If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
With the incorporation of new data gathering methods in clinical research, it becomes fundamental for survival analysis techniques to deal with high-dimensional or/and non-standard covariates. In this paper we introduce a general non-parametric independence test between right-censored survival times and covariates taking values on a general (not necessarily Euclidean) space X. We show that our test statistic has a dual interpretation, first in terms of the supremum of a potentially infinite collection of weight-indexed log-rank tests, with weight functions belonging to a reproducing kernel Hilbert space (RKHS) of functions; and second, as the norm of the difference of embeddings of certain finite measures into the RKHS, similar to the Hilbert-Schmidt Independence Criterion (HSIC) test-statistic. We study the asymptotic properties of the test, finding sufficient conditions to ensure that our test is omnibus. The test statistic can be computed straightforwardly, and the rejection threshold is obtained via an asymptotically consistent Wild-Bootstrap procedure.
While Amazon takes special care to position its Ring video doorbell product as a friendly, high-tech version of the traditional "neighborhood watch," U.S. lawmakers and privacy advocates are becoming increasingly skeptical. As they see it, Amazon Ring is putting into place few if any safeguards to protect personal privacy and civil rights. Now that Amazon Ring is partnering with hundreds of law enforcement and police agencies around the nation to share surveillance video, these privacy concerns are only mounting. In November, Amazon Ring released new details about its surprisingly extensive partnership agreements with law enforcement agencies. This update is a follow-up to a Washington Post article outlining Amazon Ring's new partnerships with law enforcement.
In extreme classification settings, embedding-based neural network models are currently not competitive with sparse linear and tree-based methods in terms of accuracy. Most prior works attribute this poor performance to the low-dimensional bottleneck in embedding-based methods. In this paper, we demonstrate that theoretically there is no limitation to using low-dimensional embedding-based methods, and provide experimental evidence that overfitting is the root cause of the poor performance of embedding-based methods. These findings motivate us to investigate novel data augmentation and regularization techniques to mitigate overfitting. To this end, we propose GLaS, a new regularizer for embedding-based neural network approaches.
In this paper, we (1) argue that the international human rights framework provides the most promising set of standards for ensuring that AI systems are ethical in their design, development and deployment, and (2) sketch the basic contours of a comprehensive governance framework, which we call'human rights-centred design, deliberation and oversight', for ensuring that AI can be relied upon to operate in ways that will not violate human rights.
Imagine a random walk that outputs a state only when visiting it for the first time. The observed output is therefore a repeat-censored version of the underlying walk, and consists of a permutation of the states or a prefix of it. We call this model initial-visit emitting random walk (INVITE). Prior work has shown that the random walks with such a repeat-censoring mechanism explain well human behavior in memory search tasks, which is of great interest in both the study of human cognition and various clinical applications. However, parameter estimation in INVITE is challenging, because naive likelihood computation by marginalizing over infinitely many hidden random walk trajectories is intractable.
The Electronic Frontier Foundation (EFF) has published an extensive study into the hidden techniques and methods used by online service providers to collect and track our personal information and activities. On Monday, as shoppers plundered e-commerce websites for Cyber Monday bargains, the civil and privacy rights outfit released "Behind the One-Way Mirror," outlining corporate surveillance methods with a focus on behind-the-scenes tracking. The paper covers a variety of different tracking methods including browser fingerprinting, invisible pixel images, social widgets, mobile tracking, and facial recognition employed by tech giants including Amazon, Facebook, Google, Twitter, as well as countless data brokers, to "collect information about who we are, what we like, where we go, and who our friends are." Third-party tracking is usually invisible to the naked eye. Code, images, and plugins can all contain functions that track browsing, activities, purchases, the duration of visits, ad engagement, and clicks, and may link up different data sources to create a comprehensive shadow profile of your digital self.
The company was among eight Chinese tech firms placed on the U.S. entity list in October amid ongoing trade tensions. The United States alleges the companies have played a role in human rights abuses against Muslim minority groups in China. SenseTime said at the time that it strongly opposed the U.S. ban and would work with relevant authorities to resolve the situation. "We don't comment on market speculation," a SenseTime spokeswoman said. Hong Kong-headquartered SenseTime, which provides technology-based applications including, facial recognition and video analyzing and autonomous driving, says it is valued at more than $7.5 billion.
Employers engage artificial intelligence solutions amid a talent shortage. As employers grapple with a widespread labor shortage, more are turning to artificial intelligence tools in their search for qualified candidates. Hiring managers are using increasingly sophisticated AI solutions to streamline large parts of the hiring process. The tools scrape online job boards and evaluate applications to identify the best fits. They can even stage entire online interviews and scan everything from word choice to facial expressions before recommending the most qualified prospects.