I remember in 1997 when I helped found a consulting business, we told customers “we did internet development,” which sounds like a silly statement today. In 2023, every piece of significant software is somehow utilizing the Internet, but back in the late ’90s, when the internet was new to most companies, internet development was new, technologies were quickly emerging, and the future looked bright.
Today at SPR, among other conversations, we talk to our customers about “implementing AI/ML solutions,” which is relevant as AI and ML have historically resulted in niche solutions and required niche skills. However, someday in the not too distant future, “implementing AI/ML solutions” will sound as equally silly as “Internet development,” since AI and ML will be ubiquitous and embedded into everything. In the future, it will be impossible to develop any software solution that does not incorporate AI or ML, directly or indirectly.
The Evolution of AI and ML
While data scientists have built AI and ML solutions for decades, its introduction to mainstream IT initiatives is relatively new. For the most part, AI and ML still require data science expertise, but that is quickly changing as cloud capabilities grow.
As the field of AI continues progress, cloud vendors like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are investing heavily in developing AI services that are easy to integrate and use. These services are designed to be accessible to enterprise software developers who may lack specialized knowledge in AI or ML, but there is still a gap between what is possible and what developers may be aware of.
One of the main challenges for enterprise software developers is that they may not fully understand the range of AI and ML services available to them through cloud vendors. For example, they may be aware of pre-built models for tasks like natural language processing or image recognition, but they may not be aware of the range of options available within these areas.
Know Your Cloud Vendors
Since the range of cloud-based AI and ML services is constantly growing, It’s important for developers to explore the latest offerings from cloud vendors to stay up to date with the latest developments in AI and ML.
Cloud vendors offer a vast array of AI and ML services that can be used to build powerful applications. For example, AWS offers Amazon SageMaker, a fully managed service that provides developers with the ability to build, train, and deploy ML models quickly and easily. Microsoft Azure offers services like Azure Cognitive Services for speech and image recognition, as well as Azure Machine Learning for building custom ML models. GCP offers services like Cloud AutoML for building custom ML models, as well as Google Cloud Vision for image recognition and Google Cloud Natural Language for text analysis.
By using these services, businesses can gain a competitive edge, and benefit from the power of AI without needing to invest heavily in research and development themselves.
If there is a tricky part, it is that cloud vendors are constantly expanding and changing their offerings, so it's important for enterprise software developers to stay informed about the latest developments in AI and ML services.