During the re:Invent conference in Las Vegas on Wednesday, AWS CEO Andy Jassy unveiled two new blockchain products - Amazon Quantum Ledger Database (QLDB) and Amazon Managed Blockchain - for developers.
"I think we are entering this golden age of what is going to be possible in applications, and in five years from now or 10 years from now, I think virtually every application will have machine learning and AI in it".
"The problem with ML today is that most companies do not know what they want to do with it".
"We are not overspending on ML". It removes the need to build complex audit functionality into a relational database or rely on the ledger capabilities of a blockchain framework. It takes inputs such as customers' or users' activity streams, inventory (there's little point recommending a product you can't supply) and demographics; builds a recommendation model that's private to the AWS customer; and provides an API for recommendation and personalisation.
"You can expect that we are not close to being done".
"This is still not our focus, although people want us to make more of these things".
These services automate multi-step processes to get customers up and running more quickly, while also centralising management of crucial elements of their AWS environment, helping maintain consistency and providing more complete visibility.
About a year ago, AWS chief executive officer, discarded any form of interest in blockchain services.
AWS also showcased the increasingly influential role of AI in traditional auto races during the conference. "With QLDB, your data's change history is immutable - it cannot be altered or deleted - and using cryptography, you can easily verify that there have been no unintended modifications to your application's data".
In addition to the vehicle itself, AWS is launching the DeepRacer League, an autonomous racing league that will hold matches at Amazon cloud events all next year.
Findings are correlated into integrated dashboards that visualise and summarise a customer's current security and compliance status, and highlight trends and Amazon Elastic Compute Cloud (Amazon EC2) instances that are generating an increasing number of findings.
The service automatically optimises the partitioning of data to improve performance and reduce costs, transforms data into formats like Apache Parquet and ORC for faster analytics, and also uses machine learning to deduplicate matching records to increase data quality.
SageMaker "Ground Truth" capability produces high-quality labelled training data; SageMaker RL delivers Cloud's first managed service for reinforcement learning algorithms and simulators; and a new ML Marketplace offers more than 150 new models and algorithms to developers via SageMaker.
This is good news for the overall industry but not for specific cryptocurrencies.
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