Vision-Language Models (VLMs) are increasingly deployed in diverse cultural contexts, yet their internal biases remain poorly understood. In this work, we propose a novel framework to systematically evaluate how VLMs encode cultural differences and biases related to race, gender, and physical traits across countries. We introduce three retrieval-based tasks: (1) Race to Country retrieval, which examines the association between individuals from specific racial groups (East Asian, White, Middle Eastern, Latino, South Asian, and Black) and different countries; (2) Personal Traits to Country retrieval, where images are paired with trait-based prompts (e.g., Smart, Honest, Criminal, Violent) to investigate potential stereotypical associations; and (3) Physical Characteristics to Country retrieval, focusing on visual attributes like skinny, young, obese, and old to explore how physical appearances are culturally linked to nations. Our findings reveal persistent biases in VLMs, highlighting how visual representations may inadvertently reinforce societal stereotypes.

An artificial intelligence-based chatbot will start answering questions from a Buddhist viewpoint in English in Bhutan, its developers including a Kyoto University professor said Monday. The team of the university and a startup initially developed a chatbot called Buddhabot in 2021 with the Japanese translation of the Sutta Nipata, considered to be the oldest collection of discourses of Buddha. Data on other classic collections were also incorporated into the AI Buddha later. In 2023, the team remodeled the Buddhabot using OpenAI's ChatGPT generative AI to create Buddhabot Plus, which adds interpretations and explanations to the discourses. The English version of Buddhabot Plus was completed last year following the Bhutanese government's request.

The Bhutanese government is increasing its utilization of technological approaches such as including Remote Sensing-based knowledge in their decision-making process. This study focuses on crop type and crop extent in Paro, one of the top rice-yielding districts in Bhutan, and employs publicly available NICFI high-resolution satellite imagery from Planet. Two Deep Learning (DL) approaches, point-based (DNN) and patch-based (U-Net), models were used in conjunction with cloud-computing platforms. Three different models per DL approaches (DNN and U-Net) were trained: 1) RGBN channels from Planet; 2) RGBN and elevation data (RGBNE); 3) RGBN and Sentinel-1 (S1) data (RGBNS), and RGBN with E and S1 data (RGBNES). From this comprehensive analysis, the U-Net displayed higher performance metrics across both model training and model validation efforts. Among the U-Net model sets, the RGBN, RGBNE, RGBNS, and RGBNES models had an F1-score of 0.8546, 0.8563, 0.8467, and 0.8500 respectively. An independent model evaluation was performed and found a high level of performance variation across all the metrics. For this independent model evaluation, the U-Net RGBN, RGBNE, RGBNES, and RGBN models displayed the F1-scores of 0.5935, 0.6154, 0.5882, and 0.6582, suggesting U-Net RGBNES as the best model. The study shows that the DL approaches can predict rice. Also, DL methods can be used with the survey-based approaches currently utilized by the Bhutan Department of Agriculture. Further, this study demonstrated the usage of regional land cover products such as SERVIR's RLCMS as a weak label approach to capture different strata addressing the class imbalance problem and improving the sampling design for DL application. Finally, through preliminary model testing and comparisons outlined it was shown that using additional features such as NDVI, EVI, and NDWI did not drastically improve model performance.

The Department of Innovation & Technology (InnoTech) under Druk Holding & Investments (DHI), the commercial arm of the Royal Government of Bhutan, has partnered with Omdena, a global collaborative platform that makes AI for good accessible to all. This partnership is a step further in DHI InnoTech's mission to strategize technology and innovation pathways to enhance access and diffusion of emerging technologies, and build local capacity in the fields of science and technology. Omdena will assist InnoTech in hosting a global 2-week hackathon wherein InnoTech will identify key themes and issues that can be resolved using innovative AI/ML applications. Omdena will work with 50 AI engineers over an additional 8-week challenge to develop the idea or POC selected from the hackathon into a fully deployable algorithm. The pilot InnoTech-Omdena event will serve as a showcase for local institutions and the general public who are interested in AI/ML.

Bhutan is sometimes described as \a pebble between two boulders", a small country caught between the two most populous nations on earth: India and China. This pebble is, however, about to be caught up in a vortex: the transformation of our economic, political and social orders by new technologies like Artificial Intelligence. What can a small nation like Bhutan hope to do in the face of such change? What should the nation do, not just to weather this storm, but to become a better place in which to live?

The Space Invaders arcade video game, celebrating its 40th anniversary, is a classic piece of software credited as one of the earliest digital shooting games. As a game designer and teacher of games, I know how meaning is carried from designer to the mechanics of play. As a game studies researcher, I also know how games reveal myth, meaning and culture. An analysis of Pac-Man, for instance, shows how that game embodies many values of its day – including consumerism, drug use and gender politics. The message in Space Invaders is as basic as the graphics: when faced with conflict, players have no option except to blast it away.

The war for your digital home is waging. Apple has finally followed Amazon, Google and Microsoft by launching a smart speaker with a voice-controlled artificial intelligence assistant. Yet even though the "HomePod" is another technological marvel, there's a chance Apple is already losing the battle. The competition isn't just through the sound quality of the speaker – but the other things that users can do with it. The most common requests to AI personal assistants such as Apple's Siri are reportedly to play music, read the weather forecast and set timers or reminders.

The Chinese military, Thursday, strongly condemned and opposed the trespassing of an Indian Unmanned Aerial Vehicle (UAV) into Chinese airspace. India, on the same day, claimed that the UAV "lost control" and entered into Chinese territory through the Sikkim (a state in India) border. According to a report by the Hindustan Times, an Indian news website, India replied to the incident, Thursday, claiming that the UAV was on a "regular training mission," lost control and crossed the border area from Sikkim. A statement by the Indian Defense Ministry said: "An Indian UAV which was on a regular training mission inside the Indian territory lost contact with the ground control due to some technical problem and crossed over the LAC [Line of Actual Control] in the Sikkim Sector. As per standard protocol, the Indian border security personnel immediately alerted their Chinese counterparts to locate the UAV."