The term Artificial Intelligence(AI), refers to the simulation of human intelligence by machines or in other words, AI is software that imitates human behaviors and capabilities. Technologies or workloads that come under AI include machine learning and deep learning, Natural Language Processing(NLP), Document Intelligence, Computer Vision, Knowledge Mining, Generative AI etc.
Machine Learning – This is the foundation for an AI system, and is the way we “teach” a computer model to make predictions and draw conclusions from data. Machine learning enables software applications to become more accurate at predicting outcomes without being explicitly programmed to do. It uses historical data as input to predict new output values. This approach became more effective with the rise of large data sets to train on.
Computer vision – Capabilities within AI to interpret the world visually through cameras, video, and images. In other words, it helps computers to derive information from images and videos.
Natural Language Processing(NLP) – Natural language processing – This Capabilities ability to interpret written or spoken language, and respond in kind. It helps machines process and understand the human language so that they can automatically perform repetitive tasks.
Document Intelligence – This deal with managing, processing, and using high volumes of data found in forms and documents. It helps in automate processing for contracts, health documents, financial forms and more
Knowledge Mining – This is related to extracting information from large volumes of often unstructured data to create a searchable knowledge store.
Generative AI – Create original content in a variety of formats including natural language, image, code, and more. It takes natural language input, and return appropriate responses in a different formats including natural language, image, code, and audio.
Key Challenges and Risks in Artificial Intelligence Systems
Artificial Intelligence(AI) is a great tool and can be used for the benefit of humans. But like any other systems its also has many challenges and risk and must be used in a responsible way. Some of the keay challenges and risk which I forsee are as follows:
- Data privacy issues especially in health care, banking and legal.
- Bias due to improperly trained algo and or gender bias.
- Misuses due to deepfakes and phishing
- Elimination of some jobs. This risk may be short term. As we adopt more and more AI, there will be options in some other fields which are now not common. Remember the grand old days when we had typewriters and demand for shorthand.
Some Key Advantages
- It helps reduce errors in repetitive tasks as we can automate it.
- Saves labour costs and improve productivity
- Reduce time for data heavy tasks.
Artificial Intelligence(AI) Tools and Services
ChatGPT from OPenAI and Bard from Google are few of the most popular Generative AI tools. Computer Vision is used in test automation tool to recognize elements when traditional methods fails. Used in tools like UI Path. It is also used in face detection and reading vehicle number plates. Then comes Office 365 and Windows CO-Pilot.