6 reasons to use OpenAI alternatives

Co-authored with ChatGPT

Context

In recent years, OpenAI has captured the imagination of developers, researchers, and businesses worldwide with its remarkable advancements in the field of generative artificial intelligence (GenAI). Their models, such as GPT-4, have opened up a world of possibilities for natural language understanding, text generation, and even creative content generation. Many developers have eagerly adopted OpenAI’s APIs to harness the power of generative AI. However, OpenAI is not the only game in town. Many cloud providers including Amazon Web Services (AWS) offers similar services.

The AWS Alternative

While OpenAI leads the way in generative AI, AWS and other cloud providers have entered the ring with their own versions of AI services. This provides developers with an alternative ecosystem to leverage. Here are some compelling considerations of using AWS for generative AI:

1. Eliminating single vendor risks

If we learned anything from the recent firing of Sam Altman — the CEO of OpenAI and his prompt return, is that startups are inherently risky. There is often a significant market risk, some technology risk, but as it turns out sometimes there is also a governance risk. In this case, when the board fired their CEO, close to 95% of employees threatened to quit. This clearly shows that organizations leveraging third party Gen AI services should really consider these kinds of risks.

2. Protection of Copyrighted Materials

One significant concern for corporate legal departments when using generative AI models is the potential for copyrighted materials to leak into the models. While OpenAI publicly stated that it will “not use data submitted to and generated by our API to train OpenAI models or improve OpenAI’s service offering”, some corporate legal departments remain skeptical. This is where alternatives can help. For instance, AWS offers a private version of AI models with robust protections that align with organizational needs and compliance requirements.

3. Legal Indemnification

AWS goes the extra mile by indemnifying its customers from any legal issues that may arise from the use of some of its AI services. This added layer of protection can provide peace of mind for organizations worried about legal implications.

4. Model Choices

With AWS (like with OpenAI), developers have the flexibility to choose from several AI models, allowing them to pick the one that best fits their specific use case. Unlike with OpenAI, Amazon Bedrock also offers third party models from companies such as Anthropic.

5. Familiar APIs

Developers who are already familiar with AWS services will find it convenient to work with AWS’s generative AI offerings. The consistency in the developer experience can streamline integration and development processes. (Although, the OpenAI APIs are very easy to use as well.)

6. Billing Integration

Amazon Bedrock is billed like any other AWS service, simplifying financial management for organizations. This integration into existing billing structures can be advantageous for budgeting and cost control.

Generative AI on AWS for developers

If you’re a developer looking to explore generative AI on AWS, you can get started with some sample code available on this GitHub page. This resource can help you dive into AWS’s generative AI offerings and discover how they can benefit your projects.