AWS re:Invent 2023 – Day 1 news, updates and more



And with that final flourish, that’s a wrap! Nearly two and a half hours of pure AWS innovation and revelation – we’re off to digest the mountain of press releases, so stay tuned for all the latest news on TechRadar Pro.

We’ll be back tomorrow morning with the day two keynote from Swami Sivasubramanian, looking at all things AI and ML, so join us then!


“The most important reinvention of all is yours,” Selipsky notes, emphasizing how AWS is looking to give businesses everywhere the tools they need to experiment and grow.

He notes how Amazon has a history of making big bets, and how its long-term focus is part of its DNA.

Next up is Project Kuiper, the LEO satellite project that looks to deliver fast and reliable internet access for those in need. We’re then treated to a little promo video about Kuiper’s recent advances, complete with real-life smoke machines!

It’s not just consumers who can benefit from Kuiper though, as Selipsky outlines how first-responders, environmental scientists and more can see advances.

Kuiper is also going to provide enterprise-ready data transfer services via Kuper Network Core, coming next year.

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To help with governance, there’s an update to Amazon DataZone, which now goes further to help users find the right data at the right time with new AI recommendations, which can automatically add business context to your data catalog in just a few clicks.


Another new announcement – three new zero-ETL integrations with Amazon Redshift, giving users access to more databases.

ETL is a big pain point for many businesses, and Selipsky notes that AWS is going even further with the launch of Amazon DynamoDB zero-ETL integration with Amazon OpenSeach Service.


Wouldn’t you know it – Selipsky outlines how Amazon has provided the most comprehensive set of data services around, from Data Lkes to Aurora to Analytics to Databases via RedShift.

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Selipsky is back, and looking at how important data in generative AI really is.

“Your data is your differentiator,” he notes, and ensuring it is all up to date and relevant is paramount – as is getting your data in the cloud.

Different organizations across a business will use different kinds of data from different sources – but there’s no one tool to help smooth this out.

What you need is a set of tools to allow you to get value and access to your data – if only there was something like that around, hey.


“This is just the start of how we’re going to revolutionize the future of work,” Selipsky notes, saying that it’s still early in the game.

He now turns to data itself – which is more important than ever before – and he welcomes Stephan Durach from BMW to talk more about personalization and customization using AWS and AI.


Amazon Q can also help workers who may not be as clued-up, allowing natural language queries that will track down the data or information needed much faster, even if your question is just a single word.

The platform will also help create graphs, tables and even reports – and customer service agents will be able to get better help using Q integrations with Amazon Connect, the company’s contact center-specific platform, which will provide real-time response generations as the call develops.


It can also take access on your behalf, updating processes and notifying co-workers of any changes or upgrades.

“Amazon Q brings AI into the business world,” Wood notes.


But what about the less technical workers in your company?

Selipsky notes how workers across multiple roles struggle to find the information they need and turn it into the results they need.

Amazon Q will also be “your business expert” he says, allowing workers to ask complex questions relevant to their precise roles. It connectes to over 40 popular tools such as Salesforce, Gmail, Slack, Atlassian and Microsoft 365.

We’re then treated to a demo from AWS’ head of product Matt Wood, who shows us how Q is able to use generative AI to allow users to ask complex questions based on company (and even role) specific tasks and responsibilities. 

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AWS also wants to help developers who are swamped with upgrades, especially those struggling with migations and updates when it comes to language versions for platforms such as Java.

In order to help, Amazon Q Code Transformation can help complete upgrades in just a fraction of the time – not just Java, but also migraton from Windows to Linux.


Trained on 17 years of AWS knowledge, Amazon Q can be specifically tailored and customized to the precise tasks you encounter at work.

The Q Architect service can also help you research, troubleshoot and analyze issues across your business, saving time and stress, and provide suggestions on optimizing AWS infrastructue queries, such as EC2 instances.

Amazon Q is also going to be in the IDE for developers, working alongside CodeWhisperer for further code suggestions, helping reduce “hours of work…it’ll do all the heavy lifting for you,” Selipsky says.

Amazon Q will be available today as a preview, but will get a wider release soon.


“But we’re just getting started,” Selipsky notes, highlighting AI chat applications as another major target.

Often, these models aren’t smart enough to know about specific companies or workers, your preferences or data sources – so AWS is announcing Amazon Q, a new generative AI-powered assistant that’s tailored to your workplace.

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Selipsky says there is a huge opportunity from infusing Generative AI into the apps you use every day.

“We believe generative AI has the potential to transfrom every customer interaction we know,” he says.

