U.S. seeking transfer of intellectual property rights in drone deal, Kyiv says Through a combination of new technology and tactics, Kyiv's forces have been able to strike deep into Russian territory, to slow and in some cases even reverse battlefield gains by Moscow's bigger army and inflict significant damage on oil facilities that help finance the Kremlin's war machine. Kyiv has said that the U.S. is seeking the transfer of technology and access to intellectual property rights from Ukraine as part of a drone deal that is awaiting approval at the highest political level, a person familiar with the matter has said. The U.S. Department of Defense has asked to test a range of Ukrainian defense products, including drones and electronic warfare systems, as Washington is considering their potential purchase for military use, the official said. The agreement has not been finalized, the person added, speaking on condition of anonymity because the discussions are private. Growing interest from the U.S. shows how the world's largest military is looking to tap into the drone expertise Ukraine has acquired over four years fighting against the Russian invasion.

When OpenAI's new voice assistant said it was "doing fantastic" in a launch demo this month, Scarlett Johansson was not. The Hollywood star said she was "shocked, angered and in disbelief" that the updated version of ChatGPT, which can listen to spoken prompts and respond verbally, had a voice "eerily similar" to hers. One of Johansson's signature roles was as the voice of a futuristic version of Siri in the 2013 film Her and, for the actor, the similarity was stark. The OpenAI chief executive, Sam Altman, appeared to acknowledge the film's influence with a one-word post on X on the day of the launch: "her". In a statement, Johansson said Altman had approached her last year to be a voice of ChatGPT and that she had declined for "personal reasons".

The advent of Generative AI, particularly through Large Language Models (LLMs) like ChatGPT and its successors, marks a paradigm shift in the AI landscape. Advanced LLMs exhibit multimodality, handling diverse data formats, thereby broadening their application scope. However, the complexity and emergent autonomy of these models introduce challenges in predictability and legal compliance. This paper delves into the legal and regulatory implications of Generative AI and LLMs in the European Union context, analyzing aspects of liability, privacy, intellectual property, and cybersecurity. It critically examines the adequacy of the existing and proposed EU legislation, including the Artificial Intelligence Act (AIA) draft, in addressing the unique challenges posed by Generative AI in general and LLMs in particular. The paper identifies potential gaps and shortcomings in the legislative framework and proposes recommendations to ensure the safe and compliant deployment of generative models, ensuring they align with the EU's evolving digital landscape and legal standards.

The rapidity with which generative AI has been adopted and advanced has raised legal and ethical questions related to the impact on artists rights, content production, data collection, privacy, accuracy of information, and intellectual property rights. Recent administrative and case law challenges have shown that generative AI software systems do not have independent intellectual property rights in the content that they generate. It remains to be seen whether human content creators can retain their intellectual property rights against generative AI software, its developers, operators, and owners for the misappropriation of the work of human creatives, given the metes and bounds of existing law. Early signs from various courts are mixed as to whether and to what degree the results generated by AI models meet the legal standards of infringement under existing law.

Google announced on Thursday that it will protect its generative AI customers against any intellectual property claims made on the data used or output served by Google-hosted AI models. By extending protection in its cloud and workspace environments, Google joins the list of technology firms that have recently announced IP support for using their own generative AI tools. These include companies like IBM, Microsoft, Amazon, and Adobe. Google said the protection would span across all Google environments using the Duet AI collaborator, and the company's homegrown generative AI engine Vertex AI. The indemnity clause by leading technology companies will likely bring in hope as generative AI's challenges over privacy, security, and intellectual property violations peak.

The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable greater study of this question, we present LegalBench: a collaboratively constructed legal reasoning benchmark consisting of 162 tasks covering six different types of legal reasoning. LegalBench was built through an interdisciplinary process, in which we collected tasks designed and hand-crafted by legal professionals. Because these subject matter experts took a leading role in construction, tasks either measure legal reasoning capabilities that are practically useful, or measure reasoning skills that lawyers find interesting. To enable cross-disciplinary conversations about LLMs in the law, we additionally show how popular legal frameworks for describing legal reasoning -- which distinguish between its many forms -- correspond to LegalBench tasks, thus giving lawyers and LLM developers a common vocabulary. This paper describes LegalBench, presents an empirical evaluation of 20 open-source and commercial LLMs, and illustrates the types of research explorations LegalBench enables.

Generative Artificial Intelligence (GAI) has made outstanding strides in recent years, with a good-sized impact on software product management. Drawing on pertinent articles from 2016 to 2023, this systematic literature evaluation reveals generative AI's potential applications, benefits, and constraints in this area. The study shows that technology can assist in idea generation, market research, customer insights, product requirements engineering, and product development. It can help reduce development time and costs through automatic code generation, customer feedback analysis, and more. However, the technology's accuracy, reliability, and ethical consideration persist. Ultimately, generative AI's practical application can significantly improve software product management activities, leading to more efficient use of resources, better product outcomes, and improved end-user experiences.

The fuss around artificial intelligence(AI) has recently been the bone of contention. In fact, AI is disrupting virtually all sectors. Imagine if we get to a point where AI does all your tasks for you. And you'd ask–what would be left for me to do? Sure, you'd still have to feed yourself and, perhaps, take your bath yourself. Who assigns those to AI? We're at such an exciting point in the world, and one of the generative AI tools making rounds recently is ChatGPT.