Sam Altman, the CEO of artificial intelligence lab OpenAI, told a Senate panel he welcomes federal regulation on the technology'to mitigate' its risks. A class-action complaint filed Wednesday in the northern district of California alleges tech leaders OpenAI and Microsoft Corp. used "stolen and misappropriated" information from hundreds of millions of internet users without their knowledge to train and develop its artificial intelligence tech like chatbot ChatGPT. The 16 plaintiffs, who are represented by the Clarkson Law Firm and listed with initials, claimed the defendants "continue to unlawfully collect and feed additional personal data from millions" worldwide to that end and that they systematically scraped 300 billion words from the internet without consent. "Once trained on stolen data, defendants saw the immediate profit potential and rushed the products to market without implementing proper safeguards or controls to ensure that they would not produce or support harmful or malicious content and conduct that could further violate the law, infringe rights and endanger lives," Clarkson continued. "Without these safeguards, the products have already demonstrated their ability to harm humans, in real ways."

In June 2021, GitHub announced Copilot, a kind of auto-complete for computer code powered by OpenAI's text-generation technology. It provided an early glimpse of the impressive potential of generative artificial intelligence to automate valuable work. Two years on, Copilot is one of the most mature examples of how the technology can take on tasks that previously had to be done by hand. This week Github released a report, based on data from almost a million programmers paying to use Copilot, that shows how transformational generative AI coding has become. On average, they accepted the AI assistant's suggestions about 30 percent of the time, suggesting that the system is remarkably good at predicting useful code.

Chloe Smith, the Science, Innovation and Technology Secretary, told the BBC: "OpenAI's decision to expand into London as their first international office is another vote of confidence for Britain as an AI powerhouse and, in OpenAI's own words, for our vibrant technology ecosystem and exceptional talent.

OpenAI, the developer of ChatGPT, has chosen London as the location for its first international office in a boost to the UK's attempts to stay competitive in the artificial intelligence race. The San Francisco-based company behind the popular chatbot said on Wednesday that it would start its expansion outside the US in the UK capital. OpenAI said the UK office would reinforce efforts to create "safe AGI". AGI refers to artificial general intelligence, or a highly intelligent AI system that OpenAI's chief executive, Sam Altman, has described as "generally smarter than humans". "We are thrilled to extend our research and development footprint into London, a city globally renowned for its rich culture and exceptional talent pool," said Diane Yoon, OpenAI's head of human resources.

The lawsuit goes to the heart of a major unresolved question hanging over the surge in "generative" AI tools such as chatbots and image generators. The technology works by ingesting billions of words from the open internet and learning to build inferences between them. After consuming enough data, the resulting "large language models" can predict what to say in response to a prompt, giving them the ability to write poetry, have complex conversations and pass professional exams. But the humans who wrote those billions of words never signed off on having a company such as OpenAI use them for its own profit.

That credibility gap, while small, is concerning given that the problem of AI-generated disinformation seems poised to grow significantly, says Giovanni Spitale, the researcher at the University of Zurich who led the study, which appeared in Science Advances today. "The fact that AI-generated disinformation is not only cheaper and faster, but also more effective, gives me nightmares," he says. He believes that if the team repeated the study with the latest large language model from OpenAI, GPT-4, the difference would be even bigger, given how much more powerful GPT-4 is. To test our susceptibility to different types of text, the researchers chose common disinformation topics, including climate change and covid. Then they asked OpenAI's large language model GPT-3 to generate 10 true tweets and 10 false ones, and collected a random sample of both true and false tweets from Twitter.

Although Big Tech is still (sometimes clumsily) figuring out generative AI's ethics and implications, the genie is out of the bottle, and the technology is already integrating into the workforce. From that perspective, Microsoft announced a new program today to train workers on AI. The initiative will offer free coursework through LinkedIn, including certification. It's somewhat ironic since the appeal of generative AI is that it's dead simple to use: It automates content creation using everyday language. But the courses could still provide tips for composing the most effective prompts while showing beginners the ropes, giving them a chance to keep pace with our rapidly changing world.

The fundamental value of generative AI is to serve as a human "co-pilot." This might mean accelerating workers' ability to find the information they need: for example, quickly searching laws, regulations, and previous reports on a topic to locate an answer or drive new policy directions. AI tools can also help summarize meeting notes or streamline the process of drafting a standard piece of ministerial correspondence. The Government Technology Agency of Singapore (GovTech) is harnessing the power of generative AI using Microsoft Azure OpenAI service to complete these types of routine tasks. This AI-powered assistance might allow team members to branch out into practical fieldwork, interact with citizens directly, or focus on the more human and strategic aspects of their role.

Generative AI is making a big splash as it gets integrated into workplace tools like email providers, graphics editors, productivity tools and coding programs. Despite some leaders, including AI creators, warning about doomsday scenarios in which the tech takes over humanity, hundreds of thousands of Gen Z students -- those born between 1997 and 2012 -- have experimented with it, and in some cases, have even been encouraged by their schools to explore it. Now as new hires, Gen Z is bringing their AI chops to work, expediting more usage in the future. And young adults are more likely to use AI than their older counterparts at work, a recent Pew Research Center survey suggests.

When adopting a model-based formulation, solving inverse problems encountered in multiband imaging requires to define spatial and spectral regularizations. In most of the works of the literature, spectral information is extracted from the observations directly to derive data-driven spectral priors. Conversely, the choice of the spatial regularization often boils down to the use of conventional penalizations (e.g., total variation) promoting expected features of the reconstructed image (e.g., piecewise constant). In this work, we propose a generic framework able to capitalize on an auxiliary acquisition of high spatial resolution to derive tailored data-driven spatial regularizations. This approach leverages on the ability of deep learning to extract high level features. More precisely, the regularization is conceived as a deep generative network able to encode spatial semantic features contained in this auxiliary image of high spatial resolution. To illustrate the versatility of this approach, it is instantiated to conduct two particular tasks, namely multiband image fusion and multiband image inpainting. Experimental results obtained on these two tasks demonstrate the benefit of this class of informed regularizations when compared to more conventional ones.