Abductive reasoning is the process of making educated guesses to provide explanations for observations. Although many applications require the use of knowledge for explanations, the utilization of abductive reasoning in conjunction with structured knowledge, such as a knowledge graph, remains largely unexplored. To fill this gap, this paper introduces the task of complex logical hypothesis generation, as an initial step towards abductive logical reasoning with KG. In this task, we aim to generate a complex logical hypothesis so that it can explain a set of observations. We find that the supervised trained generative model can generate logical hypotheses that are structurally closer to the reference hypothesis. However, when generalized to unseen observations, this training objective does not guarantee better hypothesis generation. To address this, we introduce the Reinforcement Learning from Knowledge Graph (RLF-KG) method, which minimizes differences between observations and conclusions drawn from generated hypotheses according to the KG. Experiments show that, with RLF-KG's assistance, the generated hypotheses provide better explanations, and achieve state-of-the-art results on three widely used KGs.

Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It serves as a fundamental methodology in the field of Artificial General Intelligence (AGI). With the ongoing development of foundation models, e.g., Large Language Models (LLMs), there is a growing interest in exploring their abilities in reasoning tasks. In this paper, we introduce seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks. We then delve into the potential future directions behind the emergence of reasoning abilities within foundation models. We also discuss the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning. By discussing these future research directions, we hope to inspire researchers in their exploration of this field, stimulate further advancements in reasoning with foundation models, and contribute to the development of AGI.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Think of AI as a digital Swiss Army Knife. It sounds overwhelming if you've never tried ChatGPT, Bard or any other big options. Trust me when I say if you can use Google, you can use AI.

In some ways, it already has - Baltimore union denies school principal went on'ungrateful Black kids' rant, calls it an AI fraud FORMIDABLE WARRIORS: Ukraine's artificial intelligence (AI) development continues at a frightening pace beyond that of even tech giants in the U.S. and China as the war with Russia lurches toward a third year, but experts highlighted America's critical role in helping that rapid advance. VICTOR-AI SECRET: Victoria's Secret & Co. and Google Cloud announced a multi-year partnership that will allow the popular retailer to use Google's artificial intelligence technology to create a personalized shopping experience. TECH THREATS: Concerns about AI interfering with the 2024 elections are well-founded, yet not unprecedented in recent history. In 1975, the Asilomar Conference on Recombinant DNA foreshadowed today's AI concerns. Generative AI tools can help job seekers make their resumes and applications more visual, as well as getting ideas for content.

In some ways, it already has - Experts highlight American role in Ukraine's unbelievable AI military development - Baltimore union denies school principal went on'ungrateful Black kids' rant, calls it an AI fraud ROBOT IQ: The rapid development of artificial intelligence has led some to fear dangerous scenarios where the technology is smarter than the humans who created it, but some experts believe AI has already reached that point in certain ways. FORMIDABLE WARRIORS: Ukraine's artificial intelligence (AI) development continues at a frightening pace beyond that of even tech giants in the U.S. and China as the war with Russia lurches toward a third year, but experts highlighted America's critical role in helping that rapid advance. RUSH TO JUDGMENT?: A Baltimore, Maryland school district has launched an investigation after a high school principal was allegedly recorded making racist comments to students and staff. And AI is being blamed. Baltimore County Public Schools said it launched an internal investigation after an audio recording claiming to capture the principal of Pikesville High School making offensive comments circulated online.

As media companies haggle licensing deals with artificial intelligence powerhouses like OpenAI that are hungry for training data, they're also throwing up a digital blockade. New data shows that over 88 percent of top-ranked news outlets in the US now block web crawlers used by artificial intelligence companies to collect training data for chatbots and other AI projects. One sector of the news business is a glaring outlier, though: Right-wing media lags far behind their liberal counterparts when it comes to bot-blocking. Data collected in mid-January on about 40 top news sites by Ontario-based AI detection startup Originality AI shows that almost all of them block AI web crawlers, including newspapers like The New York Times, The Washington Post, and The Guardian, general-interest magazines like The Atlantic, and special-interest sites like Bleacher Report. But none of the top right-wing news outlets surveyed, including Fox News, the Daily Caller, and Breitbart, block any of the most prominent AI web scrapers, which also include Google's AI data collection bot.

The rapid advance of artificial intelligence technology has raised concerns about eliminating jobs held by humans. Professional photography is now coming into focus as one such potential casualty. "The rapid advancements in AI and image processing are transforming photography from a skill-based art to one that is increasingly technology-driven. This evolution is making high-quality photography accessible to a broader audience, challenging the traditional notion of professional photography as a skill," according to a report published Tuesday by Medium. "As we move further into this AI-driven era, it becomes evident that the role and relevance of professional photography skills, as we have known them, are becoming obsolete."

They present new challenges to contextual confidence, disrupting participants' ability to identify the authentic context of communication and their ability to protect communication from reuse and recombination outside its intended context. In this paper, we describe strategies - tools, technologies and policies - that aim to stabilize communication in the face of these challenges. The strategies we discuss fall into two broad categories. Containment strategies aim to reassert context in environments where it is currently threatened - a reaction to the context-free expectations and norms established by the internet. Mobilization strategies, by contrast, view the rise of generative AI as an opportunity to proactively set new and higher expectations around privacy and authenticity in mediated communication.

Large Language Model (LLM) alignment aims to ensure that LLM outputs match with human values. Researchers have demonstrated the severity of alignment problems with a large spectrum of jailbreak techniques that can induce LLMs to produce malicious content during conversations. Finding the corresponding jailbreaking prompts usually requires substantial human intelligence or computation resources. In this paper, we report that LLMs have different levels of alignment in various contexts. As such, by systematically constructing many contexts, called worlds, leveraging a Domain Specific Language describing possible worlds (e.g., time, location, characters, actions and languages) and the corresponding compiler, we can cost-effectively expose latent alignment issues. Given the low cost of our method, we are able to conduct a large scale study regarding LLM alignment issues in different worlds. Our results show that our method outperforms the-state-of-the-art jailbreaking techniques on both effectiveness and efficiency. In addition, our results indicate that existing LLMs are extremely vulnerable to nesting worlds and programming language worlds. They imply that existing alignment training focuses on the real-world and is lacking in various (virtual) worlds where LLMs can be exploited.

Image generation using generative AI is rapidly becoming a major new source of visual media, with billions of AI generated images created using diffusion models such as Stable Diffusion and Midjourney over the last few years. In this paper we collect and analyse over 3 million prompts and the images they generate. Using natural language processing, topic analysis and visualisation methods we aim to understand collectively how people are using text prompts, the impact of these systems on artists, and more broadly on the visual cultures they promote. Our study shows that prompting focuses largely on surface aesthetics, reinforcing cultural norms, popular conventional representations and imagery. We also find that many users focus on popular topics (such as making colouring books, fantasy art, or Christmas cards), suggesting that the dominant use for the systems analysed is recreational rather than artistic.