Ai For Research And Scalable Efficient Systems
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AI for Research and Scalable, Efficient Systems
This book constitutes the proceedings of the Second International Workshop, AI4Research 2025, and First International Workshop, SEAS 2025, which were held in conjunction with AAAI 2025, Philadelphia, PA, USA, during February 25–March 4, 2025. AI4Research 2025 presented 8 full papers from 35 submissions. The papers covered diverse areas such as agent debate evaluation, taxonomy expansion, hypothesis generation, AI4Research benchmarks, caption generation, drug discovery, and financial auditing. SEAS 2025 accepted 7 full papers from 17 submissions. These papers explore the efficiency and scalability of AI models.
Scalable Artificial Intelligence for Healthcare
This edited volume examines the transformative impact of AI technologies on global healthcare systems, with a focus on enhancing efficiency and accessibility. The content provides a comprehensive exploration of the principles and practices required to scale AI applications in healthcare, addressing areas such as diagnosis, treatment, and patient care. Key topics include data scalability, model deployment, and infrastructure design, highlighting the use of microservices, containerization, cloud computing, and big data technologies in building scalable AI systems. Discussions cover advancements in machine learning models, distributed processing, and transfer learning, alongside critical considerations such as continuous integration, data privacy, and ethics. Real-world case studies depict both the successes and challenges of implementing scalable AI across various healthcare environments, offering valuable insights for future advancements. This volume serves as a practical and theoretical guide for healthcare professionals, AI researchers, and technology enthusiasts seeking to develop or expand on AI-driven healthcare solutions to address global health challenges effectively.
Successful AI Product Creation
The Essential Guide to AI and Generative AI Product Creation from a Veteran AI Leader and Educator In Successful AI Product Creation: A 9-Step Framework, AI product leader, professor of product management and AI, and industry expert, Prof. Shub Agarwal delivers the ultimate playbook—a comprehensive, step-by-step guide to Building, Scaling, and Integrating AI and Generative AI into real-world products. Drawing from over two decades of experience, this comprehensive guide bridges the gap between AI technology and business impact, ensuring you can navigate the AI revolution with confidence. Featuring Forewords by: Ted Shelton, Chief Operating Officer at Inflection AI (co-founded by Reid Hoffman) Dr. Jia Li, Co-Founder and Chief AI Officer at LiveX AI; Founding Head of R&D at Google Cloud AI; AI Professor at Stanford What You'll Learn: Complete 9-Step AI Product Creation Framework: Master the entire AI product lifecycle from discovery and experimentation to scaling, governance, and AI model lifecycle management. 20+ Real-World Case Studies: Learn from successful AI implementations across healthcare, finance, e-commerce, retail, manufacturing, and big tech companies like Google, Meta, Amazon, and Apple. Traditional AI vs. Generative AI: Understand when to use each approach, how to leverage models like GPT and transformers, and key differences in adoption strategies. AI Model Performance and Ethics: Address challenges like bias, fairness, model drift, and regulatory compliance. Practical Tools and Templates: Access decision-making frameworks, checklists, and internal diagrams that guide seamless execution. Who Should Read This Book? AI Product Managers and Tech Leaders: A strategic and tactical guide for AI integration. Entrepreneurs and Founders: Leverage AI for competitive advantage and scalability. Business Executives and Decision-Makers: Understand AI's potential for growth and optimization. Students and Aspiring AI PMs: Develop industry-ready skills through real-world case studies.