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AI in Travel

More on AI in the travel industry: It’s just math. But also, don’t underestimate it.: Travel Weekly


Richard Turen

The advisor reaction to AI brings to mind Alvin Toffler’s 1970 book “Future Shock.”

The point of Toffler’s seminal work was that we were experiencing the downside of rapid technological advances of a type and quantity that was overwhelming to most of us. We are, he claimed, suffering as a society from stress and disorientation specifically caused by too much change in too short a time. Our brains cannot keep up with it. The stress is often related to our jobs: Will computers replace us?

Our society, Toffler argued, is experiencing information overload that will cause instability in our social structures.

What, I wonder, would Toffler say about AI? 

In sharing my thoughts with you about AI and its likely impact on our industry, it might be interesting to begin with robotics. That is one of the sexier branches of the AI revolution and, perhaps, the easiest to understand. Let’s try to put robotics in perspective:

The hotel sector is where we have seen the largest industry adaptation of customer-facing robots. Over the past decade we’ve seen a robot named Botlr at the Aloft Property in Cupertino, Calif., that delivers amenities to guestrooms. Making deliveries such as room service has progressed far more than we might imagine. It is now a worldwide phenomenon.

The world’s first robot-staffed hotel chain, Henn na, opened in Tokyo. At check-in, robotic receptionists, luggage handlers and service bots greeted guests. Humans were rarely involved. At the Hilton in McLean, Va., a robot named Connie was powered by IBM’s AI. She/it provided guests with local dining, sightseeing and specific hotel service information.

You might argue that these are just distractions. Hotel and airport robots can do some amusing and even admirable things. 

But they are also examples of the adaptation from simple beginnings of robots performing human tasks based on a strict command/request code to something more nuanced.

Robotics has faced several hurdles, a primary example was the inability to teach a machine how to tie the shoelaces on a pair of men’s shoes. They just couldn’t do it. They can’t account for varying lengths, degrees of tightness, etc. But in May it was reported that Google DeepMind had taught a robot how to tie shoelaces. An often-referenced hurdle has now been overcome.

And now, consider the speed at which AI is adapting to fill the needs of counseling/advice and quick answers to guest questions.

Last August, the Google DeepMind Lab developed a robot that could beat 55% of intermediate pingpong players it faced. It has made some progress since. The robot was trained by simply watching high-level games on video and playing actual opponents.

There is so much to know about robotics and AI and their impact on our industry. But I think we first have to accept the fact that AI is not anything like magic. You are not creating a human. This is all about math.

At its heart, what we call AI is a machine constructed of algorithms that can quickly, almost instantaneously, process information, analyze patterns and generate answers to queries based on its skill at finding the right answer across the field of millions of data points it can access.

But the lesson is that we should never get too confident. Let’s not get too confident about the limitations of AI.

Some of our most successful travel corporations have learned that AI tools can now do two things rather successfully: They can solve problems with specific solutions and present information in what we might call a “meaningful conversation.” 

Aren’t we all seeking staff who can do that? 



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AI in Travel

India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond – Travel And Tour World

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India’s Travel Revolution: How Map My Tour is Transforming Tourism with AI-Powered Personalization in New Delhi and Beyond  Travel And Tour World



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AI in Travel

OpenAI Rolls Out ChatGPT Agent Combining Deep Research and Operator 

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OpenAI has launched the ChatGPT agent, a new feature that allows ChatGPT to act independently using its own virtual computer. The agent can navigate websites, run code, analyse data, and complete tasks such as planning meetings, building slideshows, and updating spreadsheets. 

The feature is now rolling out to Pro, Plus, and Team users, with access for Enterprise and Education users expected in the coming weeks.

The agent integrates previously separate features like Operator and Deep Research, combining their capabilities into a single system. Operator allowed web interaction through clicks and inputs, while deep research focused on synthesis and summarisation. 

The new system allows fluid transition between reasoning and action in a single conversation.

“You can use it to effortlessly plan and book travel itineraries, design and book entire dinner parties, or find specialists and schedule appointments,” OpenAI said in a statement. “ChatGPT requests permission before taking actions of consequence, and you can easily interrupt, take over the browser, or stop tasks at any point.”

