First son Hunter Biden will be sentenced on Nov. 13, the week after the general election, after he was found guilty on charges in the criminal case focused on his purchase of a handgun in 2018. Judge Maryellen Noreika, in a court order Friday, set the sentencing date for Wednesday, Nov. 13, at 10:00 a.m. at the J. Caleb Boggs Federal Building in Wilmington, Delaware. President Biden's son will learn his fate 8 days after the 2020 presidential election. Hunter Biden was found guilty in June of making a false statement in the purchase of a gun, making a false statement related to information required to be kept by a federally licensed gun dealer, and possession of a gun by a person who is an unlawful user of or addicted to a controlled substance. He faces a total maximum prison time of 25 years for the three charges.

The growth of low-end hardware has led to a proliferation of machine learning-based services in edge applications. These applications gather contextual information about users and provide some services, such as personalized offers, through a machine learning (ML) model. A growing practice has been to deploy such ML models on the user's device to reduce latency, maintain user privacy, and minimize continuous reliance on a centralized source. However, deploying ML models on the user's edge device can leak proprietary information about the service provider. In this work, we investigate on-device ML models that are used to provide mobile services and demonstrate how simple attacks can leak proprietary information of the service provider. We show that different adversaries can easily exploit such models to maximize their profit and accomplish content theft. Motivated by the need to thwart such attacks, we present an end-to-end framework, SODA, for deploying and serving on edge devices while defending against adversarial usage. Our results demonstrate that SODA can detect adversarial usage with 89% accuracy in less than 50 queries with minimal impact on service performance, latency, and storage.

Diminished Reality (DR) is considered as the conceptual counterpart Powered by augmented and virtual reality (AR/VR), the metaverse to Augmented Reality (AR), and has recently gained increasing has materialized from the realms of science fiction in stages, and attention from both industry and academia. Unlike AR which it can be expected to be well developed by 2040 [1]. In AR, virtual adds virtual objects to the real world, DR allows users to remove objects are overlaid onto real world to augment users' perception physical content from the real world. When combined with object of the world. These virtual objects provide relevant personalized replacement technology, it presents an further exciting avenue for information according to use cases and remaining consistent with exploration within the metaverse. Although a few researches have the real world, creating an illusion of seamless blending. For example, been conducted on the intersection of object substitution and DR, the Meta-empowered advanced driver assistance system there is no real-time object substitution for mobile diminished reality (ADAS) [2] provides additional information of neighboring drivers architecture with high quality. In this paper, we propose an through multiple sources of data by displaying on the ego vehicle's end-to-end architecture to facilitate immersive and real-time scene windshield as the augmented reality based head-up display to construction for mobile devices with edge computing.

Far from the stuff of fantasy, artificial intelligence (AI) has become an integral part of our lives. Even the most tech-adverse among us use AI, perhaps unknowingly, when we type a query into Google or plug in GPS. Those who embrace technology, on the other hand, actively look for ways AI can improve their work and personal lives. Though it seems AI is a new phenomenon, the technology has been around since 1956. While AI's popularity has waxed and waned, it gained legitimacy in the 1990s and 2000s when a chess computer program beat the grand chess master Garry Kasparov and speech recognition software was installed on Windows.

Far from the stuff of fantasy, artificial intelligence (AI) has become an integral part of our lives. Even the most tech-adverse among us use AI, perhaps unknowingly, when we type a query into Google or plug in GPS. Those who embrace technology, on the other hand, actively look for ways AI can improve their work and personal lives. Though it seems AI is a new phenomenon, the technology has been around since 1956. While AI's popularity has waxed and waned, it gained legitimacy in the 1990s and 2000s when a chess computer program beat the grand chess master Garry Kasparov and speech recognition software was installed on Windows.

If you like multi-variant statistics, then you're going to love what Melissa Strong, PhD., is doing at IndiOmics, the biotechnology company she founded to gain a greater understanding on how chemicals interact with -- and possibly harm – people that come into contact with them every day. For starters, there are about 84,000 chemicals registered with the Environmental Protection Agency (EPA), according to Strong. From sunscreens and pesticides to plasticizers and hardeners, the average American contains within their body a unique chemical cocktail brewed from their specific path through this world. Factor in different genetics, medical histories, and environmental factors, and you have the sort of combinatorial explosion that is unworkable in the traditional scientific sense. "It's never only X and Y," Strong says.

As an IBM developerWorks information architect, I gave a presentation last week about cognitive computing to entrepreneurs and staffers at tekMountain, a co-working and tech incubator in Wilmington, North Carolina where I work as a tech mentor. The title is a bit tongue and cheek, but I really tried to position the Watson application development demo I gave as the "applied" part of a series that we launched in the area last year on artificial intelligence. At a previous "Exploring Artificial Intelligence" TechTalk, my buddies Mike Orr (IBM Watson University program chair) and Julian Keith (UNC Wilmington Psychology Chair and brain guy), began a series of conversations about artificial intelligence that quickly blossomed into several different AI events with different AI focuses at different venues. An upcoming talk in this very popular series (for example) is titled "Is artificial intelligence going to do my job better than me?" As a software development enthusiast who sometimes teaches kids and others how to start coding, I naturally conceived of a hands-on version of Watson services as a way to take the conversation further.

As an IBM developerWorks information architect, I gave a presentation last week about cognitive computing to entrepreneurs and staffers at tekMountain, a co-working and tech incubator in Wilmington, North Carolina where I work as a tech mentor. The title is a bit tongue and cheek, but I really tried to position the Watson application development demo I gave as the "applied" part of a series that we launched in the area last year on artificial intelligence. At a previous "Exploring Artificial Intelligence" TechTalk, my buddies Mike Orr (IBM Watson University program chair) and Julian Keith (UNC Wilmington Psychology Chair and brain guy), began a series of conversations about artificial intelligence that quickly blossomed into several different AI events with different AI focuses at different venues. An upcoming talk in this very popular series (for example) is titled "Is artificial intelligence going to do my job better than me?" As a software development enthusiast who sometimes teaches kids and others how to start coding, I naturally conceived of a hands-on version of Watson services as a way to take the conversation further.