There are plethora of real-world applications of AI systems today offering many opportunities in this field, says DR ABHILASHA GAUR
Artificial intelligence leverages the computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. There are numerous, real-world applications of AI systems today. Below are some of the most common examples:
Speech recognition: It is also known as automatic speech recognition (ASR), computer speech recognition, or speech-to-text, and it is a capability which uses natural language processing (NLP) to process human speech into a written format. Many mobile devices incorporate speech recognition into their systems to conduct voice search. This technology is evaluated on its accuracy rate— word error rate and speed. A number of factors can impact word error rate like pronunciation, accent, pitch, volume, and background noise.
Customer service: Online virtual agents are replacing human agents along the customer journey. They answer frequently asked questions like shipping, or provide personalised advice, cross-selling products or suggesting sizes for users, changing the way we think about customer engagement across websites and social media platforms. The AI takes data and uses it to identify the best representative available to address the customer’s needs. It then provides the rep with necessary background information before they interact with the customer. This saves time, manpower and helps customer address issues efficiently.
Computer vision: This AI technology enables computers and systems to derive meaningful information from digital images, videos and other visual inputs, and based on those inputs, it can take action. This ability to provide recommendations distinguishes it from image recognition tasks. Powered by convolutional neural networks, computer vision has applications within photo tagging in social media, radiology imaging in healthcare, and self-driving cars within the automotive industry. Computer vision needs lots of data. It runs analyses of data over and over until it discerns distinctions and ultimately recognise images. Real-world applications demonstrate how important computer vision is to endeavours in business, entertainment, transportation, healthcare and everyday life.
AI optimised hardware: The upcoming AI-devices of the digital world are focused on being structured and are used to execute AI-oriented tasks specifically. They have improved graphics and central processing units that accelerated the next generation of application advancements. One avenue is to increase the performance and throughput of the systems to speed up training and to enable the training of more complex models. Graphics Processing Units are playing an important role to accelerate training and inference because of their high degree of parallelism and because they can be optimised for neural network operations.
AI in agriculture: Automation in agriculture is an emerging subject across the world. In recent time, Artificial Intelligence has been seeing a lot of direct application in farming AI-powered solutions will not only enable farmers to do more with less, it will also improve quality and ensure faster go-to-market for crops. The AI is being used by the agriculture industry to help produce healthier crops, control pests, monitor soil and growing conditions, organise data for farmers, reduce effort, and improve a wide range of agriculture-related operations.