Artificial Intelligence is a term that specifies Intelligence revealed by machines as compared to natural intelligence demonstrated by humans. They are programmed in such a way that we can make machines to think like a human brain, as the name specifies. It is the ability of a digital computer or a robot to perform the task as expected. The field encompasses computer science and robust datasets for solving real-world problems.
Main Characteristics of AI include
- Feature Engineering
- Artificial Neural Networks.
- Deep Learning.
- Natural language processing.
- Intelligent Robotics.
- Perception.
- Automate Simple and Repetitive Tasks
- Data Ingestion
Limitations
- Not expressive/self-explanatory: AI cannot draw a conclusion about how and why it reached that particular state. It keeps users blind due to its in black-box nature.
- Data Temperament Issue: AI sometimes proves to be a threat to national security if the highly sensitive data is utilized in government bodies or big ventures or in any machinery of governance.
- Inaccurate data analysis: AI can only do the analysis and drew the result based on the data that WE provide. It filters out everything that is not given as input. So the unreliable or skewed data might hamper the overall end result.
Cognitive Computing is the use of algorithmic models that simulates the human brain under complex circumstances where the responses might be questionable and dubious. They are quicker than a person at handling and ascertaining, yet they still can’t seem to dominate tasks, like figuring out normal language and perceiving objects in a picture. Some features of CC are: interactive, adaptive, stateful, iterative, and contextual. Human beings can interact with the cc system via GUI or any other interface.
Limitations
- Vulnerable to breaches since it handles a large amount of data.
- Complex training process is time-consuming, lengthy and tedious. Needs a particular and huge volume of data until the model perfectly understands and generates the desired outcome.
- Voluntary adoption in government, enterprise or other organizations as people think they would replace humans.
- Not dynamic and non-adaptability to changing environments.
Cognitive computing and AI are used interchangeably but their way of approaching the task creates the basic differences
| S.No. |
Artificial Intelligence |
Cognitive Computing |
|---|---|---|
| 1. | Algorithm of AI generates the most accurate result without the utilization of human input. | Based on human input i.e. thinking, reasoning, and belief to generate output |
| 2. | AI is autonomous | Cognitive is dependent |
| 3. | Machine as an author of its own actions. It does the work of the human brain | Machine as an agent of some business process or intention of a human being. It is just an information tool. |
| 4. | It reflects the reality | It copies human behaviour |
| 5. | AI itself generates the algorithm to produce end results and decisions | It generates only the information and allows the end result to be interpreted by humans itself |
| 6. | Utilizes pre-trained algorithms | Utilizes prediction and analysis as a basic tool. |
| 7. | To produce results, AI finds the hidden information and uses a specific pattern | To generate solutions, it imitates the human thought process. Helps for smarter decisions |
| 8. | Retail, finance, and manufacturing security are a few areas that use AI | Enhances process across various fields viz. industries, customer service, health care |
| 9. | Job of AI is to make our work easier | If we complex human-like decisions, Cognitive comes into hand |
| 10. | Technologies, where AI is utilized, are NLP, speech recognition, image processing, video analytics, chatbots | Cognitive shines when there is a need for sentiment analysis, facial recognition, fraud detection, risk assessment, |
Similarity
The similarity between the two is based on the ability of machines to act, adapt, and reason based on experience it has learned. They are similar in intent and dissimilar in their approaches in interacting with humans. Both these technologies are in the growing phase for rapid advancements. Deep learning, machine learning, and neural network are the common technologies behind Cognitive Computing and AI.