Artificial Intelligence and Machine Learning
Ian is tech specialist. Artificial intelligence and machine learning and trending technologies.
Artificial Intelligence
What is artificial intelligence?
AI is a branch of computer science that deals with equipping machines to behave like a human being. AI aims to create a system that can perform exactly like a human being. AI presents itself in many ways, including search predict technology, automated cars, robotic processing automation, and virtual assistant.
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Types of Artificial Intelligence
1. Reactive machines
They sense external impulse or reaction and plan a suitable action. They perform specialized duties and can only understand the tasks presented to them. They provide consistent behavior, provided the situation is repetitive. In the 20th century, IBM designed a reactive machine named Deep Blue; its role was to play chess, predicting chess moves by planning down each piece's board placement.
2. Limited memory
A limited memory machine collects recent observations to arrive at an informed decision. The machine prioritizes observational data into their pre-programmed conceptual framework. They only retain this data for a short period, after which they forget.
3. Theory of mind
The theory of mind machine can create thoughts and decide as per the contextual context.; Thus, they can take part in social interaction. These machines are still in their primary stages; however, many can mimic a human being. For instance, consider voice assistance applications. It can handle basic speech prompts and directions but cannot save a conversation.
4. Self-awareness
These machines their intelligence through the formation of ideas, desires, and understanding their inner states. In early 1940, Allan Turing designed the Turing test to illustrate that machines could behave exactly like a human being.
Achieving Machine Learning?
The best way to understand how machines learn is by comparing them with human learning. For example, consider a person learning how to control a car. The person boards the car, grip the steering and hopes to stay focused and in control. This person does not learn how to operate a car by understanding the jet's physics but rather via trial and error.
Over time the person gets used to operating the jet. This is what is known as repetitive stimulation. Machines learn through the following ways:
1. Supervised Learning
This is the most utilized form of learning in artificial intelligence. The machine derives labeled sets of input and output. Regression is used when dealing with numerical data sets. However, classification is used when dealing with categorized variables. Models are always adjusted in case they provide an incorrect response to provide an accurate answer.
2. Unsupervised Learning
In this form of learning, a machine translates data into information. Clustering and association are the main methods used. Clustering puts together similar variables, whereas association pins down correlation among data sets. Unsupervised learning can be used while transforming large data sets into useful information.
3. Reinforcement Learning
In this form of learning, the system automatically responds to external force and is conditioned to respond to occasional rewards and punishment. Reinforcement learning aims to create a machine that can independently act on its own.
What do we expect from Artificial Intelligence in the future?
Rapid development and growth of artificial intelligence will give rise to an appealing milestone on productivity, employment, and competition. However, the future of artificial intelligence is still controversial. The following are expected developments:
1. Impact on Productivity
Increased productivity means there would be satisfied customers and a reliable cooperate profitability. For example, in the flight sector, artificial intelligence will ensure customer satisfaction through a faster and accurate schedule of the flights. Profit will rise since jobs will be automated.
2. Impact on Employment
The growth of AI will lead to the growth of high-paying jobs that will require high-level skills. This means that artificial intelligence will automate low skills jobs hence job loss for less skilled people.
3. Impact on Competition
As companies struggle to adopt AI. They will tend to adopt automation of tasks to optimize labor and capital. Once this technology is stable, more institutions and companies will opt for the new technology, hence losing jobs and increased profit.
4. AI Impact on Infrastructure
AI will demand more resources; AI needs massive computing power. To avail this, the organization need could computing services or servers. Training the AI need a massive amount of data, hence demand more storage space. The necessity of AI in security, the AI compiles a vast amount of data hence becomes impossible to be analyzed by human beings. Intelligent storage, storage management will be revolutionized through machine learning and IO devices. IT will enable the system to make intelligent decisions in the future. Prediction and prevention of failures, AI algorithms will be able to compute and solve a problem within a small amount of time. Reduce dependency on humans and saving cost; most of the process will be automated hence reduced workers.
Conclusion
This theory and development with advantages and disadvantages. But in the long run, we have to accept that technology is a good thing, and we must embrace it.
This content is accurate and true to the best of the author’s knowledge and is not meant to substitute for formal and individualized advice from a qualified professional.
© 2020 Ian Muiruri
