Artificial intelligence
Artificial intelligence
Artificial intelligence (AI) is a process of imitating human intelligence based on the creation and application of algorithms executed in a dynamic computer environment. Its goal is to enable computers to think and act like human beings.
To achieve this, three components are required:
- Computer systems
- Data with management systems
- Advanced AI algorithms (code)
To get as close as possible to human behavior, artificial intelligence needs a high amount of data and processing capacity.
What are the origins of artificial intelligence?
Since at least the first century B.C., humans have been working on creating machines that can imitate human reasoning. The term "artificial intelligence" was coined more recently, in 1955 by John McCarthy. In 1956, John McCarthy and his collaborators organized a conference called the Dartmouth Summer Research Project on Artificial Intelligence, which gave rise to machine learning, deep learning, predictive analytics, and, more recently, prescriptive analytics. A new field of study has also emerged: data science.
Why is artificial intelligence important?
Today, humans and machines generate data faster than it is humanly possible to absorb and interpret it to make complex decisions. Artificial intelligence is the basis of all computer learning and represents the future of complex decision making. For example, most humans can learn not to lose in a simple game of tic-tac-toe, when there are 255,168 possible actions, 46,080 of which lead to a draw. In contrast, checkers champions are rarer, since there are more than 500 x 1018 (500 trillion) possible moves. Computers are able to calculate these combinations and the best possible permutations very efficiently, in order to make the right decision. AI (with its logical evolution, machine learning) and deep learning represent the future of decision making.
Uses of artificial intelligence:
AI is present in our daily life. For example, it is used by financial institutions' fraud detection services, for predicting purchase intentions and in interactions with online customer services. Here are some examples:
- Fraud detection. In the financial industry, artificial intelligence is used in two ways. Applications that score credit applications use AI to assess consumer creditworthiness. More advanced AI engines are responsible for monitoring and detecting fraudulent credit card payments in real time.
- Virtual Customer Service (VCS). Call centers use VCS to predict and respond to customer requests without human intervention. Voice recognition and a human dialogue simulator are the first point of interaction with customer service. More complex requests require human intervention.
- When an Internet user opens a chat window on a web page (chatbot), the interlocutor is often a computer running a specialized form of AI. If the chatbot fails to interpret the question or solve the problem, a human agent takes over. These interpretation failures are sent to the machine learning system to improve future interactions of the AI application.
NetApp and Artificial Intelligence:
As the gold standard for data management in the hybrid cloud, NetApp understands the importance of data access, management, and control. NetApp® Data Fabric provides a unified data management environment that spans endpoints, data centers, and multiple hyperscale clouds. It enables organizations of all sizes to accelerate business-critical applications, improve data visibility, optimize data protection, and enhance business agility.
NetApp AI solutions are built on key building blocks:
ONTAP® software enables AI and deep learning to be leveraged locally and in the hybrid cloud.
100% Flash FAS systems accelerate AI and deep learning workloads while eliminating performance bottlenecks.
ONTAP Select software enables efficient data collection at the edge using IoT endpoints and aggregation points.
Cloud Volumes can be used to quickly create prototypes for new projects. It allows AI data to be received and sent to and from the cloud.
NetApp has also begun to integrate Big Data analytics and artificial intelligence into its own products and services, including Active IQ®, which uses billions of data points, predictive analytics, and a powerful machine learning engine to provide proactive customer support recommendations for complex IT environments. Active IQ is a hybrid cloud application built using the same NetApp products and technologies that our customers use to build their AI solutions in multiple domains.
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