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Amazon Web Services (AWS) just announced that Amazon Bedrock has reached general availability, making the artificial intelligence (AI) service accessible to more customers than ever. Amazon Bedrock is a platform for businesses of all sizes to build and scale generative AI applications.
Bedrock gives customers access to multiple foundational models (FM) to simplify the deployment and scaling of generative AI tools. With these FMs and other services, businesses can build generative AI applications for tasks like content creation, data analysis, and more.
4 ways Amazon Bedrock can help businesses use generative AI tools
In a month full of AI announcements from Apple, Microsoft, and Meta, Amazon continues to double down on generative AI tech, this time by announcing the general release of Amazon Bedrock.
1. Democratizing AI: From startups to corporations
AWS first announced the launch of Amazon Bedrock in April, and for the past five months, the platform has been used by startups like Coda, Hurone AI, and Nexxiot, and large companies like Adidas, GoDaddy, and Broadridge.
From travel companies like Lonely Planet to independent software vendors (ISVs) like Salesforce, Amazon Bedrock makes the creation of generative AI tools accessible to a wide range of businesses.
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“To help a broad range of organizations build differentiated generative AI experiences, AWS has been working hand-in-hand with our customers, including BBVA, Thomson Reuters, Philips, and LexisNexis Legal & Professional,” Swami Sivasubaramanian, vice president for Data and Machine Learning Services at AWS, shared in a blog post. “And with the new capabilities launched today, we look forward to enhanced productivity, improved customer engagement, and more personalized experiences that will transform how companies get work done.”
Amazon has a free 60-minute digital course on getting started with Amazon Bedrock and a collection of on-demand training courses available.
2. Cost-effectiveness: Time saved = money saved
The old adage of “time is money” couldn’t be more accurate in generative AI.
Creating, training, and deploying a Large Language Model can take weeks or months and requires properly trained experts, gathering and storing data, and high-performance hardware. Bedrock works as a one-stop shop for AI models, where businesses can pick the models that suit their needs and fine-tune them with their data.
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Customers using Amazon Bedrock don’t need to worry about managing their servers. Its serverless architecture means businesses only pay for what they use and don’t have to manage infrastructure.
AWS claims it’s keeping Amazon Bedrock services affordable to allow more people and businesses to use it. It offers different pricing models: on-demand, provisioned throughput, and model customization.
3. Making the ability to customize AI easy
AWS is also giving customers more options by adding Meta’s Llama 2 in the next few weeks and Amazon Titan Embeddings, which “gives customers greater choice and flexibility to find the right model for each use case,” said Sivasubaramanian.
Llama 2 joins the existing models from AI21 Labs, Anthropic, Cohere, Stability AI, and Amazon in Bedrock. The variety of models to choose from gives customers higher customization possibilities since each model can excel in performing specific tasks and be less effective in others. This also makes the platform more accessible for businesses, unrestricted by low budgets and lack of expertise.
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Along the lines of customization and data security, Sivasubaramanian also announced that Amazon Bedrock is now HIPAA-eligible and capable of being used in compliance with GDPR.
This means customers in the medical field can create generative AI applications to work as virtual health assistants for patients looking for pharmaceutical information, to understand and categorize medical records, or to analyze a patient’s data and predict their risk of complications to allow for preventative measures.
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“With security and privacy built in since day one, Amazon Bedrock customers can trust that their data remains protected,” said Sivasubaramanian. “None of the customer’s data is used to train the original base FMs. All data is encrypted at rest and in transit. And you can expect the same AWS access controls that you have with any other AWS service.”
4. Giving businesses speed to market
The goal of generative AI tools that offer pre-trained FM to build upon, like Amazon Bedrock, removes many of the time-consuming aspects of launching an AI-powered system. This allows systems to focus on customization and can significantly accelerate the time for a generative AI tool to grow from an idea to a market-ready product.
For example, an online store could integrate AI tools generated with Bedrock to seamlessly enhance its search functionality by giving shoppers personalized recommendations. Alternatively, a bank can use it for risk management quickly and without sacrificing data privacy.
“Together, the new capabilities and models we announced today for Amazon Bedrock will accelerate how quickly enterprises can build more personalized applications and enhance employee productivity,” according to Sivasubaramanian.
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