The revolutionary CroissantLLM language model breaks the English-centric bias by offering robust bilingual capabilities in English and French, addressing the limitations in traditional models and the critical need for bilingual language understanding. Developed through collaboration, it sets new benchmarks in bilingual language processing, paving the way for more inclusive NLP applications and inspiring future endeavors…

The UK Government has revealed its response to AI innovation and regulation consultations. The white paper proposes a pro-innovation regulatory framework and emphasizes safety, transparency, fairness, and accountability. It aims for context-based regulations tailored to specific AI applications and contexts. The government is investing in AI skills, talent initiatives, and intellectual property protection. The UK…

The ITIF report challenges the narrative of AI’s energy consumption as overblown and emphasizes the need for accurate information. It highlights the increasing efficiency of AI models and hardware, as well as the substitution effects of AI, reducing higher carbon-emitting tasks. The report calls for energy transparency standards for AI models while cautioning against misleading…

Meta has launched new initiatives to increase transparency around AI-generated content on its platforms. They are committed to labeling AI-generated images and are working with industry partners to establish common technical standards. Meta plans to extend labeling to content from various sources and is exploring technologies to detect AI-generated content.

Microsoft partners with Semafor to help journalists utilize AI for news creation. Semafor, founded by ex-BuzzFeed and Bloomberg execs, launches “Signals” with Microsoft’s backing, aiming to deliver diverse and up-to-date perspectives on global news. The use of AI tools for news research sparks questions about objectivity and the potential for AI to eventually write stories.

Researchers at New York University trained an AI model on data from a baby’s perspective in an attempt to mimic human learning. This approach challenged conventional large data set trainings, showing promise in the AI’s ability to match words to objects. This method, inspired by how babies learn, could be key in advancing AI systems.

Recent research by EPFL and Meta introduces the Chain-of-Abstraction (CoA) reasoning method for large language models (LLMs) to enhance multi-step reasoning by efficiently leveraging tools. The method separates general reasoning from domain-specific knowledge, yielding a 7.5% average accuracy increase in mathematical reasoning and a 4.5% increase in Wiki QA, with improved inference speeds.

Researchers from The University of Texas at Austin and JPMorgan have developed a pioneering algorithm and framework for machine unlearning within image-to-image generative models. This addresses the challenge of removing specific data from AI systems without affecting model performance. The research sets a new standard for privacy-aware AI development and is crucial in the evolving…

An AI chatbot called Limbic Access has effectively increased patient referrals for mental-health services in England’s NHS, particularly among underrepresented groups. A study in Nature Medicine found that referrals rose by 15% when the chatbot was used, especially among minority groups. The chatbot efficiently screens patients and provides tailored referrals without increasing waiting times.