Artificial intelligence (AI) is continually evolving, with a significant challenge being the creation of systems that can effectively collaborate in dynamic environments. One area of focus in this regard is multi-agent reinforcement learning (MARL), which aims to teach agents to interact and adapt in these settings. However, these methods struggle with complexity and adaptability, especially…
Deep learning's exceptional performance across a wide range of scientific fields and its utilization in various applications have been proven. However, these models often come with many parameters that require a substantial amount of computational power for training and testing. The improvement of these models has been a primary focus of advancement in the field,…
The realm of language models has seen tremendous growth thanks to transformative scaling efforts and applications such as OpenAI's GPT series. Innovations like Transformer-XL have broadened context windows, while models like Mistral, Falcon, Yi, DeepSeek, DBRX, and Gemini extended the reach of these capabilities. Parallel to these, visual language models (VLMs) have also observed similar…
At the Data + AI Summit 2024, Databricks unveiled the public preview of the Mosaic AI Agent Framework and Agent Evaluation, aimed at helping developers build and deploy superior Agentic and Retrieval Augmented Generation (RAG) applications on the Databricks Data Intelligence Platform.
Building quality generative AI applications pose distinct challenges for developers, such as selecting the…
Google DeepMind's AI systems AlphaProof and AlphaGeometry 2 have achieved a silver medal-level score at the 2024 International Mathematical Olympiad (IMO), a highly prestigious competition for budding mathematicians worldwide. Despite competing against 609 contestants, the AI models secured rankings among the top 58, by resolving four of the six difficult math problems, earning 28…
A recent research study by teams at Imperial College Business School, Samsung AI, and IBM has proposed an innovative solution for scientific discovery, using a framework that they call AI-Hilbert. The system is designed to discover natural laws by modeling axioms and laws as polynomials. The research leverages binary variables and logical constraints to solve…
Artificial intelligence (AI) developing systems often encounter several challenges like performing tasks that require human intellect, such as managing complex tasks and interacting with dynamic environments. This necessitates finding and synthesizing information from the web accurately and reliably. Current models face this difficulty, hence pointing out the need for more advanced AI systems. Existing solutions…
Harvard researchers have launched ReXrank, an open-source leaderboard that aims to improve artificial intelligence (AI)-powered radiology report generation. This development could revolutionize healthcare AI, especially concerning chest X-ray image interpretation. ReXrank aims to provide a comprehensive, objective evaluation framework for advanced AI models, encouraging competition and collaboration among researchers, clinicians, and AI enthusiasts and accelerating…
Harvard researchers have won the medical AI field's attention with their launch of ReXrank, an open-source leaderboard promoting the advancement of AI-driven radiology report generation, particularly in chest X-ray imaging. This unveiling implicates changes in healthcare AI and is designed to bring a transparent and full-picture evaluation framework.
ReXrank makes use of a variety of datasets…