According to a report from Tractica, the forecasted revenue generated from the application of artificial intelligence software is expected to jump from $1.4 billion in 2016 to $59.8 billion by 2025. And the AI intelligence sector is also expanding at a rapid pace and is anticipated to be the next big technological disruption, similar to the advent of smartphones. Machine learning is an important piece of the overall artificial intelligence pie. It can be thanked for Amazon’s one-day delivery and Netflix’s ability to accurately suggest movies based on user preferences.
Machine learning is the idea that algorithms can tell us something meaningful from a set of data. The unique aspect of machine learning, compared to other areas of artificial intelligence such as robotics or neural networks, is that machine learning allows devices to learn from their own experience.
How Do Machines Learn?
Large sets of data are poured into a machine learning algorithm in order to achieve a result that is usable, without any human intervention. The algorithm is the model that defines a specific goal for the program to strive for. Learning begins as the machine makes guesses, mostly incorrect, to reach the desired outcome. Artificial intelligence will then compare the wrong guesses with the correct result, minimizing error and increasing the accuracy of the prediction rate as it continues to process data.
A Machine Learning Framework is an interface, library or tool that allows developers to more easily and quickly build machine learning models, without getting into the nitty-gritty of the underlying algorithms. Some of the key features of a good machine learning framework are:
- Optimized for performance
- Developer friendly (This framework utilizes traditional ways of building models.)
- Easy to understand and code on
- Not completely a black box
- Provides parallelization to distribute the computation process
IBM Brings AI Benefits to Business
Overall, an efficient ML Framework reduces the complexity of machine learning, making it accessible to more developers. With IBM’s Watson Machine Learning Accelerator, a new piece of Watson Machine Learning makes deep learning and machine learning more accessible to your staff and brings the benefits of AI into your business. It combines popular open-source deep learning frameworks, efficient AI development tools and accelerated IBM Power Systems servers.
Now your organization can deploy a fully optimized and supported AI platform that delivers blazing performance, proven dependability and resilience. Watson Machine Learning Accelerator is a complete environment for data science as a service, enabling your organization to bring AI applications into production.
Last modified: August 23, 2019