We present SocialGenPod, a decentralised and privacy-friendly way of deploying generative AI Web applications. Unlike centralised Web and data architectures that keep user data tied to application and service providers, we show how one can use Solid -- a decentralised Web specification -- to decouple user data from generative AI applications. We demonstrate SocialGenPod using a prototype that allows users to converse with different Large Language Models, optionally leveraging Retrieval Augmented Generation to generate answers grounded in private documents stored in any Solid Pod that the user is allowed to access, directly or indirectly. SocialGenPod makes use of Solid access control mechanisms to give users full control of determining who has access to data stored in their Pods. SocialGenPod keeps all user data (chat history, app configuration, personal documents, etc) securely in the user's personal Pod; separate from specific model or application providers. Besides better privacy controls, this approach also enables portability across different services and applications. Finally, we discuss challenges, posed by the large compute requirements of state-of-the-art models, that future research in this area should address. Our prototype is open-source and available at: https://github.com/Vidminas/socialgenpod/.

The authors are concerned about the safety, health, and rights of the European citizens due to inadequate measures and procedures required by the current draft of the EU Artificial Intelligence (AI) Act for the conformity assessment of AI systems. We observe that not only the current draft of the EU AI Act, but also the accompanying standardization efforts in CEN/CENELEC, have resorted to the position that real functional guarantees of AI systems supposedly would be unrealistic and too complex anyways. Yet enacting a conformity assessment procedure that creates the false illusion of trust in insufficiently assessed AI systems is at best naive and at worst grossly negligent. The EU AI Act thus misses the point of ensuring quality by functional trustworthiness and correctly attributing responsibilities. The trustworthiness of an AI decision system lies first and foremost in the correct statistical testing on randomly selected samples and in the precision of the definition of the application domain, which enables drawing samples in the first place. We will subsequently call this testable quality functional trustworthiness. It includes a design, development, and deployment that enables correct statistical testing of all relevant functions. We are firmly convinced and advocate that a reliable assessment of the statistical functional properties of an AI system has to be the indispensable, mandatory nucleus of the conformity assessment. In this paper, we describe the three necessary elements to establish a reliable functional trustworthiness, i.e., (1) the definition of the technical distribution of the application, (2) the risk-based minimum performance requirements, and (3) the statistically valid testing based on independent random samples.

Automotive: Autonomous cars are as inherent to the vision of the future as space travel and holograms. Automobiles have been seen as the final leading edge of technological innovation. In the meantime, artificial intelligence has slowly begun to transform the vehicles through integrated innovations such as preventing accidents through risk assessment and driver monitoring, personalized vehicles, and in-car assistance. The impact of technology on automobiles and the entire automotive sector will expand in the coming years with the increasing penetration of AI for different operations. Moreover, neural networks and specific algorithms are used in autonomous vehicles to collect data, analyze objects, and make accurate decisions on the road.

The inventor of the World Wide Web (also known as the Web), Tim Berners-Lee said that in the future, people will have their own personal AI assistant, similar to ChatGPT. In a recent episode of CNBC's Beyond the Valley podcast, Berners-Lee said that his new company envisions people having online'pods' where all of their personal data is stored. Inrupt, a startup co-founded by Berners-Lee, aims to provide web users with a single login that can be used across multiple websites. Inrupt intends to store individual users' data in digital containers as part of its work on developing that technology. The pods will be capable of granting websites or services access to some or all of a person's personal information, ranging from sleeping patterns to shopping preferences, reports Fortune.

Artificial intelligence (AI) is all around us. It is playing a vital role from Facebook News Feed to Google Search. Despite the technology's relative novelty, the general public as well as businesses have already witnessed numerous applications of AI and are, by now, convinced about AI's ability to replicate human thought and assist in performing cognitive and creative tasks. Artificial intelligence has quickly grown from being a distant hope to a casual part of the present reality. Computer programs capable of performing human-like cognitive and computational tasks without human intervention are rapidly growing in capability as well as ubiquity.

In less than a year, these same scholars will be writing about the "future of labor," and given the speed of innovation, by the time these articles are published, they will be made obsolete. Based on the research recently conducted by the newly formed Stanford Digital Economy Lab, before the pandemic, in early March, remote workers represented 15% of the workforce in enterprise-level organizations. Now that number is well over 50%, and the trajectory is steepening daily as we record higher levels of infections. In this article, we will attempt to build on our current understanding of the future of work and to identify potential challenges that could arise for different demographic groups. Dropbox was the first major digitized company to announce a remote-first work environment for all of its employees.

Samsung have unveiled a tiny robot assistant in the shape of a ball, which can roll around and help patrol a users home - and even act as a fitness buddy. The tech giant unveiled'Ballie' during one of two keynotes at the Consumer Electronics Show in Las Vegas. Samsung consumer electronics CEO H.S. Kim demonstrated how the ball-shaped bot is able to follow its owner around, traveling closely but also recognizing personal space and speed. Samsung's'Ballie' was revealed during one of two keynotes at the Consumer Electronics Show in Las Vegas Samsung consumer electronics CEO H.S. Kim demonstrated how the ball-shaped bot works When Kim stepped forward, Ballie reacted by wheeling itself further back; when Kim began to increase his pace, Ballie sped up. 'I think he likes me,' Kim said turning to the crowd.

work is creative, problem-solving work which requires high levels of education and is usually well-rewarded. Manual work is skilled dexterous physical work. It usually does not require high levels of education and is typically poorly-paid and highly-precarious (i.e.