Amazon Web Services (AWS) has made a series of announcements at its annual re:Invent customer event.
AWS has unveiled new capabilities for products including SageMaker, Amazon Q Business, and Amazon Connect. The company also shared details on data centre improvements that will support the next generation of artificial intelligence (AI) innovation.
Andy Jassy, president and CEO of Amazon, and former CEO of AWS, pinpointed the new capabilities for Amazon Aurora as one key highlight.
Amazon Aurora DSQL is a new serverless, distributed SQL database that enables customers to build applications with the highest availability, strong consistency, PostgreSQL compatibility, and faster reads and writes compared to other popular distributed SQL databases.
Jassy said, “We announced so many things today I can’t get through all of them. But I thought I’d talk about [key] announcements I’m excited about. The first is in the database space. If you’ve looked at what’s happened to databases over the last ten years, we went from assuming there was one tool – one database – to rule the world, to realising that there’s lots of relational database opportunities and options, and lots of non-relational database options.”
He discussed how AWS went about building Aurora ten years ago, with initial ambitions to offer the performance of the highest grade enterprise database out there, while at the same time being a fraction of the cost and fully SQL compatible. Over time, however, AWS found that some customers were facing “the tyranny of the ‘or’” as the company pushed the limits of what relational databases could provide for customers.
Jassy explained, “You don’t want to have to make ‘or’ choices because it means you have to give up on some of the capabilities you want to provide. We worked hard at this and today we announced Aurora DSQL. This is a new flavour of Aurora. It’s a distributed database, it’s multi-region, it’s very low latency, it’s high availability, has strong consistency, and has zero operational burden because it’s all serverless and it’s SQL compatible. People are very excited about this and it’s going to bring a huge change for what people can do.”
Improvements have also been made to Amazon DynamoDB to support demanding workloads that need to operate across multiple regions with strong consistency, low latency, and the highest availability.
Amazon DynamoDB global tables supports multi-region strong consistency, ensuring multi-region applications are always reading the latest data without having to change any application code.
Energy efficient data centres
The company also unveiled new data centre components designed to support the next generation of AI innovation and evolving customer needs.
These capabilities combine innovations in power, cooling, and hardware design to create a more energy efficient data centre. These new capabilities will be implemented globally in new AWS data centres, and many components are already deployed in existing data centres.
Prasad Kalyanaraman, vice president of infrastructure services at AWS, said, “AWS continues to relentlessly innovate its infrastructure to build the most performant, resilient, secure, and sustainable cloud for customers worldwide.
“These data centre capabilities represent an important step forward with increased energy efficiency and flexible support for emerging workloads. But what is even more exciting is that they are designed to be modular, so that we are able to retrofit our existing infrastructure for liquid cooling and energy efficiency to power generative AI applications and lower our carbon footprint.”
There are also new capabilities for Amazon Bedrock, the company’s fully managed service for building and scaling generative AI applications. The improvements will help prevent factual errors due to hallucinations, orchestrate multiple AI-powered agents for complex tasks, and create smaller, task-specific models that can perform similarly to a large model at a lower cost and reduced latency.
New capabilities are also coming for Amazon Q Business, the company’s generative artificial intelligence (AI)-powered assistant for finding information and taking action at work.
Amazon Q Business and generative AI-powered experiences in third-party applications, such as Asana and Zoom, can now work from the same index of enterprise data. This could allow employees to get insights across all of their enterprise information and benefit from more personalised generative AI-powered experiences in third-party applications.
Users can now take over 50 new actions, like creating a task in Asana or sending a private message in Teams, across popular third-party applications.
The company also announced new generative AI enhancements for Amazon Connect, its cloud contact centre solution (pictured below). These new features aim to further improve customer experiences by enabling more personalised, efficient, and proactive customer service. As a result, organisations can help improve customer satisfaction through faster issue resolution and continuous contact centre optimisation, while reducing operational costs.
Pasquale DeMaio, vice president and general manager of Amazon Connect at AWS, explained, “By using generative AI to improve the customer experience, Amazon Connect is paving the way for a future where every customer interaction is an opportunity to delight and foster long-term loyalty.
“The continuous evolution of Amazon Q in Connect is giving organisations the power and flexibility needed to handle sophisticated customer service scenarios without requiring programming expertise.”
There have also been updates to Amazon SageMaker that are designed to unify the capabilities customers need for fast SQL analytics, petabyte-scale big data processing, data exploration and integration, model development and training, and generative AI into one integrated platform.
The new SageMaker Unified Studio will help customers find and access data from across their organisation. It also brings together AWS analytics, machine learning, and AI capabilities.Improvements to SageMaker Catalog aims to allow users to access the right data, models, and development artifacts for the right purpose. The new SageMaker Lakehouse unifies data across data lakes, data warehouses, operational databases, and enterprise applications.
AWS re:Invent concludes on Thursday (6 December), with further announcements expected across this week.