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While AI has been a part of game development for years, generative AI’s ability to create assets for games instantly is a relatively new component. This new technology has the capacity to serve as a tool for game developers, especially those with smaller teams — and, according to the creators of Story Machine, it already is.
Generative AI is not without its critics, but Story Machine contends that its intended to work as a creative aid and help for developers, not a replacement. It’s targeted, not at large game studios, but indie developers who don’t have the programming or artistic aptitude to build all of the assets for the games themselves.
Artificial Intelligence (AI) is unarguably the most exciting field in robotics. And humanoid robots, robots resembling the human body in shape, are one of the most popular forms of AI. However, a lot of work, finances, and research are put into making these humanoid robots.
The field is already crowded with a number of companies with interesting projects, such as Boston Dynamics’ Atlas robot and Tesla’s much-hyped Optimus prototype designed to be “general purpose.”
This week, an AI Robotics startup, Figure, has unveiled Figure 1, the world’s first commercially viable general-purpose humanoid robot. The company says this humanoid will have the ability to think, learn, and interact with its environment.
Last week, Microsoft researchers announced an experimental framework to control robots and drones using the language abilities of ChatGPT, a popular AI language model created by OpenAI. Using natural language commands, ChatGPT can write special code that controls robot movements. A human then views the results and adjusts as necessary until the task gets completed successfully.
In a demonstration video, Microsoft shows robots—apparently controlled by code written by ChatGPT while following human instructions—using a robot arm to arrange blocks into a Microsoft logo, flying a drone to inspect the contents of a shelf, or finding objects using a robot with vision capabilities.
Word on the street is that GPT-4 is already done, and that the geniuses at OpenAI are secretly working on GPT-5 as we speak. That’s right; you heard it here first! But is it true? Is the next generation of language models already underway? Let’s dive in and find out.
0:00: Intro. 0:29: GPT-5 1:31: Is Bing’s AI Chatbot GPT-4? 4:13 A100 GPUs.
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Researchers have developed an AI system that can generate artificial enzymes from scratch. In laboratory experiments, some of these enzymes demonstrated efficacy comparable to natural enzymes, even when their artificially created amino acid.
Any substance that when dissolved in water, gives a pH less than 7.0, or donates a hydrogen ion.
This video was creating using multiple AI tools. Script was generated using ChatGPT, the noration voice was generated with Elevenlabs.io, background audio was generated with AudioLDM model and finally images were created with Stable Diffusion using Illuminati Diffusion v1.1 model. The script itself was a source for prompts at image generation stage.
There were still some human input. Particularly I generated several images for each part of the script and choose the most appealing ones. I did also manually combine noration with background music. But mostly it was done in a way that each part of the process might be completely automated.
John Danaher, Senior Lecturer in Law at the National University of Ireland (NUI) Galway:
“Understanding Techno-Moral Revolutions”
Talk held on August 24, 2021 for Colloquium of the Center for Humans and Machines at the Max Planck Institute for Human Development, Berlin.
It is common to use ethical norms and standards to critically evaluate and regulate the development and use of emerging technologies like AI and Robotics. Indeed, the past few years has seen something of an explosion of interest in the ethical scrutiny of technology. What this emerging field of machine ethics tends to overlook, however, is the potential to use the development of novel technologies to critically evaluate our existing ethical norms and standards. History teaches us that social morality (the set of moral beliefs and practices shared within a given society) changes over time. Technology has sometimes played a crucial role in facilitating these historical moral revolutions. How will it do so in the future? Can we provide any meaningful answers to this question? This talk will argue that we can and will outline several tools for thinking about the mechanics of technologically-mediated moral revolutions.
About the Speaker:
John Danaher is a Senior Lecturer in Law at the National University of Ireland (NUI) Galway. He is the author of Automation and Utopia (Harvard 2019), co-author of A Citizen’s Guide to AI (MIT Press 2021) and the coeditor of Robot Sex: Social and Ethical Implications (MIT Press 2017). His research focuses on the ethics and law of emerging technologies. He has published papers on the risks of advanced AI, the meaning of life and the future of work, the ethics of human enhancement, the intersection of law and neuroscience, the utility of brain-based lie detection, and the philosophy of religion. His work has appeared in The Guardian, Aeon, and The Philosophers’ Magazine.
GenAug has been developed by Meta AI and the University of Washington, which utilizes pre-trained text-to-image generative artificial intelligence models to enable imitation-based learning in practical robots. Stanford artificial intelligence researchers have proposed a method, called ATCON to drastically improve the quality of attention maps and classification performance on unseen data. Google’s new SingSong AI can generate instrumental music that complements your singing.
AI News Timestamps: 0:00 New AI Robot Tech From Meta. 2:43 Computer Vision Breakthrough From Stanford. 4:15 Masterworks Art. 6:10 Google AI Music Generator.
