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Amazon Web Services offers new artificial intelligence, machine learning, and generative AI guides to plan your AI strategy
Breakthroughs in artificial intelligence (AI) and machine learning (ML) have been in the headlines for months—and for good reason. The emerging and evolving capabilities of this technology promises new business opportunities for customer across all sectors and industries. But the speed of this revolution has made it harder for organizations and consumers to assess what these breakthroughs mean for them specifically.
Over the years, Amazon Web Services has invested in the democratizing of access to—and understanding of —AI, ML and generative AI. Through announcements around the latest
Amazon Web Services CAF for AI, ML, and Generative AI
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Used by customers and partner teams, CAF-AI helps derive, prioritize, evolve, and communicate a strategy for AI transformation. The following figure shows how we simplify an AI journey through CAF-AI: by working backward from business outcomes (1) to the opportunities that AI, ML, and generative AI provide (2), across your transformation domains (3) and your foundational capabilities (4) through an iterative process (5) of assessing, deriving, and implementing action items for an AI strategy.
In CAF-AI, we describe the AI/ML journey you may experience as your organizational capabilities on AI and ML mature. To guide you, we zoom in on the evolution of foundational capabilities that we have observed assist an organization to grow its maturity in AI further.
We also provide prescriptive guidance through an overview of the target state of these foundational capabilities and explain how to evolve them step by step to generate business value along the way. The following figure shows these foundational capabilities for cloud and AI/ML adoption. A capability is an organizational ability to use processes to deploy resources (such as people, technology, and other tangible or intangible assets) to achieve an outcome. Because the CAF-AI is a living index of knowledge, you can expect it to grow and change over time.
Designed as a starting and orientation point throughout a customer’s ML and AI journey, CAF-AI is intended to be a document that organizations can draw inspiration from as they shape their mid-term AI and ML agenda and try to understand the important topics and perspectives that influence it. Depending on where you are at on your AI/ML journey, you might focus on a specific section and hone your skills there, or use the whole document to judge maturity and help direct near-term improvement areas.
Because the business problem space to which AI/ML can be applied isn’t a single function or domain, it applies across all functions of businesses and all industry domains where you are looking for ways to reset the playing field in markets where AI/ML does make an economical difference. The
The Getting Started Resource Center machine learning decision guide
Amazon Web Services has always been about choice. As you ramp up your use of AI, it is paramount that you have the right support in choosing the best service, model, and infrastructure for your business needs. The
The decision guide can also help you articulate and consider the criteria that will inform your choices. For example, it describes the range of Amazon Web Services ML services (see the following screenshot), each of which caters to different levels of management requirement, depending on how much control and customization you need.
The guide also explains the unique capabilities of Amazon Web Services services in realizing the power of foundation models and where you can make the most of this fast-evolving branch of machine learning.
It offers details on specific services, links to detailed, service-level technical guides, a comparison table that highlights the unique capabilities of key services, and criteria for selecting AI and ML services. It also provides a curated set of links to key resources that can help you get started in using AI, ML, and generative AI services on Amazon Web Services.
If you want to understand the breadth of AI, ML, and generative AI offerings provided by Amazon Web Services, this decision guide is a great place to start.
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About the Authors
Caleb Wilkinson has more than a decade of experience building AI solutions. As a Senior Machine Learning Strategist at Amazon Web Services, Caleb pioneers innovative applications of AI that push the boundaries of possibility and helps organizations benefit responsibly from artificial intelligence. He is the co-author of CAF-AI.
Alexander Wöhlke has a decade of experience in AI and ML. He is Senior Machine Learning Strategist and Technical Product Manager at the Amazon Web Services Generative AI Innovation Center. He works with large organizations on their AI-Strategy and helps them take calculated risks at the forefront of technological development. He is the co-author of CAF-AI.
Geof Wheelwright manages the Amazon Web Services decision content team, which writes and develops the growing collection of decision guides on the Amazon Web Services Getting Started Resource Center. His team created the Choosing an Amazon Web Services machine learning decision guide. He has enjoyed working with AI and its ancestors since first being introduced to simple, text-based Apple II
The mentioned AWS GenAI Services service names relating to generative AI are only available or previewed in the Global Regions. Amazon Web Services China promotes AWS GenAI Services relating to generative AI solely for China-to-global business purposes and/or advanced technology introduction.