In the fast-paced world of artificial intelligence (AI), we have yet another bot: Amazon Q, which Amazon has said is dedicated to helping developers/business teams.
You may wonder why we need another AI bot in the current market. Consider this: Can we assert with confidence that AI achieves 100% accuracy? Not yet, but I do believe we are close to that point. Consequently, evaluating and using every new tool is worthwhile.
I am personally excited about this release because it has the potential to replace GitHub Copilot. Copilot is a great tool, but I find the intensity of the auto-complete frustrating. I appreciate suggestions, but prefer them to be more fine-tuned. In this quick post, I’ll give an overview of how Amazon Q and ChatGPT compare.
Note: In the chart below, I reference Constitutional AI. While outside the scope of this post, you can learn more about Constitutional AI here.
Amazon Q vs ChatGPT
| Comparison | Amazon Q | ChatGPT |
| Purpose | Specifically designed for business use. It’s an AI-powered assistant intended to facilitate internal business tasks like support tickets, policy information, and other questions about company data. | More general-purpose. It’s designed to generate human-like text based on the prompts it receives. |
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Core Functionality |
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| Ethics |
Not explicitly developed using Constitutional AI techniques, Amazon aims to ensure users are helpful, harmless, and honest in conversations. https://aws.amazon.com/machine-learning/responsible-ai/policy/ |
ChatGPT follows general ethical guidelines and aims for responsible AI development, though its approach does not explicitly align with the specific principles or framework of Constitutional AI. https://openai.com/safety |
| Knowledge Domain |
As it’s for internal business use, its knowledge focuses only on a given company’s data and tooling. |
Does not focus on any specific domain or industry; extremely wide breadth of knowledge. |
Looking Forward
It’s too soon to say what kind of impact Amazon Q will have on the market, but I believe it’s going to reduce a lot of coding challenges and improve the quality of the product being built. We should also expect to see more and more tools pop up as creators and organizations experiment to see what sticks. Have a favorite tool, or one you’d like to see? I'd love to hear about it – reach out on LinkedIn.
