It was quite a surprise when Adam Selipsky stepped down as CEO of Amazon’s AWS cloud computing unit. Perhaps an equally big surprise was that he was replaced by Matt Garman. Garman joined Amazon as an intern in 2005 and became a full-time worker in 2006, working on early AWS products. Few people know the corporate higher than Garman, whose last position before becoming CEO was as senior vp of sales, marketing and global services for AWS.

Garman told me in an interview last week that he hasn’t made any significant changes to the organization yet. “Not much has changed in the organization. “The business is doing quite well, so there is no need to make huge changes to anything we are focusing on,” he said. However, he identified several areas where he believes the corporate must focus and where he sees opportunities for AWS.

Emphasize start-ups and rapid innovation

One of them, somewhat surprisingly, is startups. “I think we have evolved as an organization. … In the early days of AWS, our main focus was on how to really attract developers and startups, and we got a lot of traction there from the beginning,” he explained. “And then we started thinking about how do we appeal to larger businesses, how do we appeal to governments, how do we appeal to regulated sectors around the world? And I think one of the things that I just emphasized again – it’s not really a change – but I just emphasized that we can’t lose focus on startups and developers. We have to do all these things.”

The second area he wants the team to focus on is maintaining with the whirlwind of change within the industry.

“I even have really emphasized with the team how essential it’s for us to proceed to remain on the forefront that we’ve by way of the set of services, capabilities and features and functions that we’ve today – and proceed to lean forward and construct the plan motion involving real innovation,” he said. “I think the reason customers use AWS today is because we have the best and broadest set of services. The reason people turn to us today is because we continue to deliver industry-leading security and operational efficiency by far, and help them innovate and move faster. We must continue to implement the action plan. “It’s not likely a change in itself, but that is probably what I highlighted essentially the most: how essential it’s for us to take care of the extent of innovation and the speed at which we deliver products.”

When I asked him if he thought possibly the corporate hadn’t innovated fast enough up to now, he said no. “I think the pace of innovation is only going to accelerate, so it’s just important to emphasize that we also need to accelerate the pace of innovation. It’s not that we’re losing it; it is simply an emphasis on how much we need to accelerate given the pace of technology.”

Generative Artificial Intelligence in AWS

With the emergence of generative AI and technology changing rapidly, AWS must be “on the cutting edge of all of them,” he said.

Shortly after ChatGPT’s launch, many experts questioned whether AWS was too slow to launch generative AI tools on its own and left the door open to competitors like Google Cloud and Microsoft Azure. However, Garman believes that this was more imagination than reality. He noted that AWS has long offered successful machine learning services like SageMaker, even before generative AI became a buzzword. He also noted that the corporate has taken a more thoughtful approach to generative AI than perhaps a few of its competitors.

“We were looking at generative AI before it became a widely accepted thing, but I will say that when ChatGPT came out, it was kind of a discovery of a new area and how to apply this technology. I think everyone was excited and energized by it, right? … I think a group of people – our competitors – were kind of racing to put chatbots at the top and show that they are leading the way in generative AI,” he said.

Instead, Garman said, the AWS team desired to take a step back and take a look at how its customers, whether startups or enterprises, could best integrate the technology into their applications and leverage own, differentiated data. “They will need a platform that they will construct on freely and consider it as a platform to construct on relatively than an application that they will customize. That’s why we took the time to construct this platform,” he said.

In the case of AWS, that platform is Bedrock, where it offers access to a big selection of open and proprietary models. Just doing this – and allowing users to attach different models together – was a bit controversial on the time, he said. “But for us, we thought that was probably where the world was going, and now it was certain that that was where the world was going,” he said. He said he thinks everyone will want custom models and provide their very own data for them.

Garman said the bedrock is “growing like a weed right now.”

One problem with generative AI that it still wants to resolve is price. “A lot of this is doubling down on our custom silicon and making some other changes to the models to draw the conclusion that you’re going to be building (something) much cheaper into your applications.”

