As we move forward into 2022, artificial intelligence will be the most transformative technology developed by humans. The impact of which will be greater than that of fire or electricity on our development as a species. While it may seem like an overstatement, the potential is evident. In this article by Jelani Harper at InsideBigData, we will discuss the latest Artificial Intelligence and Machine Learning trends.
In 2022, AI and ML breakthroughs and new developments will continue to push the boundaries. They will provide many use cases that enforce AI’s respective connectionist and reasoning approach.
Advanced Application of AI Intelligence and Machine Learning:
Composite AI employs the most suitable AI methodology for a specific use case. Such options include text analytics, supervised learning, traditional machine learning like predictive modeling, forecasting, etc. Neuro-symbolic AI combines AI’s statistic and reasoning capabilities within the same deployment. This presents a range of AI’s versatile benefits, as given below:
Natural Language technologies aim to create machines that can read, understand and respond to text and voice data.Feature Engineering enhances the predictive power of the learning algorithm.Routing and Network Optimization chooses the best routing paths to reduce costs, improve network efficiency and performance.Security averts cyberattacks by combining machine learning approaches with computer vision and neural networks.
In layman’s terms, machine vision is the “eyes” of a machine. Machine vision systems utilize digital input captured by cameras to determine actions. Businesses use them in various ways to improve quality, efficiency, and output.
Explainable AI (XAI)
It is a set of processes and methods that allow humans to understand. People understand words better than numbers, so reasoning systems use words that are comprehended by most people to understand the data in context.
This methodology optimizes the usage of models and applications across clouds, targeting machine learning and artificial intelligence models.
Vendors often use a company’s intellectual property to train and refine models. Therefore, companies should be careful about who owns that intellectual property.
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