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

Maybe not surprisingly, given the large potential influence of generative AI – ChatGPT formally turns one 12 months outdated immediately – a whole lot of focus has been on the AI aspect for AWS’ bulletins, together with a main partnership inked with NVIDIA throughout infrastructure,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 apart from. Right here, CloudTech rounds up the most effective of the remaining:

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 towards 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 have the ability to be deployed in EC2 UltraClusters of as much as 100,000 chips.

The EC2 UltraClusters are designed to ‘ship the best efficiency, most vitality environment friendly AI mannequin coaching infrastructure within the cloud’, as AWS places it. With it, clients will have the ability to prepare massive language fashions in ‘a fraction of the time’, in addition to double vitality effectivity.

As ever, AWS gives clients who’re already utilising these instruments. Databricks, Epic and SAP are among the many corporations 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 knowledge warehouse. The zero-ETL integrations – eliminating the necessity to construct ETL (extract, remodel, load) knowledge pipelines – make it simpler to attach and analyse transactional knowledge throughout varied relational and non-relational databases in Amazon Redshift.

A easy instance of how zero-ETL features may be seen is in a hypothetical firm which shops transactional knowledge – time of transaction, objects purchased, the place the transaction occurred – in a relational database, however use one other analytics device to analyse knowledge in a non-relational database. To attach all of it up, corporations would beforehand need to assemble ETL knowledge pipelines that are a money and time sink.

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

Amazon S3 Specific One Zone

AWS introduced the final availability of Amazon S3 Specific One Zone, a brand new storage class purpose-built for purchasers’ most frequently-accessed knowledge. Information entry pace is as much as 10 occasions sooner and request prices as much as 50% decrease than commonplace S3. Corporations may also choose to collocate their Amazon S3 Specific One Zone knowledge in the identical availability zone as their compute assets.  

Corporations and companions who’re utilizing Amazon S3 Specific 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 kind of generative AI-powered assistant’ which may be tailor-made to a buyer’s enterprise. “Clients can get quick, related solutions to urgent questions, generate content material, and take actions – all knowledgeable by a buyer’s info repositories, code, and enterprise techniques,” AWS added. The service can also help corporations constructing on AWS, in addition to corporations utilizing AWS functions for enterprise intelligence, contact centres, and provide chain administration.

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

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