AWS enters Blockchain market, launches own AI chip
Sending close rival Oracle and other competitors a clear signal that “he wants it all and wants it now”, Amazon Web Services (AWS) CEO Andy Jassy has announced two dedicated services for the much-hyped Blockchain market, along with an indigenously-built Artificial Intelligence (AI) chip.
Jassy on Wednesday announced Managed Blockchain service and a Quantum Ledger Database (QLDB) to help companies manage business transactions that require full auditability.
Managed Blockchain supports two popular open source Blockchain frameworks — Ethereum and Hyperledger Fabric.
“This service is going to make it much easier for the customers to use the two most popular Blockchain frameworks,” Jassy told a packed house during his keynote address at the “ReInvent 2018” conference here.
“AWS today has millions of active customers. There has been a dramatic Cloud growth in the enterprise sector. Every imaginable enterprise vertical on Earth is using AWS,” Jassy added.
Amazon QLDB is a transparent and cryptographically verifiable ledger for applications that need a central, trusted authority to provide a permanent and complete record of transactions — like supply chain, financial, manufacturing, insurance, and human resources.
As Jassy announced new capabilities in AWS, one presentation slide showed Oracle Executive Chairman Larry Ellison, who has been criticising AWS for quite some time and at this year’s Oracle OpenWorld, Ellison spent much of his keynote taking on AWS.
“Oracle and SQL databases are expensive and not customer-friendly. These are old guard databases. Time has changed and so are the customers. Our Aurora database has the unmatched pace of innovation. This is the moment for database freedom,” said Jassy, taking a dig on Oracle.
In an earlier interview to CNBC, Jassy said Amazon will be completely off Oracle databases by the end of 2019.
AWS then showcased AWS “Inferentia” AI chip for larger workloads that consume entire GPUs or require lower latency. The high-performance machine learning (ML) inference chip is custom designed by AWS.
The company announced 13 new ML capabilities and services, across all layers in the machine learning stack, to help put machine learning in the hands of even more developers.
“We are not overspending on ML research. It is a gigantic area and we are investing in the right direction,” said Jassy.
In a bid to capture the Hybrid Cloud market, the company along with VMware announced “AWS Outposts” — compute and storage racks that allow customers to run compute and storage on-premises, while seamlessly connecting to the rest of AWS’s broad array of services in the Cloud.
“Customers are telling us that they don’t want a hybrid experience that attempts to recreate a stunted version of a cloud on-premises, because it’s perpetually out of sync with the cloud version. There just isn’t a lot of value in that type of on-premises offering and that’s why these solutions aren’t getting much traction,” said Jassy.
In 2017, AWS collaborated with VMware to introduce VMware Cloud on AWS.
“Our new offerings, VMware Cloud on AWS Outposts and VMware Cloud Foundation for EC2, further extend our vision for consistent infrastructure and consistent operations from the data center to the cloud to the edge,” added Pat Gelsinger, Chief Executive Officer, VMware.
AWS also introduced new “Amazon SageMaker” features, making it easier for developers to build, train, and deploy machine learning models – including low cost, automatic data labeling and reinforcement learning (RL).
The company announced new AI services that can extract text from virtually any document, read medical information, and provide customized personalization, recommendations and forecasts using the same technology used by Amazon.com.
AWS said it will help developers get rolling with machine learning with AWS DeepRacer, a new autonomous model race car for developers, driven by reinforcement learning.
The car (with all-wheel drive, monster truck tires, an HD video camera, and on-board compute) is driven using reinforcement learning models trained using Amazon SageMaker.
Developers can put their skills to the test and race their cars and models against other developers for prizes and glory in the DeepRacer League, the world’s first global autonomous racing league, open to everyone.
The company has launched more than 200 significant ML capabilities in the past 12 months.