At the ongoing AWS re:Invent event, the tech giant announced various services categorised under analytics, compute and machine learning, among others. It, therefore, came as no surprise when the event was packed with machine learning services such as CodeGuru, Fraud Detector, Kendra, SageMaker Model Monitor, and more.
In the ever-increasing technology landscape, along with automating mundane tasks, organisations are highly focusing on automating strenuous tasks with ML-powered solutions. While this will improve the productivity of the firms, it will also allow them to focus on their core businesses.
Companies continually look to streamline the complete workflows right from the product development to delivery and customer satisfaction. In this article, we will take a look into how companies can integrate machine learning services to achieve their goals effortlessly.
Robust products and services are crucial for any successful businesses. Thus they often seek services that could help them in the development phase. One of the vital aspects of applications is that it should work flawlessly. However, even after numerous tries, firms fail to deliver bug-free solutions. But with the integration of machine learning models in solutions, applications’ throughput decreases and thus companies lose a lot of time in optimising algorithms.
However, with the recent release of CodeGuru, firms can expedite their development workflows. Trained with millions of lines of code from open-source projects and companies’ internal code, CodeGuru is designed to assist users in automatic code review. Using CodeGuru, developers can find bugs, get recommendations to fix or improve the code. Besides, one can identify problems such as resource leaks, wasted CPU cycles, and potential concurrency race conditions.
As of now, CodeGuru provides supports for Java application, and in the future, it will add compatibility to other programming languages, thereby, making it mush have services for organisations. The service has the potential to simplify the development process while optimising applications’ performances.
Superior applications are more often than not are the differentiating factors in the highly competitive technology landscape. Therefore, organisations develop ML-based applications, but due to numerous challenges, they fail to improve the accuracy of ML models for rendering desired results. For instance, concept drift – ML models trained on one data with specific correlation often fail to provide desired results if there are any changes in the business operations – is among one of the pressing problems that firms find difficult to solve. To address such issues, AWS has introduced SageMaker Model Monitor to determine concept issues and increase models’ accuracy.
SageMaker Modle Monitor automatically detects concept drift and notifies administrators to analyse changes through summary statistics and comparison over time with features used in training.
Post product delivery, providing useful services is of paramount importance to retain customers for business growth. Satisfied customers assist in increasing the brand of the firm, and in turn, brings new customers. Consequently, leveraging Amazon Kendra – a machine learning-based service that will enable companies to carry out enterprise search effortlessly – firms can quickly assist their customers in resolving their queries.
Kendra gathers data from various sources within organisations and delivers relevant results. It crawls through multiple documents, including legal information to quickly, resulting in eliminating the time spent while searching within records.
Anyone can query for information and Kendra will do the heavy lifting to provide the best results automatically.
Backed by powerful natural language search abilities, it can also be deployed directly into websites, applications, and more, to obtain information from a vast amount of data spread across companies.
AWS’ announcements have really made a mark as they have focused on the core problems that organisations face. Apart from the services mentioned above, AWS has also announced numerous ML-based solutions that can help firms to carry out their business efficiently.
Machine learning is the key to simplifying the day-to-day activities of every employee in any organisation. Thus, adopting such AWS services can assist organisations in gaining operational efficiency. This will also empower organisations to offer advanced products while reducing the cost through ML-based services.