Generative AI, which can create text and chat with users, presents a unique challenge because it can make people feel like they're interacting with a human. Anthropomorphism is the ascription of human attributes or personality to nonhumans. People often anthropomorphize artificial intelligence (especially Generative AI) because it can create human-like outputs. Among them, information transmission activities based on artificial intelligence technology have received more and more attention. With the help of artificial intelligence technology to obtain information and transmit information, it can be more convenient and accelerate the realization of information interaction, industry marketing, user interaction, brand publicity, and advertising, and create more creative content. Artificial intelligence technology has brought great changes and more availability to everyone's daily life and receiving information channels. However, the collection of personal data is more and more extensive, which also makes the problem of personal data privacy and security more serious. Therefore, combined with the double-sided nature of artificial intelligence, this paper analyzes the advantages and disadvantages of intelligent data processing in personal data privacy, applies the machine learning differential privacy algorithm combined with intelligent data processing to the research, and realizes the risk prediction and protection of personal data. This serves as a reminder for everyone on how to use artificial intelligence to protect their information security more effectively."

Generative AI image models may inadvertently generate problematic representations of people. Past research has noted that millions of users engage daily across the world with these models and that the models, including through problematic representations of people, have the potential to compound and accelerate real-world discrimination and other harms (Bianchi et al, 2023). In this paper, we focus on addressing the generation of problematic associations between demographic groups and semantic concepts that may reflect and reinforce negative narratives embedded in social data. Building on sociological literature (Blumer, 1958) and mapping representations to model behaviors, we have developed a taxonomy to study problematic associations in image generation models. We explore the effectiveness of fine tuning at the model level as a method to address these associations, identifying a potential reduction in visual quality as a limitation of traditional fine tuning. We also propose a new methodology with twice-human-in-the-loop (T-HITL) that promises improvements in both reducing problematic associations and also maintaining visual quality. We demonstrate the effectiveness of T-HITL by providing evidence of three problematic associations addressed by T-HITL at the model level. Our contributions to scholarship are two-fold. By defining problematic associations in the context of machine learning models and generative AI, we introduce a conceptual and technical taxonomy for addressing some of these associations. Finally, we provide a method, T-HITL, that addresses these associations and simultaneously maintains visual quality of image model generations. This mitigation need not be a tradeoff, but rather an enhancement.

Generative Artificial Intelligence (AI) has shown tremendous prospects in all aspects of technology, including design. However, due to its heavy demand on resources, it is usually trained on large computing infrastructure and often made available as a cloud-based service. In this position paper, we consider the potential, challenges, and promising approaches for generative AI for design on the edge, i.e., in resource-constrained settings where memory, compute, energy (battery) and network connectivity may be limited. Adapting generative AI for such settings involves overcoming significant hurdles, primarily in how to streamline complex models to function efficiently in low-resource environments. This necessitates innovative approaches in model compression, efficient algorithmic design, and perhaps even leveraging edge computing. The objective is to harness the power of generative AI in creating bespoke solutions for design problems, such as medical interventions, farm equipment maintenance, and educational material design, tailored to the unique constraints and needs of remote areas. These efforts could democratize access to advanced technology and foster sustainable development, ensuring universal accessibility and environmental consideration of AI-driven design benefits.

"First text, then images, now OpenAI has a model for generating videos," screamed Mashable the other day. The makers of ChatGPT and Dall-E had just announced Sora, a text-to-video diffusion model. Cue excited commentary all over the web about what will doubtless become known as T2V, covering the usual spectrum – from "Does this mark the end of [insert threatened activity here]?" to "meh" and everything in between. Sora (the name is Japanese for "sky") is not the first T2V tool, but it looks more sophisticated than earlier efforts like Meta's Make-a-Video AI. It can turn a brief text description into a detailed, high-definition film clip up to a minute long.

