIA DGX Station systems.

The AI supercomputer in the palm of your hand: the ASUS Ascent GX10

The ASUS ExpertCenter Pro ET900N G3 is much easier to deploy than a solution based on rack servers, but there are situations where even a desktop-class form factor is still too large. The ASUS Ascent GX10 democratizes AI by putting petaflop-scale AI computing capabilities in a design that you can hold in the palm of your hand.

The ASUS NUC lineup demonstrates our proven expertise in offering complete PC experiences in ultracompact designs. No mere iterative step forward, the Ascent GX10 takes our experience in the mini-PC market and melds it with the groundbreaking performance of the NVIDIA GB10 Grace Blackwell Superchip. This superchip connects a Grace CPU with 20 Arm cores with a robust Blackwell GPU through NVIDIA® NVLink®-C2C technology. All told, it delivers up to 1,000 AI TOPS of processing power, with 128GB of coherent unified system memory allowing the system to handle 200 billion parameter AI models.

Need the Ascent GX10 to handle even larger models, such as Llama 3.1 with its 405 billion parameters? Integrated NVIDIA® ConnectX®-7 Network Technology allows you to harness the AI performance of two Ascent GX10 systems working together.

Part of a complete AI solution set

ASUS stands out from every other manufacturer on the market with the breadth of AI products that we’re able to offer. The ExpertCenter Pro ET900N G3 and Ascent GX10 slot into a complete lineup that meets the needs of AI enthusiasts at every level. For those looking to build their own AI PC out of consumer-grade components, for those who need AI performance built into their everyday laptop, for enterprises who need a single-rack AI server solution, even for those institutions looking to design, deploy, and operate a data center for AI applications, the ASUS product portfolio is ready.

Yet the ExpertCenter Pro ET900N G3 and Ascent GX10 are far more than mere additions to our AI product stack. The jump from AI PC to AI supercomputer is nothing less than revolutionary, and these systems give you this level of performance in a complete turnkey solution that fits on a desktop.

Aspects of these systems are still in development, but we’ll share more details as soon as we’re able. In the meantime, explore how ASUS can help your organization seize the capabilities of AI.



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Palantir, an artificial intelligence (AI) software company, posted quarterly sales exceeding $1 bill..

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Stock prices surged 112% this year thanks to a 48% increase in sales and 83% increase in net profit U.S. government and private demand. Some on Wall Street said, “Valuation concerns are 277 times higher than PER. 1 trillion dollars in market capitalization in 2 to 3 years.”

Palantir logo

Palantir, an artificial intelligence (AI) software company, posted quarterly sales exceeding $1 billion for the first time. While stock prices have also hit record highs, Wall Street is seeing mixed forecasts on corporate value.

Palantir announced on the 4th (local time) that it recorded sales of 1.04 billion dollars (about 1.3941 trillion won) in the second quarter. This is a 48.0% increase year-on-year, the largest quarterly performance of the company.

Net profit was $405 million, up 82.7% over the same period. The EPS was $0.16, which beat market estimates by $0.14.

The strong performance is attributed to the growth of sales in the U.S. government and the private sector. Sales in the U.S. rose 68% from a year ago to $733 million.

In particular, U.S. government sales rose 53% year-on-year to $426 million thanks to President Donald Trump’s government efficiency policy. U.S. private sector sales also rose 93% to $306 million during the same period.

Palantir closed at $160.66, up 4.14% from the previous trading day, setting a new all-time high. After the earnings announcement was made, it rose more than 5% in after-hours trading.

The company raised its full-year revenue forecast for the year to $4.142 billion to $4.15 billion from $3.89 billion to $3.9 billion.

“Withstanding years of investment and external ridicule, our business growth has accelerated dramatically,” Palantir CEO Alex Karp said in a shareholder letter. “Sceptics have now lost their power and surrendered to us.”

This year, Palantir has soared 112.43% with a market capitalization of $379.1 billion. It ranks 20th among U.S. companies and 13th among global technology companies.

But on Wall Street, there are mixed views on valuations. Palantir’s 12-month forward price-to-earnings ratio (PER) is about 277 times.

Except for Tesla (about 160 times) among the top 20 U.S. companies in market capitalization, it is the only company with triple digits.

Dan Ives Wedbush, an analyst with a strong technology stock, predicted that Palantir’s market capitalization could reach $1 trillion in the next two to three years. “This quarter’s performance is transformative,” Ives said, “If you add to last week’s hyperscalers’ performance, you can see that the next phase of growth in the AI revolution has just begun.”

“Palantir is on par with Nvidia and Microsoft,” he said. Regarding valuation concerns, he said, “If I had only looked at the valuation and made a judgment, I would have missed all transformative tech stocks now,” and stressed, “Palantir falls into that category.”

On the other hand, caution is also being raised. Palantir’s growth potential is great, but some point out that its stock price is too high. Goldman Sachs, UBS, Mizuho Offer ‘Negative’ Opinion To Palantir.

Mizuho said, “Government sector sales will be solid despite geopolitical uncertainties, and we could grow at least 40% per year in the short term,” but added, “We are concerned that Palantir’s valuation is significantly higher among the software industry and could be adjusted in the next few quarters.”

UBS pointed out that “the fundamentals are very impressive, but valuation is the biggest stumbling block.”

Citi, which presented a “neutral and high-risk” opinion to Palantir, said, “The expansion of AI introduction can be a positive catalyst for sales growth,” but added, “There may be limited room for further increases due to valuation concerns and the possibility of slowing performance upward.”



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Uber Eats Debuts AI Features for Restaurants

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Uber Eats has debuted a series of artificial intelligence (AI) features for restaurants.

The new offerings, introduced last week, allow restaurants to use AI to analyze customer reviews, auto-fill menu descriptions and enhance food photos.

“We’re using AI to detect and enhance low-quality food images — improving lighting, resolution, framing, and plating — to help restaurants showcase their dishes more accurately while elevating the customer experience from discovery to checkout,” the company wrote on its blog.

The review summary feature, meanwhile, lets restaurants draw insights from customer reviews. It highlights strengths and areas for improvement. The AI-generated item descriptions can help restaurants “to complete their menus, while also helping customers feel confident in their choices,” the blog post added.

Uber Eats has also introduced new tools for customers, such as the ability to post an image of a dish they had delivered if the item does not yet have a menu image, and a tool that lets merchants chat directly with diners after an order is received.

“Live order chat can help improve order accuracy by enabling real-time communication to confirm replacements for out-of-stock items, clarify special requests, and check in on dietary or allergy preferences,” the blog post said.

Uber Eats’ increased use of AI is happening as this technology is placing a larger role in the dining industry, as covered here last month.

The smart restaurant robot industry is expected to exceed $10 billion by the the decade’s end, helped along by deployment in applications like delivery, order-taking and table service, according to Archive Market Research.

Restaurants are also using AI to cover their administrative needs, with additional PYMNTS Intelligence research showing that close three-quarters of eateries say AI is “very or extremely effective” in accomplishing business goals.

“Robots are taking more active roles in both customer-facing and back-kitchen tasks, as restaurants face a perfect storm of challenges that include rising labor and food costs, persistent workforce shortages, and growing consumer demand for efficient service,” PYMNTS reported last month.

Uber Eats is among the companies taking part in this trend, launching autonomous delivery robots developed by Serve Robotics in the Dallas-Fort Worth metro area earlier this year.



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