1. What is cognitive computing?
In 2011, manufacturing floors throughout the country welcomed a new employee: a six-foot-tall, 300-pound robot outfitted with two long, dexterous arms and expressive digital eyes. Its name was Baxter.
Although Baxter’s success was short-lived, it ushered in a new era of automation in which machines could coexist securely and peacefully with people. The collaborative robot pushed the boundaries of what humans and robots can achieve together, thanks primarily to cognitive computing, which uses computational models to simulate the human brain.
“We are entering an age where cognitive computing in particular will unburden us and allow people to become more quintessentially human,” he told Built In. “And I’m not referring to the remote future. It’s already started, and we’re going to see it accelerate quickly.”
2. How does cognitive computing work?
Cognitive computing systems make use of artificial intelligence and its various underlying technologies, which include neural networks, natural language processing, object recognition, robotics, machine learning, and deep learning. Combining these processes with self-learning algorithms, data analysis, and pattern recognition, as well as constantly ingesting new information, allows computers to “think” about issues and find answers.
Muddu Sudhakar, CEO of the technology startup Aisera, compares cognitive computing to the process of training a child. People use visuals and words to instruct youngsters as they get older. In cognitive computing, this is referred to as ontology, or teaching what is. People often utilize dictionaries and books to teach youngsters not only what certain words mean but also their context—a process known as taxonomy. For example, “weather” refers to things like temperature, precipitation, and seasons. People also teach children by modeling desired conduct and discouraging undesirable behavior. Reinforcement learning is a term used in cognitive computing.
Sudhakar told Built In that a system capable of interacting with humans can be created by combining basic knowledge, ontology, and taxonomy with reinforcement learning.
3. Cognitive computing vs. artificial intelligence.
If this sounds a lot like artificial intelligence, you’re not mistaken. Cognitive computing and artificial intelligence are commonly used interchangeably; however, they are not the same.
AI is a broad term used to describe technologies that use massive volumes of data to model and automate operations that would normally need human intelligence. Classic examples include chatbots, self-driving automobiles, and smart assistants such as Siri and Alexa. Cognitive computing requires human aid to imitate human cognition, while artificial intelligence relies on algorithms for decision-making.
This means that systems must be adaptable and change their behavior in response to new knowledge and changing circumstances. They must also be able to recall information from previous experiences, ask clarifying questions, and understand the context in which information is employed. AI is one of the foundational components that enable all of this.
“The question for cognition is if it can have its own intelligence. That is where artificial intelligence (AI) comes in. What intelligence can we bring to the system?” Sudhakar said.
4. Cognitive Computing Applications.
Single-purpose demonstrations are among the most well-known instances of cognitive computing. In 2011, IBM’s Watson computer won a round of Jeopardy! While running Deep QA software, which has been given billions of pages of data from encyclopedias and open-source projects. In 2015, Microsoft launched how-old.net, a popular age-guessing application that uses uploaded images to calculate a person’s age and gender.
5. Cognitive Computing for Healthcare.
Cognitive computing’s ability to process massive volumes of data has proven to be quite valuable in the healthcare profession, notably in diagnostics. Doctors may utilize this technology to not only make better diagnoses for their patients but also to build more personalized treatment programs for them. Cognitive systems may detect anomalies in patient images, including X-rays and MRI scans, that human experts may overlook.
6. Cognitive Computing for Finance.
In finance, cognitive computing is used to collect client information so that businesses may provide more personalized suggestions. Furthermore, by merging market trends with customer behavior data, cognitive computing can assist financial institutions in assessing risk. Finally, cognitive computing can assist businesses in preventing fraud by evaluating previous parameters that can be used to detect fraudulent transactions.
Despite being famous for Jeopardy! IBM Watson is part of the IBM Cloud, which was used by 42 of the top 50 Fortune 500 banks in 2021. Expert systems convert words into data for many finance applications, such as insurance and banking.
7. Cognitive Computing for Manufacturing.
Manufacturers employ cognitive computing technology to maintain and repair machinery and equipment, as well as to improve manufacturing times and manage parts. Once commodities are manufactured, cognitive computing may assist with the logistics of transporting them around the world through warehouse automation and administration. Cognitive technologies can also assist personnel along the supply chain in analyzing structured or unstructured data to find patterns and trends.
IBM has named this area of cognitive computing “cognitive manufacturing” and provides a suite of solutions through its Watson computer, including performance management, quality improvement, and supply chain optimization. Sawyer, Baxter’s one-armed successor, is redefining human-machine collaboration on the production floor.