Abstract-- We have reached a practical and realistic phase in human-support dialogue agents by developing a large language model (LLM). However, when requiring expert knowledge or anticipating the utterance content using the massive size of the dialogue database, we still need help with the utterance content's effectiveness and the efficiency of its output speed, even if using LLM. Therefore, we propose a framework that uses LLM asynchronously in the part of the system that returns an appropriate response and in the part that understands the user's intention and searches the database. In particular, noting that it takes time for the robot to speak, threading related to database searches is performed while the robot is speaking. This is an for actual automatic ticket sales or searching a large database asynchronous operation that separates (A) the system that and modifying the conversation based on the results.

VisitDenmark, the official tourism organization of Denmark, has recently launched an AI production campaign. The campaign, which uses AI to produce a series of videos and images, aims to attract more visitors to Denmark. And to promote the country's cultural heritage. In this it can create high-quality images and videos based on data and algorithms. It also produces unique visuals that highlight the country's charm and beauty.

Geo-tagged photo based tourist attraction recommendation can discover users' travel preferences from their taken photos, so as to recommend suitable tourist attractions to them. However, existing visual content based methods cannot fully exploit the user and tourist attraction information of photos to extract visual features, and do not differentiate the significances of different photos. In this paper, we propose multi-level visual similarity based personalized tourist attraction recommendation using geo-tagged photos (MEAL). MEAL utilizes the visual contents of photos and interaction behavior data to obtain the final embeddings of users and tourist attractions, which are then used to predict the visit probabilities. Specifically, by crossing the user and tourist attraction information of photos, we define four visual similarity levels and introduce a corresponding quintuplet loss to embed the visual contents of photos. In addition, to capture the significances of different photos, we exploit the self-attention mechanism to obtain the visual representations of users and tourist attractions. We conducted experiments on a dataset crawled from Flickr, and the experimental results proved the advantage of this method.

An AI has created hilarious postcard images of popular British tourist attractions, based solely on snippets from one-star Trip Advisor reviews. Text-to-image tool DALL-E, released by artificial intelligence firm OpenAI, is able to create images and artwork from text prompts. UK rental agency My Favourite Cottages used it to reimagine tourist spots including Stonehenge, Angel of the North, Brighton Palace Pier and Cornwall's Eden Project. Some of the results have a passing resemblance to the real thing, while others are like a window into a dystopian nightmare. DALL-E relies on artificial neural networks (ANNs), which simulate the way the brain works in order to learn.

Today, as seen in smart speakers, spoken dialogue technology is rapidly advancing to enable human-like interaction. However, current dialogue systems cannot pay attention not only to the content of speech, but also to the way of speaking and eye contact and facial expressions, while watching the facial expressions of the person with whom one is speaking. Therefore, this study participated in a Japanese competition called the "Dialogue Robot Competition" and attempted to develop a dialogue system that includes control of not only the content of speech but also the robot's facial expressions and gaze in order to realize a humanoid robot that can naturally interact with humans.

To improve the interactive capabilities of a dialogue system, e.g., to adapt to different customers, the Dialogue Robot Competition (DRC2022) was held. As one of the teams, we built a dialogue system with a pipeline structure containing four modules. The natural language understanding (NLU) and natural language generation (NLG) modules were GPT-2 based models, and the dialogue state tracking (DST) and policy modules were designed on the basis of hand-crafted rules. After the preliminary round of the competition, we found that the low variation in training examples for the NLU and failed recommendation due to the policy used were probably the main reasons for the limited performance of the system.

Every year, millions of tourists flock to Northern Ireland to visit Giant's Causeway - an unusual formation of around 40,000 hexagonal stone columns descending gently into the sea. Theories on the stones' formation range from them being built by a mythical giant Finn McCool to more scientific explanations. Now, Dr Mike Simms, curator of natural sciences at National Museums NI, has put forward the first new theory since 1940. Dr Simms considered why the extraordinary geological features are found at sea level only. To mark Unesco's International Geodiversity Day today, he has explained why he believes they were caused by an event which took just days - and not thousands of years as previously thought.

The 1911 video entitled'A Trip Through New York City' has been brought back to life more than a hundred years later by artificial intelligence. Shot by a Swedish film production company, the black and white footage has be restored with neural networks to create a colorized, sharper version of the black and white movie. The eight-minute clip transports viewers back in time to the Statue of Liberty, Battery Park, the New York Harbor and the famous Flatiron Building on Fifth Avenue. YouTuber Denis Shiryaev posted the new video on his site which is now in 4K quality at 60 frames per second. This'upscaled' footage was created using neural network-powered algorithms such as Topaz Labs' Gigapixel AI and DAIN.

Artificial intelligence, machine learning, and neural networks are words that are often seen in today's business technology headlines. Are robots taking over the world? Or are they just here to help you find the best hotel for your next holiday? Artificial intelligence may seem like the bane of some futuristic, dystopian society but you've probably already come into contact with it in something as simple as booking a hotel or flight. If you have ever binged watched a series or two on Netflix, you've seen the'what to watch next' recommendations pop up on the screen.