Large Language Models (LLMs) hold the potential to perform a variety of text processing tasks and provide textual explanations for proposed actions or decisions. In the era of hybrid work, LLMs can provide intelligent decision support for workers who are designing their hybrid work plans. In particular, they can offer suggestions and explanations to workers balancing numerous decision factors, thereby enhancing their work experience. In this paper, we present a decision support model for workspaces in hybrid work environments, leveraging the reasoning skill of LLMs. We first examine LLM's capability of making suitable workspace suggestions. We find that its reasoning extends beyond the guidelines in the prompt and the LLM can manage the trade-off among the available resources in the workspaces. We conduct an extensive user study to understand workers' decision process for workspace choices and evaluate the effectiveness of the system. We observe that a worker's decision could be influenced by the LLM's suggestions and explanations. The participants in our study find the system to be convenient, regardless of whether reasons are provided or not. Our results show that employees can benefit from the LLM-empowered system for their workspace selection in hybrid workplace.

Indoor monocular depth estimation has attracted increasing research interest. Most previous works have been focusing on methodology, primarily experimenting with NYU-Depth-V2 (NYUv2) Dataset, and only concentrated on the overall performance over the test set. However, little is known regarding robustness and generalization when it comes to applying monocular depth estimation methods to real-world scenarios where highly varying and diverse functional \textit{space types} are present such as library or kitchen. A study for performance breakdown into space types is essential to realize a pretrained model's performance variance. To facilitate our investigation for robustness and address limitations of previous works, we collect InSpaceType, a high-quality and high-resolution RGBD dataset for general indoor environments. We benchmark 12 recent methods on InSpaceType and find they severely suffer from performance imbalance concerning space types, which reveals their underlying bias. We extend our analysis to 4 other datasets, 3 mitigation approaches, and the ability to generalize to unseen space types. Our work marks the first in-depth investigation of performance imbalance across space types for indoor monocular depth estimation, drawing attention to potential safety concerns for model deployment without considering space types, and further shedding light on potential ways to improve robustness. See \url{https://depthcomputation.github.io/DepthPublic} for data and the supplementary document. The benchmark list on the GitHub project page keeps updates for the lastest monocular depth estimation methods.

With the advancement of IoT technology, recognizing user activities with machine learning methods is a promising way to provide various smart services to users. High-quality data with privacy protection is essential for deploying such services in the real world. Data streams from surrounding ambient sensors are well suited to the requirement. Existing ambient sensor datasets only support constrained private spaces and those for public spaces have yet to be explored despite growing interest in research on them. To meet this need, we build a dataset collected from a meeting room equipped with ambient sensors. The dataset, DOO-RE, includes data streams from various ambient sensor types such as Sound and Projector. Each sensor data stream is segmented into activity units and multiple annotators provide activity labels through a cross-validation annotation process to improve annotation quality. We finally obtain 9 types of activities. To our best knowledge, DOO-RE is the first dataset to support the recognition of both single and group activities in a real meeting room with reliable annotations.

Imagine an automated meeting room, whether it be a conference room, lecture hall, or council chambers. The displays turn on automatically, the lights dim or brighten to the right level, previously configured for the type of meeting you are having. Cameras focus on whoever is speaking, switching seamlessly from presenter to audience member, when required. Inconspicuous microphones pick up high-quality sound. Recording or conferencing begins automatically, on schedule, or by voice command.

Ignite is also very much a forward-looking conference that keeps the changing role of IT in mind. And while there isn't a lot of consumer news at the event, the company does tend to make a few announcements for developers, as well. This year's Ignite was especially news-heavy. Ahead of the event, the company provided journalists and analysts with an 87-page document that lists all of the news items. If I counted correctly, there were about 175 separate announcements.

According to Gartner, artificial intelligence (AI) is not defined by a single technology but by an array of capabilities and research, from advances in algorithms to abundant computing power and advanced analytical methods such as deep learning. It sounds like the voice that responds from a smart speaker when we ask about the weather or to tune into a podcast. A vast majority of CXOs are already relying on consumer technologies such as voice-activated digital assistants in their work, according to a recent survey by PwC. Imagine how much more powerful those virtual assistants could be with access to the collective knowledge of the enterprise and the ability to know individual users and what they need to work best. And imagine putting that power into the hands of users across the enterprise, in the meeting room, on a factory floor or in any device they use to do their jobs.

The world's biggest tech manufacturers are currently taking the stage at IFA 2019 in Berlin, Germany. The event is billed as Europe's largest consumer tech show where consumer tech meets innovation. But in a digital world where the lines between B2B and B2C are becoming increasingly blurry, there are a few critical lessons for businesses from all industries too. On the surface, IFA is simply a platform for 1,939 of the world's leading tech brands and manufacturers to showcase their latest innovations, products, or services across 163,900 square meters. Sure, many of these products will appear on wish lists and dominate headlines around Black Friday, Cyber Monday and the impending holiday season. But, if you zoom out from that, there is a message for every CEO.

Employees will not need a key to get into the office of the future when it opens in Berlin this year, featuring ample meeting space, plenty of copy machines always stocked with paper along with high-quality air processed to maximize worker health and minimize sick time. Their smartphones will help guide them around their new workplace -- and they may need the assistance because they will not have permanent desks. With technology changing how and where we work, property developers are tapping artificial intelligence to create more sustainable workplaces to help staff work more efficiently and comfortably. Employees will not need a key to get into the office of the future when it opens in Berlin this year. Fierce competition for talent is turbo-charging the trend in Berlin.

According to Gartner, artificial intelligence (AI) is not defined by a single technology but by an array of capabilities and research, from advances in algorithms to abundant computing power and advanced analytical methods such as deep learning. It sounds like the voice that responds from a smart speaker when we ask about the weather or to tune into a podcast. A vast majority of CXOs are already relying on consumer technologies such as voice-activated digital assistants in their work, according to a recent survey by PwC. Imagine how much more powerful those virtual assistants could be with access to the collective knowledge of the enterprise and the ability to know individual users and what they need to work best. And imagine putting that power into the hands of users across the enterprise, in the meeting room, on a factory floor or in any device they use to do their jobs.

Once cars can finally drive themselves, we'll have more time to enjoy the journey and do other, much more interesting stuff instead. At least that's the concept behind some of the designs below, developed by retail giant IKEA's "future living lab," SPACE10, based in Copenhagen. SPACE10 was asked to come up with designs for autonomous vehicles that would be extensions of our homes, offices, and local institutions. Some of the agency's seven ideas, shown below, are almost practical. Who can't imagine autonomously driven cafés or pop-up stores?