A variety of tasks can be simplified by AI, he notes, including writing code, via Amazon CodeWhisperer, which provides AI-powered code suggestions.

AWS is making CodeWhisperer code suggestions free for individual users, but in order to help developers even further, the company is launching new Amazon CodeWhisperer customization capabilities.


Now we move on to employees, and helping close the skills gap, especially when it comes to cloud computing.

Selipsky notes that AWS is looking to train 29 million employees by 2025, and has many other initiatives in operation, including over 100 AI and ML courses, as well as AI Ready, it’s committment to help millions of students learn more AI skills, as well as creating AWS AI and ML scholarships for young entreprenuers across the world. 


Now it’s time for another big customer spotlight, with Pfizer’s Lidia Fonseca, chiefi digital and information officer, on stage.

Pfizer is using AWS to launch a specific data cloud platform that gave researchers and scientists much quicker and smoother access to historical medical data, greatly speeding up research.


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AI also needs to be responsible, Selipsky says, but enforcing this will mean “unprecedented collaboration” among all kinds of stakeholders.

AWS has been at the forefront of this, he notes, highlighting its work with US and UK governments in recent weeks,

To go further, Selipsky reveals Guardrails for Amazon Bedrock, which allows companies to set up responsible AI policies to safeguard users

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But models need to be secure and private, and AWS Bedrock can allow that, the same as all other AWS services, Selipsky says.

He emphasises that no customer data will ever be used to train the underlying model, never hits the public web, and stays in the AWS network.

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Now, how do you actually use FMs to get stuff done? Selipsky says this can often be a complex process, but fortunately there’s the new Agents for AWS Bedrock tool, which allows multi-step tasks across company systems and data sources, allowing models to be more customized and optimized for specific use cases.


Using your own data to create a model that’s customized to your business is vital, Selipsky notes, with Amazon Bedrock and new Fine tuning tools allowing just that, meaning the model learns from you and your data to help create tailored responses.

There’s also a new Retrieval Augmented Generation (RAG) with Knowledge Bases release on offer, allowing even further customization.


After a glowing review from Amodei, he heads off, and Selipsky turns to Amazon Titan Models – the AI models Amazon is creating itself, with 25 years of experience with AI and ML.

These models can be used for a variety of use cases, such as text-based tasks, copy editing and writing, and search and personalization tools.

More Titan models will be coming soon – but more on that in tomorrow’s keynote, apparently…


Amodei notes that AWS will be Anthropic’s main cloud provider for mission-critical workloads, allowing it to train more advanced versions of Claude for the future.

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“It’s still early days,” Selipsky notes, highlighting how different models often work better in different use cases – “the ability to adapt is the most important ability you can have.”

In order to help deal with this, AWS is looking to expand its offerings for customers – “you need a real choice”, Selipsky notes.

To do this, he emphasizes how Bedrock can provide access to a huge range of models – including Claude maker Anthropic.

He welcomes Anthropic CEO and co-founder Dario Amodei to the stage to talk more.

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Now, moving on from infrastructure to models. Selipsky notes that customers often have many pertinent questions about how best to implement and use AI, and AWS wants to help with its Bedrock platform.

Allowing users to build and scale generative AI applications with LLMs and other FMs, Bedrock also allows significant customization and security advantages. Over ten thousand customers are using Bedrock already, and Selipsky sees this only growing and expanding in the future.


Now it’s on to AWS SageMaker, which has played a huge role in AWS’s ML and AI work over the years, and now has tens of thousands of customers across the world, training models with billions of parameters. But there’s no update for this platform today…


Moving on to the silicon level, Selipsky focuses on EC2 Inf2 Instances, which now deliver higher throughput and lower latency than ever before.

AWS Trainium is seeing major uptake among companies looking to train generative AI models – but as models get bigger, the needs get greater.

To cope with this, Selipsky reveals AWS Trainium2, four times faster than the original product, making it better for training huge models with hundreds of billions of parameters.

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With those two (frankly ridiculous) announcements, Huang departs to huge applause.

Selipsky now moves on to capacity – getting access to all this compute.

Customers often needs clustered capacity brought together, but don’t need all of it all the time – fluctuating demands call for short-term clustered capacity, but no main cloud provider provides this.

Luckily, the new Amazon EC2 Capacity Blocks for ML will now allow this, allowing customers to scale up hundreds of GPUs in a single offering, meaning they’ll have the capacity they need, when they need it.


There’s a second big announcement – Nvidia DGX Cloud is coming to AWS as well.

This is Nvidia’s AI factory, Huang notes – “this is how we develop AI”.

