Machine learning (ML) has graduated from the realm of science fiction to become a core, transformative technology for organizations across industries and categories. The unique potential and power of ML are sparking significant innovation, powering the ideas that are improving lives and protecting our planet right now. With ML, organizations are making inroads toward protecting and supporting our veterans, finding homes for homeless people, understanding climate change, improving health outcomes, and more. But this is just the beginning. The technology is ripe, and it now has the ability to provide new and significant solutions for some of the world’s biggest challenges. More than a hundred thousand companies and organizations worldwide have turned to Amazon Web Services (AWS) for ML—to help track disease outbreaks worldwide, find new ways to treat cancer, and more. However, access to ML, a new technology to so many of these organizations, can often come with a skills and technology deficit. That’s where AWS steps in, partnering with innovators to bridge the gap and bring pioneering solutions that can help tackle our most urgent and important challenges.

Machine learning (ML) has emerged as a core technology ingredient for organizations that are focused on driving innovation. Today, more than 100,000 organizations leverage artificial intelligence (AI) solutions and services from Amazon Web Services (AWS) to improve business results. These businesses span virtually every industry, including financial services, healthcare, media, professional sports, retail, and the industrial sector. The rapid emergence of generative AI is the most visible example of the impact ML innovations are having on the above industries. Generative AI applications have captured widespread attention because they can help reinvent customer experiences, create applications never seen before, and help users reach unprecedented levels of productivity. According to Goldman Sachs, generative AI could drive a 7 percent increase in global GDP over 10 years. Goldman Sachs also forecasted that AI investment could reach $200 billion by 2025 with the enormous economic potential from generative AI. Like most AI, generative AI is powered by very large ML models that are pretrained on vast amounts of data. These models are commonly referred to as foundation models (FMs). Amidst this growth, obstacles to widespread ML adoption remain. Many organizations, enticed by ML’s potential benefits, have grown frustrated by slow progress and a lack of return on their ML investments. For these organizations to reach their goals, they must find ways to move these large models into production faster and at a lower cost. In this eBook, we will explore the major barriers to ML scalability and success. Then, we will demonstrate how AWS solutions and services can help virtually any organization overcome those challenges and leverage generative AI to drive meaningful innovation.

Thanks to the rapid adoption of cloud computing, the rise of compute power and data volumes, and the emergence of easy-to-use solutions that require little or no experience, machine learning (ML) is now more accessible than ever. Leading organizations across nearly every industry are leveraging ML to achieve positive business results. For many, ML has become a core component of their operations. According to IDC, spending on artificial intelligence (AI) in the United States will grow to $120 billion by 2025, representing a compound annual growth rate (CAGR) of 26 percent over the 2021–2025 forecast period. Amazon Web Services (AWS) is playing a pivotal role in the advancement of ML, empowering customers to effectively use and derive the most benefit from the technology. These customers span finance, healthcare and life sciences, manufacturing, media and entertainment, the public sector, retail, and technology.