The software-defined nature of the HRL131 means it is situationally aware, with the ability to adapt its scan pattern depending on the driving scenario to maximize safety. It's critical that manufacturers be able to test and validate these performance modes and the product's performance in diverse situations, which NVIDIA DRIVE Sim will uniquely enable.

The registration, effective September 15, applies to a comic book called Zarya of the Dawn. Kashtanova created the artwork for Zarya using Midjourney, a commercial image synthesis service. I was open how it was made and put Midjourney on the cover page. It wasn't altered in any other way. Just the way you saw it here.

Who you are, what you have experienced, and how you think inspires us to be innovative and bold. Loyal is an equal opportunity employer. We hire great people from a wide variety of backgrounds, not just because it's the right thing to do, but because it makes our company stronger. We welcome the unique contributions that you can bring in terms of your education, opinions, culture, ethnicity, race, ancestry, sex, gender identity and expression, national origin, citizenship, marital status, age, languages spoken, veteran status, color, religion, disability, sexual orientation, and beliefs. We consider qualified applicants regardless of criminal histories, consistent with legal requirements. Further, consistent with applicable federal and state law, Loyal provides reasonable accommodations when requested by qualified applicants or employees with disabilities, unless doing so would cause an undue hardship. Loyal's policy regarding requests for reasonable accommodation applies to all aspects of employment, including the application process.

In September 2022, the United Nations System Chief Executives Board for Coordination endorsed the Principles for the Ethical Use of Artificial Intelligence in the United Nations System, developed through the High-level Committee on Programmes (HLCP) which approved the Principles at an intersessional meeting in July 2022. These Principles were developed by a workstream co-led by United Nations Educational, Scientific and Cultural Organization (UNESCO) and the Office of Information and Communications Technology of the United Nations Secretariat (OICT), in the HLCP Inter-Agency Working Group on Artificial Intelligence. The Principles are based on the Recommendation on the Ethics of Artificial Intelligence adopted by UNESCO's General Conference at its 41st session in November 2021. This set of ten principles, grounded in ethics and human rights, aims to guide the use of artificial intelligence (AI) across all stages of an AI system lifecycle across United Nations system entities. It is intended to be read with other related policies and international law, and includes the following principles: do no harm; defined purpose, necessity and proportionality; safety and security; fairness and non-discrimination; sustainability; right to privacy, data protection and data governance; human autonomy and oversight; transparency and explainability; responsibility and accountability; and inclusion and participation.

We study the problem of online dynamic pricing with two types of fairness constraints: a "procedural fairness" which requires the proposed prices to be equal in expectation among different groups, and a "substantive fairness" which requires the accepted prices to be equal in expectation among different groups. A policy that is simultaneously procedural and substantive fair is referred to as "doubly fair". We show that a doubly fair policy must be random to have higher revenue than the best trivial policy that assigns the same price to different groups. In a two-group setting, we propose an online learning algorithm for the 2-group pricing problems that achieves $\tilde{O}(\sqrt{T})$ regret, zero procedural unfairness and $\tilde{O}(\sqrt{T})$ substantive unfairness over $T$ rounds of learning. We also prove two lower bounds showing that these results on regret and unfairness are both information-theoretically optimal up to iterated logarithmic factors. To the best of our knowledge, this is the first dynamic pricing algorithm that learns to price while satisfying two fairness constraints at the same time.

The use of meta-rules in logic, i.e., rules whose content includes other rules, has recently gained attention in the setting of non-monotonic reasoning: a first logical formalisation and efficient algorithms to compute the (meta)-extensions of such theories were proposed in Olivieri et al (2021) This work extends such a logical framework by considering the deontic aspect. The resulting logic will not just be able to model policies but also tackle well-known aspects that occur in numerous legal systems. The use of Defeasible Logic (DL) to model meta-rules in the application area we just alluded to has been investigated. Within this line of research, the study mentioned above was not focusing on the general computational properties of meta-rules. This study fills this gap with two major contributions. First, we introduce and formalise two variants of Defeasible Deontic Logic with Meta-Rules to represent (1) defeasible meta-theories with deontic modalities, and (2) two different types of conflicts among rules: Simple Conflict Defeasible Deontic Logic, and Cautious Conflict Defeasible Deontic Logic. Second, we advance efficient algorithms to compute the extensions for both variants.

Text-to-image tools, such as DALL-E, Midjourney, Craiyon, and Stable Diffusion, have opened the floodgates for machine-made artwork. Anyone can either pay a small fee or use a free model to create images from text descriptions. All you have to do is tell, in writing, the AI system what kind of scene you want it to make, and the software will generate it for you. The quality of these images has got so good they are now being used by professionals to make magazine front covers, adverts, win art competitions, and so on. You can see them as interesting tools to generate pictures, or as the end of art as we know it.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! Even though responsible artificial intelligence (AI) is considered a top management concern, a newly released report from Boston Consulting Group and MIT Sloan Management Review finds that few leaders are prioritizing initiatives to make it happen. Of the 84% of respondents who believe that responsible AI should be a top management priority, only 56% said that it is, in fact, a top priority -- with only 25% of those reporting their organizations has a fully mature program in place, according to the research. Further, only 52% of organizations reported they have a responsible AI program in place – and 79% of those programs are limited in scale and scope, the BCG/MIT Sloan report said.

The problems with Clearview AI's facial recognition system, particularly in the hands of police, are myriad and serious. That the technology exists as it does at all raises significant ethical concerns, and how it has been used to feed people into the criminal justice system raises significant due process ones as well. But an article in the New York Times the other day might seem to suggest that it perhaps also has a cuddly side, one that might actually help criminal defendants, instead of just hurting them. But don't be fooled – there is nothing benign about the facial recognition technology pushed by Clearview AI, and even this story ultimately provides no defense for it. It was not the hero here, because the problem it supposedly "solved" was not the problem that actually needed solving.

AI thrives on the processing of large volumes of data to be able to deliver focused and targeted solutions. Last year in April, the European Commission (EC) unveiled a legal framework for AI, the Artificial Intelligence Act (AI Act), the first of its kind. The AI Act aims to implement an ecosystem of trust by proposing a legal framework within which people use AI-based solutions while encouraging businesses to develop them. When it comes to technology, Europe has made no secret of its desire to export its values across the world, at least at a principle level. Similar to the General Data Protection Regulation (GDPR), which has become the conventional norm, the AI Act could also become a global precedent, determining to what extent AI may seep into our general day-to-day functioning, or whether it will be limited to automated use by larger entities only.