Jeff Bezos, Nvidia and other big technology names are investing in a business that's developing human-like robots, according to people with knowledge of the situation, part of a scramble to find new applications for artificial intelligence. The startup Figure AI -- also backed by OpenAI and Microsoft -- is raising about 675 million in a funding round that carries a pre-money valuation of roughly 2 billion, said the people, who asked not to be identified because the matter is private. Through his firm Explore Investments, Bezos has committed 100 million. Microsoft is investing 95 million, while Nvidia and an Amazon.com-affiliated Robots have emerged as a critical new frontier for the AI industry, letting it apply cutting-edge technology to real-world tasks.

Imagine you are at a crossroads in a complex project and you need quick answers on how to grapple with a problem. It is quite likely that you might turn to an online knowledge community for answers, one hosted by your company, or perhaps Stack Overflow, Quora, or Reddit. These communities have come to play a central role in knowledge exchange, in many corners of the economy and society, but they depend on voluntary participation from users just like you and me. Our recent research indicates an intriguing shift is now taking place: generative AI technologies, such as OpenAI's large language model (LLM) ChatGPT, are disrupting the status quo. Increasingly, users are gravitating toward these new AI tools to obtain answers, bypassing traditional knowledge communities.

In late October, the Office received approximately 10,000 comments in response to the NOI questions. The Office expects to publish a report in 2024 offering its perspective on how these questions should be answered and perhaps recommending legislation.

Investor excitement over artificial intelligence reached a new peak this week when better-than-expected results from chipmaker Nvidia drove stock markets in three continents to record highs. The rally began on Thursday and continued into Friday, as Nvidia overtook Google's parent group, Alphabet, to become the third most valuable company in the US. Its market capitalisation hit 2tn ( 1.58tn), surpassed only by Microsoft and Apple. The artificial intelligence (AI) boom has raised many questions, not least over safety and the impact on jobs, but there are also concerns that it might be driving unsustainable market exuberance. Here we look at the latest share price rise and whether it can be maintained.

Tyler Perry has paused an 800m ( 630m) expansion of his Atlanta studio complex after the release of OpenAI's video generator Sora and warned that "a lot of jobs" in the film industry will be lost to artificial intelligence. The US film and TV mogul said he was in the process of adding 12 sound stages to his studio but has halted those plans indefinitely after he saw demonstrations of Sora and its "shocking" capabilities. "All of that is currently and indefinitely on hold because of Sora and what I'm seeing," Perry said in an interview with the Hollywood Reporter. "I had gotten word over the last year or so that this was coming, but I had no idea until I saw recently the demonstrations of what it's able to do. The AI tool was launched on 15 February – with limited access to a few researchers and video creators – and caused widespread astonishment with its ability to produce realistic footage a minute long from simple text prompts. Perry, whose successes include the Madea film series, said Sora's achievements meant he would no longer have to travel to locations or build a set: "I can sit in an office and do this with a computer, which is shocking to me." Demonstrations released by OpenAI, the developer of the groundbreaking ChatGPT chatbot, show photorealistic scenes in response to prompts such as asking for a shot of people walking through "beautiful, snowy Tokyo city" where "gorgeous sakura petals are flying through the wind along with snowflakes". Sora can create videos of up to 60 seconds featuring highly detailed scenes, complex camera motion, and multiple characters with vibrant emotions. Perry said the breakthroughs presented by Sora would affect a range of jobs throughout the film industry, including those of actors, editors, sound specialists and transportation crew. He said: "I am very, very concerned that in the near future, a lot of jobs are going to be lost.

Microsoft has announced a generative-AI powered eraser for pictures, which gives you an easy way of removing unwanted elements from your photos. Windows Photos has long had a Spot Fix tool that can remove parts of an image for you, but the company says Generative erase is an enhanced version of the feature. Apparently, this newer tool can create "more seamless and realistic" results even when large objects, such as bystanders or clutter in the background, are removed from an image. If you'll recall, both Google and Samsung have their own versions of AI eraser tools on their mobile devices. Google's used to be exclusively available on newer Pixel phones until it was rolled out to older models.