Garman said the following generation of AWS’s custom Trainium chips, which the corporate debuted on the re:Invent conference in late 2023, will likely be launched later this 12 months. “I’m really excited that we can really turn this cost curve around and start delivering real value to customers.”

One area where AWS hasn’t necessarily tried to compete with a few of the other tech giants is in constructing its own large language models. When I asked Garman about this, he noted that these are still issues the corporate is “very focused on.” He thinks it is vital for AWS to have its own models while still using third-party models. But he also desires to ensure AWS’s own models can bring unique value and differentiation, either through leveraging its own data or “through other areas where we see opportunities.”

Among these areas of opportunity are costs, but in addition agents, which everyone within the industry seems optimistic about for the time being. “Having models that are reliable, at a very high level of correctness, and can call other APIs and do things. “I think there is some innovation that can be done in this area,” Garman said. He says agents will gain way more utility from generative AI, automating processes on behalf of their users.

Q, a chatbot powered by artificial intelligence

At the recent re:Invent conference, AWS also unveiled Q, its AI-powered generative assistant. Currently, there are mainly two versions of this solution: Q Developer and Q Business.

Q Developer integrates with a lot of the most well-liked development environments and, amongst other things, offers code completion and tools for modernizing legacy Java applications.

“We really think of Q Developer as a broader sense of really helping throughout the developer lifecycle,” Garman said. “I think a lot of early developer tools focused on coding, and we’re thinking more about how do we help with everything that’s painful and labor-intensive for developers?”

At Amazon, teams used Q Developer to update 30,000 Java applications, saving $260 million and 4,500 years of developer labor, Garman said.

Q Business uses similar technologies under the hood, but focuses on aggregating internal company data from many various sources and making it searchable using a ChatGPT-like Q&A service. The company “sees a real driving force there,” Garman said.

Shutting down services

While Garman noted that not much has modified under his leadership, one thing that has happened recently at AWS is that the corporate announced plans to shut down a few of its services. Traditionally, AWS hasn’t done this fairly often, but this summer it announced plans to shut down services just like the Cloud9 web IDE, CodeCommit competitor GitHub, CloudSearch and others.

“It’s sort of a clean-up where we looked at a number of services and either, frankly, introduced a better service that people should move to, or we launched one that we just didn’t get better,” he explained. “And by the way, some of them we just don’t do well, and their traction has been quite poor. We looked at it and said, “You know what? The partner ecosystem actually has a better solution and we intend to build on it.” You cannot put money into every part. You cannot construct every part. We do not like to do that. We take this seriously if firms wish to rely on us to support their activities in the long run. That’s why we’re very careful.”

AWS and the open source ecosystem

One relationship that has long been difficult for AWS – or no less than has been perceived as difficult – is its relationship with the open source ecosystem. This is changing, and just just a few weeks ago AWS contributed its code to the OpenSearch Linux Foundation and the newly formed OpenSearch Foundation.

“I think our view is pretty simple,” Garman said after I asked him what he thought in regards to the future relationship between AWS and open source software. “We love open source. We rely on open source code. I feel we’re attempting to leverage the open source community, making an enormous contribution to the open source community. I feel that is what open source is all about – benefiting from the community – and that is why we take it seriously.”

He noted that AWS has made key investments in open source software and a lot of its own open source projects.

“Most of the friction has come from firms that originally began open source projects and then decided to sort of decommission them from open source, and I feel they’ve the appropriate to do this. But you recognize, that is not the true spirit of open source. Whenever we see people doing this, take Elastic for instance, and OpenSearch (AWS’ ElasticSearch fork) is sort of popular. … If there’s a Linux (Foundation) project, or an Apache project, or the rest that we will construct on, we would like to construct on that; we contribute to them. I feel we’ve evolved and learned as a company learn how to be good stewards of this community, and I hope that has been noticed by others.