Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems. Most recent works primarily focus on using advanced natural language processing techniques to extract semantic information from rich textual data, employing content-based methods derived from local historical news. However, this approach lacks a global perspective, failing to account for users' hidden motivations and behaviors beyond semantic information. To address this challenge, we propose a novel model called GLORY (Global-LOcal news Recommendation sYstem), which combines global representations learned from other users with local representations to enhance personalized recommendation systems. We accomplish this by constructing a Global-aware Historical News Encoder, which includes a global news graph and employs gated graph neural networks to enrich news representations, thereby fusing historical news representations by a historical news aggregator. Similarly, we extend this approach to a Global Candidate News Encoder, utilizing a global entity graph and a candidate news aggregator to enhance candidate news representation. Evaluation results on two public news datasets demonstrate that our method outperforms existing approaches. Furthermore, our model offers more diverse recommendations.

The ability of aerial robots to operate in the presence of failures is crucial in various applications that demand continuous operations, such as surveillance, monitoring, and inspection. In this paper, we propose a fault-tolerant control strategy for quadrotors that can adapt to single and dual complete rotor failures. Our approach augments a classic geometric tracking controller on $SO(3)\times\mathbb{R}^3$ to accommodate the effects of rotor failures. We provide an in-depth analysis of several attitude error metrics to identify the most appropriate design choice for fault-tolerant control strategies. To assess the effectiveness of these metrics, we evaluate trajectory tracking accuracies. Simulation results demonstrate the performance of the proposed approach.

Earlier this year, the stock-photo service provider Getty Images sued Stability AI over what Getty said was the misuse of more than 12 million Getty photos in training Stability's AI photo-generation tool, Stable Diffusion. Now Getty Images is releasing its own AI photo-generation tool, which will be available to its commercial customers. And it's bringing in the big dog to do it: Nvidia. Called simply Generative AI by Getty Images, the tool is paywalled on the Getty.com It will also be available through an API, so Getty customers can plug it into other apps.

Spotify has launched an AI system that translates popular podcasts into different languages - while maintaining the sound of the host's voices. Do the AI translations sound like the celebrity podcasters? Do the AI translations sound like the celebrity podcasters? The translation feature can transcribe English and other languages into English – but will be used to clone the speaker's voice. As part of the trial, the musical streaming giant is slowly rolling out the new feature with a small group of podcasters and translating to Spanish.

The video for "A Barely Lit Path," the first single from "Again," Daniel Lopatin's tenth album as Oneohtrix Point Never, takes place on a dark road in a shadowy forest. Two CPR dummies wearing turquoise jumpsuits are strapped into a self-driving car. On the floor, there's an artificial-intelligence manual, a book about understanding computers, and a copy of "Erewhon," the 1872 satirical novel that imagines a future in which machines achieve consciousness. The dummies play chess; they nap. Their rubbery fingers reach across the seat for each other. At some point, the road gets rough and the dummies start flopping around. A Stop button is affixed to the gearshift, but it's just out of reach. One of the dummies starts to cry.

OpenAI, developer of the ChatGPT language model, is the best-funded and largest AI platform company with over $10 billion in funding at a valuation of nearly $30 billion. Microsoft uses OpenAI, but Google, Meta, Apple and Amazon have their own AI platforms and there are hundreds of other AI startups in Silicon Valley. Will industry forces drive one of these to become a monopoly? When Google started its search business, there were already a dozen existing search platforms such as Yahoo, AltaVista, Excite and InfoSeek. Many observers asked if we need Google as yet another search engine?

The dispute has shut down many of America's top shows - popular TV series and late-night talk shows. As well as issues around pay, the writers fear the impact of artificial intelligence potentially supplanting their talents.

Hollywood's writers union says it has reached a preliminary labour agreement with the industry's major studios in a deal to end one of two strikes that have halted most film and television production for nearly five months. The Writers Guild of America (WGA) announced the deal on Sunday with the Alliance of Motion Picture and Television Producers (AMPTP), the group that represents studios, streaming services and producers in negotiations. The three-year contract agreement – agreed to after five marathon days of renewed talks by negotiators WGA and the AMPTP – must still be approved by the guild's board and members before the strike can be declared officially over. The WGA, which represents 11,500 film and television writers, described the deal as "exceptional" with "meaningful gains and protections for writers". "This was made possible by the enduring solidarity of WGA members and extraordinary support of our union siblings who joined us on the picket lines for over 146 days," the negotiating committee said in a statement.

AI-enabled tools have become sophisticated enough to allow a small number of individuals to run disinformation campaigns of an unprecedented scale. Privacy-preserving identity attestations can drastically reduce instances of impersonation and make disinformation easy to identify and potentially hinder. By understanding how identity attestations are positioned across the spectrum of decentralization, we can gain a better understanding of the costs and benefits of various attestations. In this paper, we discuss attestation types, including governmental, biometric, federated, and web of trust-based, and include examples such as e-Estonia, China's social credit system, Worldcoin, OAuth, X (formerly Twitter), Gitcoin Passport, and EAS. We believe that the most resilient systems create an identity that evolves and is connected to a network of similarly evolving identities that verify one another. In this type of system, each entity contributes its respective credibility to the attestation process, creating a larger, more comprehensive set of attestations. We believe these systems could be the best approach to authenticating identity and protecting against some of the threats to democracy that AI can pose in the hands of malicious actors. However, governments will likely attempt to mitigate these risks by implementing centralized identity authentication systems; these centralized systems could themselves pose risks to the democratic processes they are built to defend. We therefore recommend that policymakers support the development of standards-setting organizations for identity, provide legal clarity for builders of decentralized tooling, and fund research critical to effective identity authentication systems.

The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they have also introduced potential threats. One critical concern is the misuse of LLMs by disinformation spreaders, leveraging these models to generate highly persuasive yet misleading content that challenges the disinformation detection system. This work aims to address this issue by answering three research questions: (1) To what extent can the current disinformation detection technique reliably detect LLM-generated disinformation? (2) If traditional techniques prove less effective, can LLMs themself be exploited to serve as a robust defense against advanced disinformation? and, (3) Should both these strategies falter, what novel approaches can be proposed to counter this burgeoning threat effectively? A holistic exploration for the formation and detection of disinformation is conducted to foster this line of research.