This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs). We construct a benchmark, SafeEdit, which covers nine unsafe categories with various powerful attack prompts and equips comprehensive metrics for systematic evaluation. We conduct experiments with several knowledge editing approaches, indicating that knowledge editing has the potential to detoxify LLMs with a limited impact on general performance efficiently. Then, we propose a simple yet effective baseline, dubbed Detoxifying with Intraoperative Neural Monitoring (DINM), to diminish the toxicity of LLMs within a few tuning steps via only one instance. We further provide an in-depth analysis of the internal mechanism for various detoxifying approaches, demonstrating that previous methods like SFT and DPO may merely suppress the activations of toxic parameters, while DINM mitigates the toxicity of the toxic parameters to a certain extent, making permanent adjustments. We hope that these insights could shed light on future work of developing detoxifying approaches and the underlying knowledge mechanisms of LLMs. Code and benchmark are available at https://github.com/zjunlp/EasyEdit.

OpenAI – one of the world's leading artificial intelligence research laboratories – released the text generator ChatGPT and the image generator DALL-E 2. While both programmes represent monumental leaps in natural language processing and image generation, they've also been met with apprehension. Some critics have eulogised the college essay, while others have even proclaimed the death of art. But to what extent does this technology really interfere with creativity? After all, for the technology to generate an image or essay, a human still has to describe the task to be completed. The better that description – the more accurate, the more detailed – the better the results. After a result is generated, some further human tweaking and feedback may be needed – touching up the art, editing the text or asking the technology to create a new draft in response to revised specifications.

Where will we draw the line between human-generated art and AI-generated art? If so, should we bestow the acclaimed title of artisan upon said AI? Let's unpack things and see where the world stands on these mind-bending concerns. A crucial undercurrent has to do with AI Ethics and how we as a society perceive and want to make use of AI. For my ongoing and extensive coverage of AI Ethics and Ethical AI, see the link here and the link here, just to name a few. News stories this past few days have made AI and art an extremely hot topic. You see, the whole conundrum about Artificial Intelligence and art was recently thrust into the public eye when an AI "artbot" seemingly won an art contest. The headlines regarding this matter have ranged from fervent outrage to a sense of sorrowful acquiescence that it was only a matter of time before AI would prevail in the creative field of artistry. Some even claim that we've already seen AI comeuppance in art and that there is nothing new in this latest occurrence other than it managed to touch a nerve on social media. Amid all the heated debate in general, there are a lot of facts about this latest incident that muddy the waters and tend to undercut the shallow headlines and vitriolic tweets that the story has generated. It might be useful to take a moment and calmly consider the actual specifics, which I will be doing throughout this discussion. Meanwhile, one perhaps beneficial outcome of the reported story is that AI Ethics managed to suddenly get some long overdue recognition in the media at large. Whenever an AI-themed man-bites-dog story hits the airwaves and goes viral on social media, public opinions start to weigh in. We will examine the various qualms and complaints expressed in the public discourse about this brewing AI Ethics riddle. First, let's lay out the facts of the deemed newsworthy snowball that ultimately started a cantankerous snowfall avalanche. The Colorado State Fair is where the competition in this case took place. The Fair is an annual event that has a hearty 150-year-old tradition initially focused on livestock. An eventual expansion of activities included the inclusion of a fine arts contest.

Each art piece begins with some hand draw input to help setting up the overall scene of the image. Some images are generated using computer programming. The finished art piece is achieved by using AI to enhance the final look of the piece. The total number of pieces will be 999 covering different themes.

This art piece was one of the finest examples of art generated using IBM Quantum Computers here at Quantum Computing UK! We then took the image and trained it on an Quantum Adversarial Neural Network using IBM quantum hardware. This added the wonderful colours and patterns.

Nowadays, technological advances have influenced all human activities, creating new dynamics and ways of communication. In this context, some artists have incorporated these advances in their creative process, giving rise to unique aesthetic expressions referred to in the literature as Generative Art, which is characterized by assigning part of the creative process to a system that acts with certain autonomy (Galanter, 2003). This research work introduces a computational system for creating generative art using a Brain-Computer Interface (BCI) which portrays the user's brain activity in a digital artwork. In this way, the user takes an active role in the creative process. In aims of showing that the proposed system materializes in an artistic piece the user's mental states by means of a visual and sound representation, several tests are carried out to ensure the reliability of the BCI device sent data. The generated artwork uses brain signals and concepts of geometry, color and spatial location to give complexity to the autonomous construction. As an added value, the visual and auditory production is accompanied by an olfactory and kinesthetic component which complements the art pieces providing a multimodal communication character.

In 2018, a neural network bested the human in a reading comprehension test. The machine was able to answer over 100,000 questions from the Stanford Question Answering Dataset. It read over 500 Wikipedia articles and beat a human by 0.136 points. They are obviously better and quicker at analysing massive arrays of data, and they are keen on spotting the subtle differences and details. Our brain is still credited with the largest number of neurons, far exceeding any AI.

Almost two years ago, an unusual case shook the art world. Art theft and forgery are not uncommon but claiming an exhibited art piece to be "Fake" definitely induce disorder. The issue arose when in a German public collection, a painting thought to be made by artist Kazimir Malevich in 1915 was labeled as counterfeit and a judicial trial was held to seek the truth. Some witnessed and art experts said that it was original enough and "could hang in Stedelijk" while some stated to the authorities that such works were terribly "awful imitations". A similar case in 2018, led to the closure of the Ghent Museum of Fine Art in Belgium after some of the artwork raised suspicion among the critics and as a result, the director of the museum was suspended.

Science and art intermingle as artist Anna Ridler's work displays digital tulips and drawings made by specially modified algorithms in the Robert L. Ringel Gallery in Stewart Center. Ridler's art collects data and generates data sets to create unique narratives, according to information displayed in the gallery. One side of the gallery displays blooming digital tulips created through artificial intelligence. For one of her pieces, she created "Bloemenveiling," a website to auction her digital tulips. Reflecting the Tulip Mania of 17-century Holland, Ridler's auction serves as a digital representation of the interaction between humans, technology and economic markets.

An artist taught Google Assistant how to fire gun, creating an art piece that may further increase concerns on whether artificial intelligence is dangerous. While it may still be very far from the human-killing cyborgs from science fiction movies, Google Assistant firing a gun upon a voice command may already be a very scary thought for opponents of artificial intelligence. Alexander Reben, in a video that he uploaded to YouTube, showed his latest work. "OK Google, activate gun," Reben said, prompting a response of "Sure, turning on the gun" from Google Assistant. Following the voice command issued by Reben, the gun fires at the apple in front of it.