DGX Cloud will be the largest AI factory Nvidia has ever built – including running Project Seba, 16,384 GPUs connected into one AI supercomputer – “it’s utterly incredible,” Huang notes – a stunning 65 exaflops of power.


Huang announces a deployment of a whole new family of GPUs – including the new Nvidia H200 Grace Hopper superchips, offering a huge step forward in power and performance when it comes to LLMs and AI.

Nvidia is deploying 1 zettaflop of computing capacity per quarter – a staggering amount.

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Selipsky reveals an expansion of AWS and Nvidia’s relationship, and introduces a special guest – Nvidia CEO Jensen Huang!

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Selipsky highlights AWS’ close work with Nvidia to help further the training and development of AI.

But you also need high-performance clusters alongside GPUs, with AWS providing incredibly advanced and flexible offerings that allows customers to scale up when needed.

All of this is built on AWS Nitro, which “reinvented virtualization”, allowing for efficiency and productivity gains all round, Selipsky says.


Here we go – it’s AI time.

“Generative AI is going to reinvent eery application we interact with at work or home,” Selipsky says, noting how AWS has been investing in AI for years, using it to generate tools such as Alexa.

The Generative AI stack has three layers, he highlights, turning to infrastructure first. AI uses huge compute power, so getting the most out of your stack is vital.

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All this adds up to a full suite designed for helping your business, Selipsky says.

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Now, we move on to general-purpose computing – it’s Graviton time.

Selipsky looks back to the initial launch in 2018, before Graviton2 in 2020 and Graviton3 in 2022.

Now though, it’s time for an upgrade, namely AWS Graviton4 – the most powerful and energy-efficient chip the company has ever built, Selipsky says.

The chips are 30% faster than Graviton3, 40% faster for database applications, and 45% faster for large Java applications.

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Selipsky runs through some of the history of Amazon storage, looking back at how Amazon S3 has evolved.

Now, it’s time for the next step forward in this journey, he says – Amazon S3 Express One Zone.

Designed for your most-accessed data, it supports millions of requests per minute – and is up to 10x fastser than the existing S3 storage. It looks like a huge step forward for users everywhere.

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AWS offers three times the amount of data centers compared to the next closest cloud provider, 60% more services, and 40% more features – that’s what helps it stand apart from the competitor, Selipsky says.


AWS now extends to 32 regions around the world – no other cloud provider offers that, Selipsky notes.

This extends to multiple AZ’s in each region, meaning regions can remain in operation, even in case of emergency or outages.

“Others would have you believe cloud is all the same – that’s not true,” he notes.


“Reinventing is in our DNA,” Selipsky notes, adding that’s how cloud computing as a whole came about.

This has evolved to making sure companies of all sizes have access to the same technology, no matter who they are.

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But start-ups are also choosing AWS, Selipsky notes, with over 80% of unicorns running on the company’s platform – from genomics mapping to guitar-making.


Salesforce gets a special mention, with Selipsky highlighting the newly-announced partnership between the two companies. Salesforce is expanding its “already large use” of AWS, he notes, with Bedrock and Einstein working together to help developers build generative AI apps faster. 

Salesforce is also putting its apps on the  AWS marketplace.

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AWS CEO Adam Selipsky takes to the stage to rapturous applause, welcoming us to the 12th re:Invent event – there’s apparently 50,000 people here this week.

Selipsky starts with a run-down of the customers AWS is working with, from financial to healthcare, manufacturing and entertainment.

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And with that, the band is done, and it’s keynote time!


With a few minutes to go, it’s a packed out keynote theatre full of AWS fans!

The band is closing out with “My Hero” by Foo Fighters – requested by Adam Selipsky himself apparently!

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Now we have a Back in Black vs Wonderwall mash-up…if this wasn’t Vegas, I’d be confused.

20 minutes until the keynote….


In true Vegas tech conference fashion, it’s 07.35am and we’re being assaulted by full-throttle 80’s rock covers (although the band are pretty decent)

Mr Brightside anyone?

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Welcome to the official day one of AWS re:Invent 2023! We’re (relatively) well-rested and about to get caffeinated, so are nearly ready for the big kick-off shortly.

This morning kicks off with a keynote from AWS CEO Adam Selipsky, who will no doubt be unveiling a host of new products and services, as well as bringing customers and other friends on stage.

The keynote begins at 08:00am PT, so there’s just over an hour to go.


Happy re:Invent 2023! After arriving last night and getting through a jet-lagged day, we’re ready for one more night’s sleep before the main event kicks off tomorrow.

That’s not to say AWS has been cruising into the event though – as today it announced Amazon WorkSpaces Thin Client, a low-cost enterprise focused device that should help businesses everywhere.


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