OpenAI has decided that its nonprofit division will retain control over its for-profit org, after the company initially announced that it planned to convert to a for-profit organization.
Alphabet Inc. pays Samsung Electronics Co. an “enormous sum of money” every month to preinstall Google generative AI app, Gemini, on its phones and devices, according to court testimony, even though the company’s practice of paying for installations has twice been found to violate the law.
OpenAI is raising the specter of China and predicting the US will lose the AI race if it's unable to scrape copyrighted materials.
The powerful new AI model is designed to analyze intercepted communications – but experts say such systems can exacerbate biases and are prone to making mistakes
U.S. tech giants have quietly empowered Israel to track and kill many more alleged militants more quickly in Gaza and Lebanon through a sharp spike in artificial intelligence and computing services.
A researcher affiliated with Elon Musk’s xAI startup is researching a method to alter the politics of Grok and better align the chatbot with conservatives.
Why a relatively unknown Chinese-developed AI model has turned the AI industry on its head.
One of the most important AI copyright legal battles just took a major turn.
Data center emissions have tripled since 2018. As more complex AI models like OpenAI’s Sora see broad release, those figures will likely go through the roof.
This paper examines ‘open’ artificial intelligence (AI). Claims about ‘open’ AI often lack precision, frequently eliding scrutiny of substantial industry concentration in large-scale AI development and deployment, and often incorrectly applying understandings of ‘open’ imported from free and open-source software to AI systems. At present, powerful actors are seeking to shape policy using claims that ‘open’ AI is either beneficial to innovation and democracy, on the one hand, or detrimental to safety, on the other. When policy is being shaped, definitions matter. To add clarity to this debate, we examine the basis for claims of openness in AI, and offer a material analysis of what AI is and what ‘openness’ in AI can and cannot provide: examining models, data, labour, frameworks, and computational power. We highlight three main affordances of ‘open’ AI, namely transparency, reusability, and extensibility, and we observe that maximally ‘open’ AI allows some forms of oversight and experimentation on top of existing models. However, we find that openness alone does not perturb the concentration of power in AI. Just as many traditional open-source software projects were co-opted in various ways by large technology companies, we show how rhetoric around ‘open’ AI is frequently wielded in ways that exacerbate rather than reduce concentration of power in the AI sector.
Tesla's robotaxis are part of a wave of renewed enthusiasm for self-driving cars, but they will not help to solve our transport problems, writes Paris Marx.