Using characters and scenes he generated with Dall-E, writer / director Chad Nelson and creative agency Native Foreign have made the animated short Critters, which recently debuted on YouTube. The five-minute film, which was partly financed by OpenAI and is a cross between something from Pixar and a David Attenborough-style documentary, we meet a cast of cute, furry creatures who live in an imaginary jungle. While the assets were generated using AI, Chad wrote the script himself. He used actors to record the voices and the film was made together with a team of animators. His son also worked on the film, as an Unreal Engine programmer.

Google's chief executive has said concerns about artificial intelligence keep him awake at night and that the technology can be "very harmful" if deployed wrongly. Sundar Pichai also called for a global regulatory framework for AI similar to the treaties used to regulate nuclear arms use, as he warned that the competition to produce advances in the technology could lead to concerns about safety being pushed aside. In an interview on CBS's 60 minutes programme, Pichai said the negative side to AI gave him restless nights. "It can be very harmful if deployed wrongly and we don't have all the answers there yet – and the technology is moving fast. So does that keep me up at night? Google's parent, Alphabet, owns the UK-based AI company DeepMind and has launched an AI-powered chatbot, Bard, in response to ChatGPT, a chatbot developed by the US tech firm OpenAI, which has become a phenomenon since its release in November. Pichai said governments would need to figure out global frameworks for regulating AI as it developed. Last month thousands of artificial intelligence experts, researchers and backers – including the Twitter owner Elon Musk – signed a letter calling for a pause in the creation of "giant" AIs for at least six months, amid concerns that development of the technology could get out of control. Asked if nuclear arms-style frameworks could be needed, Pichai said: "We would need that." The AI technology behind ChatGPT and Bard, known as a Large Language Model, is trained on a vast trove of data taken from the internet and is able to produce plausible responses to prompts from users in a range of formats, from poems to academic essays and software coding. The image-generating equivalent, in systems such as Dall-E and Midjourney, has also triggered a mixture of astonishment and alarm by producing realistic images such as the Pope sporting a puffer jacket. Pichai added that AI could cause harm through its ability to produce disinformation "It will be possible with AI to create, you know, a video easily.

The new video-generation systems could speed the work of moviemakers and other digital artists, while becoming a new and quick way to create hard-to-detect online misinformation, making it even harder to tell what's real on the internet. The systems are examples of what is known as generative A.I., which can instantly create text, images and sounds. Another example is ChatGPT, the online chatbot made by a San Francisco start-up, OpenAI, that stunned the tech industry with its abilities late last year. Google and Meta, Facebook's parent company, unveiled the first video-generation systems last year, but did not share them with the public because they were worried that the systems could eventually be used to spread disinformation with newfound speed and efficiency. But Runway's chief executive, Cristóbal Valenzuela, said he believed the technology was too important to keep in a research lab, despite its risks.

There's some controversy in the photography world as an AI-generated image won a major prize at a prestigious competition, PetaPixel has reported. An piece called The Electrician by Boris Eldagsen took first prize in the Creative category at the World Photography Organization's Sony World Photography Awards -- despite not being taken by a camera. Eldagsen subsequently refused the award, saying "AI is not photography. I applied... to find out if the competitions are prepared for AI images to enter. Eldagsen's image is part of a series called PSEUDOMNESIA: Fake Memories, designed to evoke a photographic style of the 1940s. However, they are in reality "fake memories of a past, that never existed, that no one photographed.

'The Big Sunday Show' highlights Elon Musk's upcoming interview with Tucker Carlson warning about the dangers of A.I.. Twitter CEO Elon Musk raised concerns of bias in artificial intelligence (A.I.), saying leftist programmers can use it to "lie" and "comment on some things but not others." "What's happening is they're training the A.I. to lie. It's bad," he said in a preview of his interview with "Tucker Carlson Tonight." "A.I. is more dangerous than, say, mismanaged aircraft design or production maintenance or bad car production," he explained. "In the sense that it has the potential, however, small one may regard that probability, but it is non-trivial, it has the potential of civilization destruction."

Insider plans to begin experimenting with ways to leverage AI in its journalism, its global editor-in-chief Nicholas Carlson told Axios. Why it matters: "A tsunami is coming," Carlson said. "We can either ride it or get wiped out by it." Details: The company will set up a working group first to test ways to responsibly incorporate AI into its workflow before rolling out a set of AI rules and best practices to the broader newsroom. The rest of the newsroom will be encouraged to use AI to generate outlines for stories, fix typos, craft headlines optimized for search engines, and prep interview questions.

Instruction tuning enables language models to generalize more effectively and better follow user intent. However, obtaining instruction data can be costly and challenging. Prior works employ methods such as expensive human annotation, crowd-sourced datasets with alignment issues, or generating noisy examples via LLMs. We introduce the LongForm dataset, which is created by leveraging English corpus examples with augmented instructions. We select a diverse set of human-written documents from existing corpora such as C4 and Wikipedia and generate instructions for the given documents via LLMs. This approach provides a cheaper and cleaner instruction-tuning dataset and one suitable for long text generation. We finetune T5, OPT, and LLaMA models on our dataset and show that even smaller LongForm models have good generalization capabilities for text generation. Our models outperform 10x larger language models without instruction tuning on various tasks such as story/recipe generation and long-form question answering. Moreover, LongForm models outperform prior instruction-tuned models such as FLAN-T5 and Alpaca by a large margin. Finally, our models can effectively follow and answer multilingual instructions; we demonstrate this for news generation. We publicly release our data and models: https://github.com/akoksal/LongForm.

Having a computer do the work for you has become more and more common over time. But in the entertainment area, where a human is a creator, we want to avoid having too much influence on technology. On the other hand, inspiration is still important; we developed a virtual conductor that can generate an emotionally associated interpretation of known music work. This was done by surveying a set number of people to determine, which emotions were associated with a specific interpretation and instruments. As a result of machine learning this conductor was then able to achieve his goal. Unlike earlier studies of virtual conductors, which would replace the role of a human conductor, this new one is supposed to be an assisting tool for conductors. As a result, starting on a new interpretation will be easier because it streamlines research time and provides a technical perspective that can inspire new ideas. By using this technology as a supplement to human creativity, we can create richer, more nuanced interpretations of musical works.

The recent advances of AI technology, particularly in AI-Generated Content (AIGC), have enabled everyone to easily generate beautiful paintings with simple text description. With the stunning quality of AI paintings, it is widely questioned whether there still exists difference between human and AI paintings and whether human artists will be replaced by AI. To answer these questions, we develop a computational framework combining neural latent space and aesthetics features with visual analytics to investigate the difference between human and AI paintings. First, with categorical comparison of human and AI painting collections, we find that AI artworks show distributional difference from human artworks in both latent space and some aesthetic features like strokes and sharpness, while in other aesthetic features like color and composition there is less difference. Second, with individual artist analysis of Picasso, we show human artists' strength in evolving new styles compared to AI. Our findings provide concrete evidence for the existing discrepancies between human and AI paintings and further suggest improvements of AI art with more consideration of aesthetics and human artists' involvement.

One exception to that is investment in artificial intelligence. Deloitte found that an overwhelming majority of CFOs expect to see significant growth in spending on AI over the next five years but were divided on whether that would lead to an increase or decrease in the number of employees.