Xbox users in the US face price increases up to 50 percent on their monthly gaming subscription, making it a great time to check if you're on the right tier or if you even need to subscribe at all. Like it or loathe it, we live in a subscription economy. Music, movies, meal boxes, and more are no longer things you buy once. Gaming is no exception, and while every major player in the sector has some form of sub for players--from PlayStation Plus and Nintendo Switch Online for consoles to Apple Arcade on phones--none of them offered quite as much for a modest monthly fee as Xbox Game Pass. Depending on the subscription tier, the service gave players access to a significant library of titles and was available on Xbox consoles, PC, or via cloud gaming.

The electric vehicle tax credit is gone, and Tesla's new, more affordable models don't quite close the gap. For nearly two decades, CEO Elon Musk has promised Tesla would make a more affordable electric vehicle, to, as he put it in 2006, "help expedite the move from a mine-and-burn hydrocarbon economy towards a solar electric economy." On Tuesday, Tesla announced a new Model Y and Model 3 Standard, versions of its popular compact SUV and sedan stripped of a few higher-end touches and features to bring the price down to $39,990 and $36,990, respectively. They're both about $5,000 cheaper than the Premium variants, which goes a ways--but not all the way--toward recouping the $7,500 tax credit canceled by the GOP-led Congress this past summer . The price point also puts Tesla's newest models firmly in the "more affordable" EV camp.

The rapid development of artificial intelligence (AI) has significantly transformed human-computer interactions, making it essential to establish robust design standards to ensure effective, ethical, and human-centered AI (HCAI) solutions. Standards serve as the foundation for the adoption of new technologies, and human-AI interaction (HAII) standards are critical to supporting the industrialization of AI technology by following an HCAI approach. These design standards aim to provide clear principles, requirements, and guidelines for designing, developing, deploying, and using AI systems, enhancing the user experience and performance of AI systems. Despite their importance, the creation and adoption of HCAI-based interaction design standards face challenges, including the absence of universal frameworks, the inherent complexity of HAII, and the ethical dilemmas that arise in such systems. This chapter provides a comparative analysis of HAII versus traditional human-computer interaction (HCI) and outlines guiding principles for HCAI-based design. It explores international, regional, national, and industry standards related to HAII design from an HCAI perspective and reviews design guidelines released by leading companies such as Microsoft, Google, and Apple. Additionally, the chapter highlights tools available for implementing HAII standards and presents case studies of human-centered interaction design for AI systems in diverse fields, including healthcare, autonomous vehicles, and customer service. It further examines key challenges in developing HAII standards and suggests future directions for the field. Emphasizing the importance of ongoing collaboration between AI designers, developers, and experts in human factors and HCI, this chapter stresses the need to advance HCAI-based interaction design standards to ensure human-centered AI solutions across various domains.

Technical standards, or simply standards, are established documented guidelines and rules that facilitate the interoperability, quality, and accuracy of systems and processes. In recent years, we have witnessed an emerging paradigm shift where the adoption of generative AI (GenAI) models has increased tremendously, spreading implementation interests across standard-driven industries, including engineering, legal, healthcare, and education. In this paper, we assess the criticality levels of different standards across domains and sectors and complement them by grading the current compliance capabilities of state-of-the-art GenAI models. To support the discussion, we outline possible challenges and opportunities with integrating GenAI for standard compliance tasks while also providing actionable recommendations for entities involved with developing and using standards. Overall, we argue that aligning GenAI with standards through computational methods can help strengthen regulatory and operational compliance. We anticipate this area of research will play a central role in the management, oversight, and trustworthiness of larger, more powerful GenAI-based systems in the near future.

NVIDIA AI Enterprise 2.1 is now generally available for all enterprise users. Today, the global technology leader NVIDIA announced the most advanced version of its AI-powered data and analytics software for enterprise users. The new AI suite would enable users to fully-optimize their IT and Low Code DevOps processes in a highly scalable AI-based environments. These include applications across bare metal, virtual, container, and Cloud environments. The latest NVIDIA AI Enterprise 2.1 is part of NVIDIA's AI enterprise suite.

Microsoft's updated Responsible AI Standard is the internal framework for developing innovative AI products and services aligned with the company's core values. It sets out the best thinking on how we must design, develop, and deploy AI systems to serve human values and earn society's trust. The updated Responsible AI Standard was developed by a core working group, made up of colleagues from engineering, Aether, Microsoft Research, legal and policy teams. Three of those core team members provide insights on how the Standard was developed, moving the company from principles to practices.

Speech recognition or machine translation have entered the lives of millions of people but, to make the machine learning (ML) algorithms behind them work better, it takes a lot of annotated and structured data. One way to get this data is by creating your own using specialized tools, an approach for which Christophe Ré coined the term'Data Programming'. We now compare corpora annotated by hand and by humans as'Gold Standard' with'Silver Standard' data created semi-automatically by artificial means. While Ré's group has produced its own set of tools to do this (called'Snorkel'), we decided to address the problem from the angle of programming. Having spent many years doing research on formal grammars, I watched these so-called symbolic methods gradually decline in favour of statistical approaches.

We invite you to join Intel's Next Generation & Standards (NGS) Group and the 5G revolution! We are a global team of passionate engineers and technologists from diverse industry backgrounds, working together to realize a world of connected computing. Intel's NGS team is chartered with developing advanced prototypes of various technologies to deliver innovative and state of the art wireless experiences into the market within the Internet of Things, 5G Next Generation Wearable and IoT solutions and other world-class wireless connectivity technologies and products In this position, you will be working on advanced algorithm design, development and innovation towards the future emerging technologies in the Next Generation and Standards (NGS) group within Intel. PhD or Master's degree in Electrical Engineering, Computer Science, Video/Graphics/Image Processing, Computer Vision, Signal Processing or other related areas: The Next Generation and Standards Group's mission is to lead standards, ecosystem, and prototyping development efforts across Intel for advanced wireless communications IP, starting with 5G and beyond. This group brings together a panorama of competencies including standards creation, ecosystem development, use case and business development in creating advanced prototypes and technologies that propel Intel's leadership.

We had to go through a whole process of development and discovery, and, as a result of computer experts working hand in hand with domain experts over the course of 15 to 20 years, computers and specialized software were developed to suit different needs. Most people now are familiar with conversion rate optimization (CRO), where site operators try to maximize conversions by testing new ideas for design, messaging, user experience, and more. The operator sets parameters and goals, but the AI decides the combination of ideas, always trying to find a better answer and better results against that goal. And just like computerization, AI enablement will only be fully achieved once all of us can be considered AI experts by today's standards.

Movies like I, Robot, Wall-e and Bicentennial Man pose interesting questions that blur lines between man and machines. Now that we step forward into the "cognitive era" with machines capable of thinking and taking decisions just like humans, the question of what should be the guiding star for our actions is gaining a newfound importance. This is yet another issue that we must contend with, and that is – we must decide as to not only which ethical principles must be encoded into our man-made machines to think like us, but also how to encode these ethics. While for the most part, "Thou shalt not kill" remains a cornerstone of a principle for coding intelligence in AI.