From Headspace to Apple One, these gift ideas will come in handy if you've procrastinated with your shopping. There are way too many online services and subscriptions to keep track of these days, but the flip side is there's a tool for just about everything. Time is just about up to get a physical gift shipped in time for the holidays, so below we've pulled together some of our favorite digital gifts and subscriptions, including time-tested video, music and gaming services as well as tools to clear your mental space and learn new skills. There are also a few subscriptions that provide ongoing, IRL deliveries, if you think your giftee will appreciate the nostalgic charm of a physical object. The big streaming video platforms just keep getting more expensive. As such, Disney's latest content bundle feels like a breath of fresh air.

Ethnography (social scientific methods that illuminate how people understand, navigate and shape the real world contexts in which they live their lives) and machine learning (computational techniques that use big data and statistical learning models to perform quantifiable tasks) are each core to contemporary social science. Yet these tools have remained largely separate in practice. This chapter draws on a growing body of scholarship that argues that ethnography and machine learning can be usefully combined, particularly for large comparative studies. Specifically, this paper (a) explains the value (and challenges) of using machine learning alongside qualitative field research for certain types of projects, (b) discusses recent methodological trends to this effect, (c) provides examples that illustrate workflow drawn from several large projects, and (d) concludes with a roadmap for enabling productive coevolution of field methods and machine learning.

Human-robot interaction requires to be studied in the wild. In the summers of 2022 and 2023, we deployed two trash barrel service robots through the wizard-of-oz protocol in public spaces to study human-robot interactions in urban settings. We deployed the robots at two different public plazas in downtown Manhattan and Brooklyn for a collective of 20 hours of field time. To date, relatively few long-term human-robot interaction studies have been conducted in shared public spaces. To support researchers aiming to fill this gap, we would like to share some of our insights and learned lessons that would benefit both researchers and practitioners on how to deploy robots in public spaces. We share best practices and lessons learned with the HRI research community to encourage more in-the-wild research of robots in public spaces and call for the community to share their lessons learned to a GitHub repository.

Research in speech technologies and comparative linguistics depends on access to diverse and accessible speech data. The UCLA Phonetics Lab Archive is one of the earliest multilingual speech corpora, with long-form audio recordings and phonetic transcriptions for 314 languages (Ladefoged et al., 2009). Recently, 95 of these languages were time-aligned with word-level phonetic transcriptions (Li et al., 2021). Here we present VoxAngeles, a corpus of audited phonetic transcriptions and phone-level alignments of the UCLA Phonetics Lab Archive, which uses the 95-language CMU re-release as our starting point. VoxAngeles also includes word- and phone-level segmentations from the original UCLA corpus, as well as phonetic measurements of word and phone durations, vowel formants, and vowel f0. This corpus enhances the usability of the original data, particularly for quantitative phonetic typology, as demonstrated through a case study of vowel intrinsic f0. We also discuss the utility of the VoxAngeles corpus for general research and pedagogy in crosslinguistic phonetics, as well as for low-resource and multilingual speech technologies. VoxAngeles is free to download and use under a CC-BY-NC 4.0 license.

Today, many systems use artificial intelligence (AI) to solve complex problems. While this often increases system effectiveness, developing a production-ready AI-based system is a difficult task. Thus, solid AI engineering practices are required to ensure the quality of the resulting system and to improve the development process. While several practices have already been proposed for the development of AI-based systems, detailed practical experiences of applying these practices are rare. In this paper, we aim to address this gap by collecting such experiences during a case study, namely the development of an autonomous stock trading system that uses machine learning functionality to invest in stocks. We selected 10 AI engineering practices from the literature and systematically applied them during development, with the goal to collect evidence about their applicability and effectiveness. Using structured field notes, we documented our experiences. Furthermore, we also used field notes to document challenges that occurred during the development, and the solutions we applied to overcome them. Afterwards, we analyzed the collected field notes, and evaluated how each practice improved the development. Lastly, we compared our evidence with existing literature. Most applied practices improved our system, albeit to varying extent, and we were able to overcome all major challenges. The qualitative results provide detailed accounts about 10 AI engineering practices, as well as challenges and solutions associated with such a project. Our experiences therefore enrich the emerging body of evidence in this field, which may be especially helpful for practitioner teams new to AI engineering.

If you haven't met Sia, perhaps you should get to know her. Sia is a digital AI assistant who helps make sense of the deluge of unstructured data. My company, Opentopic, a 25-employee startup, developed Sia for people who work in the financial services industry. Powered by IBM Watson and blockchain, purple-haired Sia won't tell anyone what to do or predict the future. But she can unlock insights from the overwhelming volume of public and private data that comes at people every second of their professional lives.

People are living longer, driving the percentage of those over 65 to unprecedented highs. Today, 8.5 percent of people worldwide are aged 65 and over; this will double to nearly 17 percent by 2050. With this coming age wave, there will not be enough resources to continue with current caregiving models. Higher costs and a declining number of caregivers threaten the quality and availability of care to this growing demographic. However, despite the challenging demographics, technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) can be applied to help enhance overall elder well-being and enable improved care at lower costs and with reduced human effort.

Artificial intelligence has received an extraordinary amount of hype from the media. Hollywood in particular has pushed a dystopian view--it's science fiction that has an awful lot of fiction in the science. We are heading into an era where we'll be increasingly interfacing with artificial intelligence--as robots, machines, drones, self-driving cars, chatbots, etc. And because of the media's AI hype, many people fear this future. At Soul Machines, we think that people will be more comfortable interacting with AI if these systems are actually more like us--if we can interact with these systems in natural ways, and over time, learn to trust and comfortably engage with them.

Italy's population is growing older. Today, more than 22 percent of our citizens are 65-plus. By 2050, experts say that number will reach 40 percent. There will be an immense need for elderly care. But will the healthcare industry be prepared for this demographic shift?

Cyberbullying is a critical issue to the health and mental health of our children and teens. Eighty-seven percent of youth have witnessed cyberbullying. Nearly two-thirds of students who have experienced cyberbullying stated that it affected their ability to learn and feel safe at school. At Identity Guard, we began looking into how our monitoring services, empowered by IBM Watson technologies, could be applied to this issue in 2016. We reached out to academics and experts to learn more about cyberbullying and its consequences, and to ascertain how we might design an effective solution to combat it.