Artificial intelligence (AI) is the creation of machines that have human-like intelligence and that can reason, learn, perceive, and interpret natural language or plan. AI examples that are common today include self-driving cars and chess-playing computers that heavily rely on natural language processing (interactions between computers and human (natural) languages) and deep learning.
AI is further broken down to general AI and narrow AI. General AI is not domain specific, or rather, it performs tasks anywhere. Narrow AI, on the other hand, performs specific tasks in a domain; for instance, language translation. AI popularity was highly boosted by innovation in algorithms, improved computing power and storage, and increased data volumes.
- Innovative Algorithmic - Improved machine learning techniques in deep learning or layered neural networks inspire new services and boosts research and investments in different parts of the field.
- Improved Computing Power - Increased powerful computers that connect remote processing power via the internet makes machine learning techniques that produce numerous data possible.
- Increased Data Volumes - There are more than 3 billion individuals online, and 17 billion devices and sensors connected. For this reason, there are large volumes of data that are easily accessible due to decreased storage costs. The information acts as training data for developing new rules, and learning algorithms to perform complex tasks.
Artificial intelligence evolved in 1956 but has become popular in recent years. Traditional AI in the 1950s dealt with topics such as symbolic and problem-solving methods. In the 1960s, the United States Department of Defense showed interest in AI and trained computers to imitate human reasoning.
The early innovations allowed formal reasoning and automation that's seen in computers today. An excellent example is a smart search system and support systems designed to augment and complement human intelligence.
Science fiction novels and movies depict Artificial Intelligence as human robots that control the world. However, modern AI is not scary or exaggerated. It's meant to provide specific benefits in all industries, including the translation industry.
Examples of where Artificial Intelligence is Applied
Currently, in large manufacturing companies, Artificial Intelligence is mainly used in the production units as robots that give specific shapes to an object, to move objects from one place to another and as conveyor belts among other uses, for instance in the car industry where robotic arms build a car.
Artificial intelligence is vital in enabling communication service providers to create self-optimizing networks. The operators will automatically improve network quality based on traffic data by time zone and region. AI technologies in the telecommunication field use advanced algorithms to unlock patterns within the data. Telecoms can thus predict and detect network anomalies for correction by operators before negatively impacting customers.
Digital Service Providers
Through Artificial Intelligence, real-time customer-related data is adequately analyzed to predict and identify customer satisfaction. This application is vital for Digital Service Providers who want to respond appropriately to problems and provide the right solutions to their customers instantly.
Network Service Providers
Artificial Intelligence automates issue resolution in the Network and Service Operations Centers by noting the cause and prompting corrective actions. This feature is vital in service assurance and end-to-end security management. AI can also predict capacity constraints and future shortcomings.
Communication Service Providers
Communication service providers serve many customers handling numerous endless daily transactions that are prone to human error. RPA is a type of automation technology based on Artificial Intelligence. Using RPA helps telecoms manage back-office activities and repetitive and rule-based operations efficiently. Through streamlining the management of complex, time-consuming, and labor-intensive activities such as data entry, billing, order fulfillment, and employee management, Robotic Process Automation frees CSP staff for better work.
Artificial Intelligence boosts customer interaction mechanisms such as chatbots to improve self-care activities and handle support requests. It also automates network resolutions and customer service issues. AI prevents future issues by analyzing network evolution.
All these industries will either need the data generated, the computer programs, or the customer-facing information translated. In turn, the translation industry is also applying AI in the form of Neural Machine Translation. We can now translate millions of words faster and better than ever before.
If you are facing the challenge of translating large volumes of words and want to test whether machine translation could be a solution, check out our latest case study on Deployment of Machine Translation.