Imagine generating personalized marketing campaigns for millions of customers with a few clicks, or exploring thousands of new molecule configurations in minutes rather than months. But how can companies of varying sizes and skill sets get started with developing new innovations?
The rapid evolution of generative AI is transforming industries and unlocking new possibilities for all organizations. From automating content creation and personalization at scale to accelerating drug discovery and material design, generative AI has the power to drive innovation across industries.
Harnessing the full potential of this technology, though, has tended to require significant expertise and resources, putting it out of reach for many companies. That's why democratizing access to generative AI tools and capabilities is critical for widespread adoption and breakthrough innovations. At AWS, we believe that generative AI should be accessible to all.
The Power of Democratized AI
At the core of today's generative AI capabilities are foundation models—large machine learning models trained on vast datasets to acquire broad knowledge and capabilities. These models can then be adapted for a wide range of downstream tasks through techniques such as prompting and fine-tuning.
Democratizing generative AI means making these powerful foundation models—and the tools to work with them—available to everyone, no matter their technical background or resources. For example, Amazon SageMaker provides fully managed integrated development environments for data scientists and no-code interface for business analysts to build, train, and deploy foundation models, including large language models (LLMs), for any use case. In addition, Amazon Bedrock makes it easy for developers to build and scale generative AI applications with foundation models.
This approach accelerates innovation. When more people and organizations can experiment with generative AI, we see an explosion of creative new use cases and applications. Ideas that may have taken months or years to develop can now be built in days.
It also increases productivity. As many companies have discovered, AI-powered tools can automate routine tasks, generate content, and provide intelligent assistance, freeing up human workers to focus on higher-value creative and strategic work.
Democratizing AI levels the playing field. Small businesses and startups can now access the same powerful AI capabilities as large enterprises, letting them compete more effectively and bring innovative solutions to market faster.
At the same time, companies can customize AI solutions for their specific needs. Organizations can fine-tune models for their unique use cases and data, rather than relying solely on general-purpose, one-size-fits-all solutions.
AWS’s democratization efforts emphasize ethical AI principles and best practices, helping to ensure that generative AI is developed and deployed responsibly across industries.
The Power of Choice
To be sure, no single generative AI solution works for all companies. Businesses have diverse needs, resources, and levels of AI expertise. Some are just beginning to experiment, while others are ready to develop and deploy custom models at scale. That's why our approach emphasizes flexibility and choice. Our vision is to meet builders and organizations wherever they are on their generative AI journey.
For those just getting started, AWS offers no-code tools such as Amazon SageMaker Canvas that abstract away complexity, allowing business users to leverage foundation models through a visual interface. This democratizes access and enables rapid experimentation without significant AI knowledge.
As organizations progress, AWS provides fully managed services like Amazon Bedrock for building and scaling generative AI applications with powerful foundation models. This allows developers and AI engineers to harness the latest advances in areas such as retrieval augmented generation and agentic workflows, while maintaining full control and customizability.
For those looking for more flexibility and control, Amazon SageMaker lets you train, evaluate, fine-tune with advanced techniques, and deploy foundation models with fine-grain controls. This includes a variety of compute solutions including AWS’s purpose-built AI chips Trainium and Inferentia, simplified distributed training environments, automated model optimization, and flexible model deployment options to help organizations balance performance and cost.
This flexibility allows you to mix and match services based on your skill set and use case requirements. For instance, a data scientist might build custom models using AWS’s advanced training capabilities, share them via custom model import capabilities, and make them available to application developers via API. This seamless collaboration empowers teams to leverage their respective strengths while working toward a common goal.
Real-World Impact
The democratization of generative AI is already driving innovation across industries. For example, Workday, a leading provider of solutions that help organizations manage their people and money, focuses on developing AI-powered products. To streamline model development and free engineers from infrastructure maintenance, the company adopted SageMaker, allowing Workday to rapidly iterate and deploy complex models, including LLMs, to production.
Similarly, Perplexity, a startup building a conversational “answer” engine (as opposed to a search engine), faced the challenge of optimizing its LLMs for accuracy and precision while answering more than 250 million user queries each month. By leveraging AWS's advanced ML infrastructure, Perplexity reduces model training time by up to 40 percent, handles more than 500,000 queries per hour without compromising latency, and enables developers to focus on model fine-tuning instead of managing infrastructure. The flexibility to allocate tailored computing resources further optimized Perplexity's workflows.
Finally, Amazon Pharmacy aimed to improve medication access and affordability. Studies show that 20 to 30 percent of Americans never fill prescriptions due to cost and access issues. By deploying deep learning models on AWS, Amazon Pharmacy now provides upfront insurance estimates for 99 percent of prescriptions. This helps customers make informed decisions about medication costs. Amazon Pharmacy also created an AI-powered chatbot using AWS’ generative AI services. This enabled customer support staff to access accurate information quickly and in turn helped enhance response times for customer inquiries. These solutions improved efficiency while maintaining robust data privacy and security standards.
These examples highlight how democratized access to generative AI tools can benefit organizations of all sizes and skill sets. Democratized access can help drive innovation and operational excellence, even in highly regulated industries like healthcare.
From startups pushing boundaries to enterprises enhancing existing products with AI-powered features, the impact of generative AI is significant and far-reaching.
The Path Forward
As generative AI continues to evolve at a rapid pace, democratization efforts will play a crucial role in ensuring that this technology delivers value across the entire business landscape. We're committed to continually expanding and refining our tools to make generative AI more accessible, powerful, and responsible. Hundreds of thousands of AWS customers use AWS artificial intelligence and machine learning services. We're lowering the barriers to entry and empowering organizations to leverage this powerful technology to build differentiated experiences and innovate faster.
Looking ahead, there is tremendous potential for generative AI to continue to transform industries, enhance productivity, and unlock new realms of creativity. By providing tools that cater to users of all skill levels—from visual interfaces to advanced distributed training environments to access to small language models and industry specific models like EvolutionaryScale’s ESM3, a new frontier language model family for biology—the team is working to ensure that every type of organization has the opportunity to harness this transformative technology.
The democratization of generative AI is not just about making powerful tools available; it's about empowering people and organizations to reimagine what's possible. As we continue to lower the barriers to entry and provide intuitive, scalable solutions, we're excited to see the wave of innovation that will emerge from businesses of all sizes across every industry.
Get started with generative AI on AWS.
By Antje Barth, Principal Developer Advocate AI/ML, Amazon Web Services
This story was produced by AWS and edited by WIRED Brand Lab.