Education and skill-building is a key priority of the AI Alliance. Already, leaders are sounding alarm about an AI skills crisis, with too few people having the skills needed to work in the field, and too few opportunities for diverse populations to gain the training and experiences they need at scale, and economies standing to lose trillions.
The AI trust and safety guide is a “living” document that provides an introduction to current trends in research and development for ensuring AI models and applications meet requirements for trustworthy results, and in particular, results that satisfy various safety criteria. Aimed at developers and leaders who are relatively new to this topic, the guide defines some common terms, provides an overview of several leading trust and safety education and technology projects, and offers recommendations for how to build-in trust and safety into your AI-based applications.
The AI Alliance application and tools working group has conducted a comprehensive study on best practices for advancing domain-specific Q&A using retrieval-augmented generation (RAG) techniques. The findings of this research, provide insights and recommendations for maximizing the capabilities of Q&A AI in specialized domains.
The era of generative AI has ushered in new challenges and risks, which have completely changed the way we think about product development. With increasingly diverse ways to evaluate models, we learn both about emergent capabilities but also about the potential harms they bring. One of the major challenges as evaluations become more esoteric is that ways to collaborate are limited for experts in various fields that also intersect in generative AI.
Ongoing progress in Artificial Intelligence (AI) holds the potential to transform science and help humanity solve complex global challenges. Recognizing the impact that research in AI is going to have on science and society at large, the Abdus Salam International Centre for Theoretical Physics (ICTP), a member of the AI Alliance, has launched a new prize for researchers in AI – the AI for Science Prize, aimed at acknowledging major contributions in this field.
On May 15, leaders across industry, academia and government gathered in Tokyo, Japan, to discuss the latest advances in AI and to explore why open technologies and open communities are essential to the successful advancement of AI.
New AI Alliance Members Include: Anaconda; Applied Digital; Citadel AI; Core42; Databricks; Domino Data Lab; ESADE, Hitachi; Institut Polytechnique De Paris; Impact AI; Kera Health Platforms; LastMile AI; Lightning AI; MLOps Community; NEC Corporation; New Native Inc.; Neo4j; Northeastern University; Predibase; SeedAI; Snowflake, Inc.; Uber; University at Buffalo; University of Pennsylvania; Interdisciplinary Centre for Artificial Intelligence and Cybersecurity @ Poznan University of Technology; University of Utah; Weights & Biases (ML/LLMops); and Zilliz
IBM and Meta Launch the AI Alliance in collaboration with over 50 Founding Members and Collaborators globally including AMD, Anyscale, CERN, Cerebras, Cleveland Clinic, Cornell University, Dartmouth, Dell Technologies, EPFL, ETH, Hugging Face, Imperial College London, Intel, INSAIT, Linux Foundation, MLCommons, MOC Alliance operated by Boston University and Harvard University, NASA, NSF, Oracle, Partnership on AI, Red Hat, Roadzen, ServiceNow, Sony Group, Stability AI, University of California Berkeley, University of Illinois, University of Notre Dame, The University of Tokyo, Yale University and others