At the top of my morning social feeds recently was a post by Swami Sivasubramanian, the VP of Databases, Analytics, and ML at AWS, announcing that AWS has just launched a new Generative AI innovation center. This has been designed to align AWS customers with Artificial and Machine Learning experts from across the globe to speed up the rate of development in building new applications and services using this technology.
Generative AI has made headline news a lot recently, and as people become more aware of its capabilities and explore new business initiatives by adopting this technology, the rate at which organizations can harness its potential is likely going to grow exponentially. AWS already heavily invests in both ML and AI, and has done so for many years, and this is evident in the wide range of services they currently provide, as shown in this table:
|Machine Learning||Artificial Intelligence|
|Amazon Bedrock||Amazon CodeWhisperer|
|Amazon SageMaker||Amazon Augmented AI|
|Amazon SageMaker Canvas||Amazon CodeGuru|
|Amazon SageMaker Ground Truth||Amazon Comprehend|
|Amazon SageMaker Data Wrangler||Amazon Comprehend Medical|
|Amazon SageMaker Feature Store||Amazon DevOps Guru|
|Amazon SageMaker Studio Lab||Amazon Forecast|
|Amazon SageMaker Studio||Amazon Fraud Detector|
|Amazon SageMaker Build||Amazon HealthLake|
|Amazon SageMaker Train||Amazon Kendra|
|Amazon SageMaker Debugger||Amazon Lex|
|Amazon SageMaker Distributed Training||Amazon Lookout for Equipment|
|Amazon SageMaker Deploy||Amazon Lookout for Metrics|
|Amazon SageMaker Pipelines||Amazon Lookout for Vision|
|Amazon SageMaker Model Monitor||Amazon Monitron|
|Amazon SageMaker Autopilot||Amazon Omics|
|Amazon SageMaker Jumpstart||Amazon Personalize|
|Amazon SageMaker Edge||Amazon Polly|
|Amazon SageMaker Clarify||Amazon Rekognition|
|Amazon SageMaker and Kubernetes||Amazon Textract|
One of AWS’ most recent services in this area, specific to generative AI is AWS CodeWhisperer. This is a great example of how generative AI can be used to develop faster, while also enhancing your security posture. AWS CodeWhisper is used to suggest snippets of code based upon your comments and any existing code. This allows you to quickly develop code based upon security best practices using built-in security scanning mechanisms, which leads to improved productivity.
With all this growth, seeing this new generative AI innovation center is likely going to cause a lot of excitement for a lot of AWS customers. This puts them in a strong position to begin exploring ways to invest into generative AI to push the boundaries of their offerings, creating new experiences, all with the assistance of AI/ML experts and AWS partners.
Who makes up the AWS Generative AI Innovation Center?
The AWS Generative AI Innovation Center is composed of a team of specialists, including data scientists, strategists, and of course solutions architects. This dedicated team will work closely with AWS customers to design, build, and deploy new solutions that will change the way they operate, kickstarting their journey into the realms of utilizing AI/ML and propelling their services forward, enabling them to reach new levels of increased productivity at scale, regardless of the industry they are operating in.
Through the Innovation Center, customers can take full advantage of the support that AWS has to offer, including no cost workshops and training, allowing you to get a deeper understanding of this technology and how to best implement these solutions directly into your business. You’ll gain insight of best practices, work with industry experts and recognized AWS partners who specialize within the generative AI space, allowing you to quickly develop justified business cases and proof of concepts before taking your AI-backed products to market.
You will be exposed to the tools and features that AWS has developed especially for generative AI, including:
- Amazon Bedrock – Used to help you build and scale your generative AI applications using foundation models, which are essentially large models that are pre-trained on vast amounts of data
- AWS Trainium – Machine learning training chip, custom-designed by AWS to deliver the most cost-effective training in the cloud
- AWS Inferentia – AWS Inferentia accelerators have been built by AWS to provide the highest-performance EC2 instances for the lowest cost for your deep learning inference applications.
- Amazon CodeWhisperer – Acting as a code companions, CodeWhisperer allows you automatically generate code based on description of requirements using security best practices
- Hugging Face on AWS – This allows you to fine-tune pre-trained models from Hugging Face. Hugging Face is an open-source provider of natural language processing and is focused on all things AI and ML
- Amazon SageMaker – This is the flagship of ML services on AWS and enables you to build, train and deploy machine learning models across your AWS environment using a range of different frameworks at scale
Adopting these tools and features will help you implement your generative AI solutions across your suite of applications and business offerings.
So, if you feel generative AI is a technology that your business could take advantage of, and are looking for some direction, assistance, feedback, and guidance, then the AWS Generative AI Innovation Center is a great place to get started!