Data Annotation Service Driving Factor Behind The Market

How AI Plays Major Role In Technology Industry

There is no doubt that Artificial intelligence, Machine Learning, and Deep Learning are changing the way we see computers. In earlier days of computers, who would have thought that humming a song on the phone can tell you the name of the song? Or that devices could talk to us? Or that AI can help retain existing customers and can even help attract new customers?

Nobody would have thought. But here we are today, and there are endless possibilities of things we can do and achieve through Artificial intelligence. But there’s a problem. Computers are dumb, they are still dumb machines. 

They don't know how to do things unless you teach them. And if you want your model to do certain things, you have to spoon-feed the information to the model. And the first step is to collect high-quality and accurate ai training dataset. Because these datasets can eventually help the AI to understand and do the things of your choice. 

What is Artificial Intelligence?

AI or artificial intelligence is a branch of computer science that creates and develops systems that can perform human-like tasks such as speech and text recognition, content learning, problem-solving, and more. By using AI-powered technologies, computers can complete tasks by analysing a huge amount of data and recognising different patterns. 

Segments of AI

AI In Technology is a big term, and it contains different segments like machine learning, deep learning, NLP (Natural Language Processing), Image processing, computer vision and more. 

1. Machine Learning: Machine Learning is a subset of AI, which allows software applications and AI models to predict outcomes for a situation using different methods.
2. Deep Learning: Deep learning is a subset of machine learning. The algorithms and techniques used by machine learning and deep learning are the same, but the capabilities are not. In Deep learning, the AI model learns how to perform tasks with the use of audio, text, images, or videos using a huge amount of labelled data and neural network architectures. 
3. Natural Language Processing (NLP): This allows the AI to understand the human language and manipulate it. This allows things like machine translation, Information retrieval, Sentiment analysis, answering of questions, and more.
4. Computer Vision: This allows computers to extract insights and useful data from images, videos and other types of visual data. 

Areas in which AI can be used?

There are many areas in which AI is used, like quality assurance, service management, process management and IT operations (AIOps).

• Quality Assurance: In quality assurance, there are many areas in which AI can be used:

1. Software testing: When a development team releases new code, it must test it before releasing it to the public. If regression testing is done manually by QA experts, it requires a lot of effort and time. This process can be made easier and faster because of AI's capacity to detect repeating patterns.
2. Application Testing: By analysing behavioural patterns depending on location, device, and demographics, an AI-based system creates test suites. This allows QA departments to streamline testing methods and improve application effectiveness.
3. Social Media Analysis: Artificial intelligence systems can analyse and evaluate massive amounts of data obtained through social media. The system may predict market trends and client behaviour based on these data, giving a company a competitive advantage.
4. Defect Analysis: In order to find faults or areas that require special attention, AI systems monitor and analyse data, then compare it to set parameters.
5. Efficiency Analysis: An AI system gives valuable information to QAs by evaluating and summarising pertinent data from a variety of sources, giving QA engineers a clear picture of the changes they must make. QAs can make better-informed decisions using this information.

• Service Management: Service management makes extensive use of AI technologies. Using AI for service automation allows businesses to better utilise their resources, resulting in faster, cheaper, and more effective service delivery.

1. Self-solving service desk: Companies can use AI to observe customer behaviour, provide suggestions, and, as a result, provide self-help alternatives to improve service management.

• Process Management: AI-powered automation will make it simple for IT organisations to automate numerous operational procedures, lowering costs and decreasing manual labour.

1. Computer engineering: An advanced AI system will soon be able to execute and control the software development cycle on its own, comprehending the fundamentals of the code. AI now assists human programmers in navigating the growing number of APIs, making writing easier for them.
2. Automated Network Management: AI helps companies run and manage their networks more efficiently. AI's machine learning skills enable it to detect problems as they arise and take the necessary steps to restore network stability.

• IT operation (AIOps): Gartner invented the term "AIOps," which refers to the use of artificial intelligence (AI) to manage information technology on a multi-level platform. To automate data processing and decision making, AIOps employs big data, analytics, and machine learning capabilities.

Applications of AI in the Technology industry

1. AI is already being used in industries like healthcare, Retail, E-Commerce, Food, Banking and Finance, Transportation, Real Estate, Entertainment, and more. For example, customer support can be improved through AI chatbots that can solve the query of a user by understanding the context of their problem. Hyper personalization can also be achieved through AI. 
2. The digital transformation and industries' revolutionary use of technology resulted in new technological developments to optimise and solve the industry's key concerns. Among all tech applications, AI is at the heart of every industry's deployment, with information technology at the top of the list. 
3. Integrating AI systems into IT helps developers work more efficiently, while also ensuring quality and increasing productivity. And, thanks to AI's sophisticated algorithmic functions, large-scale development, implementation, and deployment of IT systems that were before impossible are now possible.

How can GTS help you?

We at GTS understand the importance of high quality and accurate AI Training Dataset for your machine learning model. That’s why we provide the best datasets to train and validate your AI model. We provide different services like the collection and annotation of image datasets, video datasets, Text datasets and speech datasets. 

The information we gather is used in the development of artificial intelligence and machine learning. We have data on various languages spoken all over the world because of our global reach, and we use it expertly. We support more than 200 languages and our services are fast, reliable and we do all our work fully professionalism.