Users can activate agent mode via the tools dropdown in ChatGPT’s composer window. The agent uses a suite of tools, including a visual browser, a text-based browser, terminal access, and API integration. It can also work with connectors like Gmail and GitHub, provided users log in via a secure takeover mode.

All tasks are carried out on a virtual machine that preserves state across tool switches. This allows ChatGPT to browse the web, download files, run commands, and review outputs, all within a single session. Users can interrupt or redirect tasks at any time without losing progress.

ChatGPT agent is currently limited to 400 messages per month for Pro users and 40 for Plus and Team users. Additional usage is available through credit-based options. Support for the European Economic Area and Switzerland is in progress.

The standalone Operator research preview will be phased out in the coming weeks. Users who prefer longer-form, slower responses can still access deep research mode via the dropdown menu.

While slideshow generation is available, OpenAI noted that formatting may be inconsistent, and export issues remain. Improvements to this capability are under development.

The system showed strong performance across benchmarks. On Humanity’s Last Exam, it scored a new state-of-the-art pass@1 rate of 41.6%, increasing to 44.4% when using parallel attempts. On DSBench, which tests data science workflows, it reached 89.9% on analysis tasks and 85.5% on modelling, significantly higher than human baselines.

In investment banking modelling tasks, the agent achieved a 71.3% mean accuracy, outperforming OpenAI’s o3 model and the earlier deep research tool. It also scored 68.9% on BrowseComp and 65.4% on WebArena, both benchmarks measuring real-world web navigation and task completion.

However, OpenAI acknowledged new risks with this capability. “This is the first time users can ask ChatGPT to take actions on the live web,” the company said. “We’ve placed a particular emphasis on safeguarding ChatGPT agent against adversarial manipulation through prompt injection.”

To counter these risks, ChatGPT requires explicit confirmation before high-impact actions like purchases, restricts actions such as bank transfers, and offers settings to delete browsing data and log out of sessions. Sensitive inputs entered during takeover sessions are not collected or stored.

The new system is classified under OpenAI’s “High Biological and Chemical” capability tier, triggering additional safeguards. The company has worked with external biosecurity experts and introduced monitoring tools, dual-use refusal training, and threat modelling to prevent misuse.



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AI in Travel

Lovable Becomes AI Unicorn with $200 Million Series A Led by Accel in Less than 8 Months

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Stockholm-based AI startup Lovable has raised $200 million in a Series A funding round led by Accel, pushing its valuation to $1.8 billion. The announcement comes just eight months after the company’s launch.

Lovable allows users to build websites and apps using natural language prompts, similar to platforms like Cursor. The company claims over 2.3 million active users, with more than 180,000 of them now paying subscribers. 

CEO Anton Osika said the company has reached $75 million in annual recurring revenue within seven months.

“Today, there are 47M developers worldwide. Lovable is going to produce 1B potential builders,” he said in a post on X.

The latest round saw participation from existing backers, including 20VC, byFounders, Creandum, Hummingbird, and Visionaries Club. In February, Creandum led a $15 million pre-Series A investment when Lovable had 30,000 paying customers and $17 million in ARR, having spent only $2 million.

The company currently operates with a team of 45 full-time employees. The Series A round also attracted a long list of angel investors, including Klarna CEO Sebastian Siemiatkowski, Remote CEO Job van der Voort, Slack co-founder Stewart Butterfield, and HubSpot co-founder Dharmesh Shah.

Most of Lovable’s users are non-technical individuals building prototypes that are later developed further with engineering support. According to a press release, more than 10 million projects have been created on the platform to date.

Osika said the company is not targeting existing developers but a new category of users entirely. “99% of the world’s best ideas are trapped in the heads of people who can’t code. They have problems. They know the solutions. They just can’t build them.”

Lovable is also being used by enterprises such as Klarna and HubSpot, and its leadership sees the platform evolving into a tool for building full-scale production applications. 

“Every day, brilliant founders and operators with game-changing ideas hit the same wall: they don’t have a developer to realise their vision quickly and easily,” Osika said in a statement.

Osika also said on X that he has become an angel investor in a software startup built using Lovable. 

In another recent example, Osika noted that a Brazilian edtech company built an app using Lovable that generated $3 million in 48 hours.

Lovable’s growth trajectory suggests increased adoption among both individual users and enterprise customers, positioning it as a significant player in the growing AI-powered software creation market.



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