Although extensive research has been carried out to evaluate the effectiveness of AI tools and models in detecting deep fakes, the question remains unanswered regarding whether these models can accurately identify genuine images that appear artificial. In this study, as an initial step towards addressing this issue, we have curated a dataset of 510 genuine images that exhibit a fake appearance and conducted an assessment using two AI models. We show that two models exhibited subpar performance when applied to our dataset. Additionally, our dataset can serve as a valuable tool for assessing the ability of deep learning models to comprehend complex visual stimuli. We anticipate that this research will stimulate further discussions and investigations in this area. Our dataset is accessible at https://github.com/aliborji/FLORIDA.

Graph neural networks (GNNs) encounter significant computational challenges when handling large-scale graphs, which severely restricts their efficacy across diverse applications. To address this limitation, graph condensation has emerged as a promising technique, which constructs a small synthetic graph for efficiently training GNNs while retaining performance. However, due to the topology structure among nodes, graph condensation is limited to condensing only the observed training nodes and their corresponding structure, thus lacking the ability to effectively handle the unseen data. Consequently, the original large graph is still required in the inference stage to perform message passing to inductive nodes, resulting in substantial computational demands. To overcome this issue, we propose mapping-aware graph condensation (MCond), explicitly learning the one-to-many node mapping from original nodes to synthetic nodes to seamlessly integrate new nodes into the synthetic graph for inductive representation learning. This enables direct information propagation on the synthetic graph, which is much more efficient than on the original large graph. Specifically, MCond employs an alternating optimization scheme with innovative loss terms from transductive and inductive perspectives, facilitating the mutual promotion between graph condensation and node mapping learning. Extensive experiments demonstrate the efficacy of our approach in inductive inference. On the Reddit dataset, MCond achieves up to 121.5x inference speedup and 55.9x reduction in storage requirements compared with counterparts based on the original graph.

Hideo Kojima said his documentary, Hideo Kojima: Connecting Worlds, will be distributed exclusively by Disney . The legendary game designer posted Thursday on X (formerly Twitter) that the film, which premiered at the Tribeca Film Festival this summer, will launch globally in the spring of 2024. Hideo Kojima: Connecting Worlds tracks the pioneering auteur during the development of Death Stranding while providing a rare glimpse into his creative process as he launched his studio, Kojima Productions. The film also includes "shots from the early days of our independent studio, memories from my childhood and my creative journey," as the designer said. The film strives to capture the artistic side of gaming, which Kojima embodies as well as anyone.

Sorcha O'Carroll, senior director for mergers at the CMA, said: "The invitation to comment is the first part of the CMA's information gathering process and comes in advance of launching any phase 1 investigation, which would only happen once the CMA has received the information it needs from the partnership parties."

A little more than a year ago, the world seemed to wake up to the promise and dangers of artificial intelligence when OpenAI released ChatGPT, an application that enables users to converse with a computer in a singularly human way. Within five days, the chatbot had a million users. Within two months, it was logging a hundred million monthly users--a number that has now nearly doubled. Call this the year many of us learned to communicate, create, cheat, and collaborate with robots. Shortly after ChatGPT came out, Google released its own chatbot, Bard; Microsoft incorporated OpenAI's model into its Bing search engine; Meta débuted LLaMA; and Anthropic came out with Claude, a "next generation AI assistant for your tasks, no matter the scale."

AI expert Marva Bailer explains how, even though there are currently laws in place, the average person has more access than ever to create deepfakes of celebrities. "Elvis" director Baz Luhrmann is not afraid of artificial intelligence so much as he worries about the lack of regulation over the technology. In an interview with Sky News, Luhrmann admitted he was not "personally frightened of AI, but having worked with a very, very smart robot named Ai-Da, and having formed a relationship with her, she would tell you, and I would agree, we are way behind in terms of governance of AI." Earlier this year, Luhrmann partnered with Bombay Sapphire on its "Saw This Made This" campaign, which used an AI robot artist, named Ai-Da, to create art pieces live at exhibitions in London and New York inspired by submissions from human creators. Luhrmann also praised the writers and actors strikes that took place over the summer and fall, with the use of AI being a major issue in negotiations. WHAT IS ARTIFICIAL INTELLIGENCE (AI)?

Fox News host Bret Baier has more on U.S. and its allies efforts to increase semiconductor manufacturing on'Special Report.' The world could face another chip shortage as companies and nations seek to lead the way with artificial intelligence (AI) development, having seemingly made few changes after the impacts of the 2021 supply chain crisis, experts said. "The answer is different for different segments of the semiconductor industry and the chip economy," Gregory C. Allen, the director of the Wadhwani Center for AI and Advanced Technologies for the Center for Strategic and International Studies, told Fox News Digital. "Companies that make these chips are building out additional capacity to a different extent and in different market niches," he said, adding that while the world is "headed to an oversupply of certain types of chips," there is "already a shortage" of more advanced chips, reflected in the "extraordinary cost of each of these chips." China enacted a series of extreme lockdown measures, known as "zero-COVID," to combat the coronavirus pandemic, which required cities to shut down and test every resident after officials detected just a few positive cases.

In the final moments of Stephen Spielberg's 2001 film AI: Artificial Intelligence, android boy David brings his "mother" Monica back to life for a single, bewildering day. People think this scene is sentimental, but it actually underlines the film's dark central point: David can never be a real boy, and the bizarre and cruel resurrection of Monica only reinforces his intrinsic inhumanity. This came to mind on Thursday night, as I snuck in late to Melbourne Symphony Orchestra's "concert in hologram" with legendary soprano Maria Callas. Callas died in 1977, and she appears here via "cutting-edge holographic technology", according to the program. The hologram – which uses projectors and motion capture technology to create a 3D image of Callas – interacts with the audience without speaking directly to us; she motions to conductor Daniel Schlosberg, who motions back. She pauses for applause even after any real applause has died off.

This paper addresses a UAV path planning task that seeks to observe a set of objects while satisfying the observation quality constraint. A dynamic programming algorithm is proposed that enables the UAV to observe the target objects with shortest path while subjecting to the observation quality constraint. The objects have their own facing direction and restricted observation range. With an observing order, the algorithm achieves (1+$\epsilon$)-approximation ratio in theory and runs in polynomial time. The extensive results show that the algorithm produces near-optimal solutions, the effectiveness of which is also tested and proved in the Airsim simulator, a realistic virtual environment.

We introduce a multi-modal diffusion model tailored for the bi-directional conditional generation of video and audio. Recognizing the importance of accurate alignment between video and audio events in multi-modal generation tasks, we propose a joint contrastive training loss to enhance the synchronization between visual and auditory occurrences. Our research methodology involves conducting comprehensive experiments on multiple datasets to thoroughly evaluate the efficacy of our proposed model. The assessment of generation quality and alignment performance is carried out from various angles, encompassing both objective and subjective metrics. Our findings demonstrate that the proposed model outperforms the baseline, substantiating its effectiveness and efficiency. Notably, the incorporation of the contrastive loss results in improvements in audio-visual alignment, particularly in the high-correlation video-to-audio generation task. These results indicate the potential of our proposed model as a robust solution for improving the quality and alignment of multi-modal generation, thereby contributing to the advancement of video and audio conditional generation systems.