At AWS re:Invent 2023, we chatted with numerous developers about the thing everyone was talking about. Which was…
drum roll
AI.
Specifically, Generative AI.
So much has happened over the last year in this space. LLMs have gone from being primarily a field of academic research to something every developer, product engineer, IT decision maker, C-level executive (and everyone in between) is thinking about.
Questions that have emerged in that time—in the news, at tech conferences, in conversations with developers, among colleagues, in blog articles, etc.—include: Are we in a hype cycle? Is this just another fad? Is AI, after a series of promising starts and then long winters, here to stay for real this time? And if so, how can an organization use Generative AI to disrupt the market instead of being disrupted?
We chatted with several developers at AWS re:Invent to get a sense of what they were thinking about when it comes to Generative AI.
Here’s some of what they had to say:
"[Generative AI] will help people build faster and safer, but [it’s] definitely not going to replace everything." - Developer
"I'm excited about all the tools that can help developers to develop faster, like CodeWhisperer." - Head of Cloud Operations
"Generative AI is here to stay." - Chief Technology Officer
The theme throughout these quotes is how Generative AI will benefit developers in the work they do. Specifically, how Generative AI will help them develop faster and easier.
A prime example of this is, as one of those quotes above notes, Amazon CodeWhisperer, which boosts developer productivity through AI-driven code assistance.
The data used to train Generative AI code assistants, like Amazon CodeWhisperer, is key, though.
This is why MongoDB collaborated with the Amazon CodeWhisperer Data Science team to train CodeWhisperer’s foundational model on MongoDB use cases to give developers the best possible code suggestions.
In addition to helping developers do their work faster and easier, advancements in Generative AI are also empowering developers—specifically developers with more limited backgrounds in AI/ML—to use LLMs more effectively in their applications.
In fact, it’s now easier than ever for developers to build AI-powered apps.
As one data engineer at AWS re:Invent 2023 said: “Generative AI enables people that have no experience in AI to start entering this industry to use their domain knowledge to explore the applications.”
A good example of this is Retrieval-Augmentation Generation or RAG.
MongoDB’s Mat Keep writes in a recent blog article: “As recently as 12 months ago, any mention of retrieval-augmented generation (RAG) would have left most of us confused. However, with the explosion of generative AI, the RAG architectural pattern has now firmly established itself in the enterprise landscape.”
RAG presents developers with a potent combination. They can take the incredible knowledge and reasoning capabilities of pre-trained, general purpose Generative AI models and feed them with accurate and up-to-date company-specific data. This means developers can build AI-powered apps that generate outputs grounded in enterprise data and knowledge without having to turn to specialized data science teams to train or fine-tune models — which is a complex, time-consuming, and expensive process.
RAG is one of many examples of how development tools and technologies are changing to allow developers to build AI confidently and securely.
When you look at all of the above, it’s very clear that this new revolutionary era of Generative AI is driven by empowered developers.
Still, because there are so many incredible advances in both commercial and open-source Generative AI models, and because everyone has access to these, the real differentiation comes down to something unique to every organization: data.
One question we’re left to ask is: What will developers be talking about with respect to Generative AI at AWS re:Invent in the coming year?
As we’ve seen over the last twelve months, a lot can happen and change. So there’s no exact telling what the future will hold.
But what is clear is that the two key things that will determine Generative AI’s future will continue to be data and developers.
To learn more, check out our resources page for building AI-powered apps.