A California state court jury has handed Tesla Inc a sweeping win, finding that the carmaker's Autopilot feature did not fail to perform safely in what appears to be the first trial related to a crash involving the partially automated driving software. The verdict could be an important victory for Tesla as it tests and rolls out its Autopilot and more advanced "Full Self-Driving (FSD)" system, which Chief Executive Elon Musk has touted as crucial to his company's future, but which has drawn regulatory and legal scrutiny. Justine Hsu, a resident of Los Angeles, sued the electric vehicle maker in 2020, saying her Tesla Model S swerved into a curb while it was on Autopilot and then an airbag was deployed "so violently it fractured Plaintiff's jaw, knocked out teeth, and caused nerve damage to her face". She alleged there were defects in the design of Autopilot and the airbag, and sought more than $3m in damages for the alleged defects and other claims. Tesla denied liability for the 2019 accident.

European lawmakers are putting their finishing touches on a set of wide-ranging rules designed to govern the use of artificial intelligence that, if passed, would make the E.U. the first major jurisdiction outside of China to pass targeted AI regulation. That has made the forthcoming legislation the subject of fierce debate and lobbying, with opposing sides battling to ensure that its scope is either widened or narrowed. Lawmakers are close to agreeing on a draft version of the law, the Financial Times reported last week. After that, the law will progress to negotiations between the bloc's member states and executive branch. The rules could set a global bar for how companies build and deploy their AI systems as companies may find it easier to comply with E.U. rules globally rather than to build different products for different regions--a phenomenon known as the "Brussels effect."

There's good reason to fear that A.I. systems like ChatGPT and GPT4 will harm democracy. Public debate may be overwhelmed by industrial quantities of autogenerated argument. People might fall down political rabbit holes, taken in by superficially convincing bullshit, or obsessed by folies à deux relationships with machine personalities that don't really exist. These risks may be the fallout of a world where businesses deploy poorly tested A.I. systems in a battle for market share, each hoping to establish a monopoly. A.I. could advance the public good, not private profit, and bolster democracy instead of undermining it.

Users are able to trick ChatGPT into writing code for malicious software applications by entering a prompt that makes the artificial intelligence chatbot respond as if it were in developer mode, Japanese cybersecurity experts said Thursday. The discovery has highlighted the ease with which safeguards put in place by developers to prevent criminal and unethical use of the tool can be circumvented. Amid growing concerns that AI chatbots will lead to more crime and social fragmentation, calls are growing for discussions on appropriate regulations at the Group of Seven summit in Hiroshima next month and other international forums. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

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This year is the 10th anniversary of Lucas Pope's wrenching game about being a border officer in the functional communist country of Arstotzka, deciding when to turn desperate people away and when to risk your job but save your conscience by letting them slip by. It remains an impactful and illuminating exploration of how documentation can save or cost lives, and the moral and human cost of border enforcement. Your wife, Nour, has finally decided to risk getting out of Syria as the bombs keep falling – but you must stay behind, to look after your mother and grandfather. In this game, you are not the person fleeing but the person trying to survive back home, waiting for text message updates or an occasional photo and doing your best to give good advice from afar. An affecting work of interactive fiction told through the medium of the smartphone.

Naftali Bennett spoke exclusively with Fox News Digital about the benefits of AI and the need to set parameters for its use now. Israel is working to integrate artificial intelligence (AI) into its battlefield operations as it looks to lead the way on handling "the biggest game changer" for technology. "The future of defense systems and of military will rely heavily on artificial intelligence," former Israeli Prime Minister Naftali Bennett told Fox News Digital in an exclusive interview. "I'm talking about the analysis of massive data in intelligence," he explained. Any country who seeks to be strong has to develop now an AI strategy," which he said he did during his tenure as prime minister. The Israel Defense Forces announced in February that the force has started utilizing AI in its operations, saying new digital methods helped produce "200 new target assets" during a 10-day operation in 2021 to successfully target at least two Hamas commanders, The Jerusalem Post reported. "Remember breaking the human barrier?

Naftali Bennett spoke exclusively with Fox News Digital about the benefits of AI and the need to set parameters for its use now. The U.S. military is embracing artificial intelligence as a tool for quickly digesting data and helping leaders make the right decision – and not to make those decisions for the humans in charge, according to two top AI advisors in U.S. Central Command. CENTCOM, which is tasked with safeguarding U.S. national security in the Middle East and Southeast Asia, just hired Dr. Andrew Moore as its first AI advisor. Moore is the former director of Google Cloud AI and former dean of the Carnegie Mellon University School of Computer Science, and he'll be working with Schuyler Moore, CENTCOM's chief technology officer. In an interview with Fox News Digital, they both agreed that while some are imagining AI-driven weapons, the U.S. military aims to keep humans in the decision-making seat, and using AI to assess massive amounts of data that helps the people sitting in those seats.

Along with Markov chain Monte Carlo (MCMC) methods, variational inference (VI) has emerged as a central computational approach to large-scale Bayesian inference. Rather than sampling from the true posterior $\pi$, VI aims at producing a simple but effective approximation $\hat \pi$ to $\pi$ for which summary statistics are easy to compute. However, unlike the well-studied MCMC methodology, algorithmic guarantees for VI are still relatively less well-understood. In this work, we propose principled methods for VI, in which $\hat \pi$ is taken to be a Gaussian or a mixture of Gaussians, which rest upon the theory of gradient flows on the Bures--Wasserstein space of Gaussian measures. Akin to MCMC, it comes with strong theoretical guarantees when $\pi$ is log-concave.

However, all of these terms are also being significantly overloaded. In this paper, we discuss their strong relation under particular interpretations. Specifically, we discuss a notion of explanation termed ontological unpacking, which aims at explaining symbolic domain descriptions (conceptual models, knowledge graphs, logical specifications) by revealing their ontological commitment in terms of their assumed truthmakers, i.e., the entities in one's ontology that make the propositions in those descriptions true. To illustrate this idea, we employ an ontological theory of relations to explain (by revealing the hidden semantics of) a very simple symbolic model encoded in the standard modeling language UML. We also discuss the essential role played by ontology-driven conceptual models (resulting from this form of explanation processes) in properly supporting semantic interoperability tasks. Finally, we discuss the relation between ontological unpacking and other forms of explanation in philosophy and science, as well as in the area of Artificial Intelligence.