AWS re:Invent, which has been going down from November 27 and runs to December 1, has had its traditional plethora of bulletins: a complete of 21 at time of print.

Maybe not surprisingly, given the massive potential affect of generative AI – ChatGPT formally turns one yr previous as we speak – plenty of focus has been on the AI facet for AWS’ bulletins, together with a main partnership inked with NVIDIA throughout infrastructure, software program, and providers.

But there was a lot extra introduced on the Las Vegas jamboree moreover. Right here, CloudTech rounds up the perfect of the remainder:

Subsequent-generation chips

This was the opposite main AI-focused announcement at re:Invent: the launch of two new chips, AWS Graviton4 and AWS Trainium2, for coaching and working AI and machine studying (ML) fashions, amongst different buyer workloads. Graviton4 shapes up in opposition to its predecessor with 30% higher compute efficiency, 50% extra cores and 75% extra reminiscence bandwidth, whereas Trainium2 delivers as much as 4 occasions sooner coaching than earlier than and can be capable to be deployed in EC2 UltraClusters of as much as 100,000 chips.

The EC2 UltraClusters are designed to ‘ship the very best efficiency, most power environment friendly AI mannequin coaching infrastructure within the cloud’, as AWS places it. With it, prospects will be capable to practice massive language fashions in ‘a fraction of the time’, in addition to double power effectivity.

As ever, AWS affords prospects who’re already utilising these instruments. Databricks, Epic and SAP are among the many firms cited as utilizing the brand new AWS-designed chips.

Zero-ETL integrations

AWS introduced new Amazon Aurora PostgreSQL, Amazon DynamoDB, and Amazon Relational Database Providers (Amazon RDS) for MySQL integrations with Amazon Redshift, AWS’ cloud information warehouse. The zero-ETL integrations – eliminating the necessity to construct ETL (extract, remodel, load) information pipelines – make it simpler to attach and analyse transactional information throughout numerous relational and non-relational databases in Amazon Redshift.

A easy instance of how zero-ETL capabilities will be seen is in a hypothetical firm which shops transactional information – time of transaction, gadgets purchased, the place the transaction occurred – in a relational database, however use one other analytics software to analyse information in a non-relational database. To attach all of it up, firms would beforehand should assemble ETL information pipelines that are a money and time sink.

The most recent integrations “construct on AWS’s zero-ETL basis… so prospects can rapidly and simply join all of their information, irrespective of the place it lives,” the corporate mentioned.

Amazon S3 Categorical One Zone

AWS introduced the overall availability of Amazon S3 Categorical One Zone, a brand new storage class purpose-built for purchasers’ most frequently-accessed information. Knowledge entry velocity is as much as 10 occasions sooner and request prices as much as 50% decrease than commonplace S3. Firms may also decide to collocate their Amazon S3 Categorical One Zone information in the identical availability zone as their compute sources.  

Firms and companions who’re utilizing Amazon S3 Categorical One Zone embrace ChaosSearch, Cloudera, and Pinterest.

Amazon Q

A brand new product, and an fascinating pivot, once more with generative AI at its core. Amazon Q was introduced as a ‘new sort of generative AI-powered assistant’ which will be tailor-made to a buyer’s enterprise. “Prospects can get quick, related solutions to urgent questions, generate content material, and take actions – all knowledgeable by a buyer’s data repositories, code, and enterprise methods,” AWS added. The service can also help firms constructing on AWS, in addition to firms utilizing AWS functions for enterprise intelligence, contact centres, and provide chain administration.

Prospects cited as early adopters embrace Accenture, BMW and Wunderkind.

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