Best in Technology – Artificial intelligence and Machine learning

Artificial Intelligence and Machine Learning generally interest and astonish us with their advancements. Computer-based intelligence and Ml have arrived at ventures like Customer Service, E-business, Finance and where not. By 2020, 85% of the client connections will be overseen without a human. There are sure ramifications of AI and ML to consolidate information investigation like Descriptive examination, Prescriptive investigation, and Predictive investigation talked about in our next blog.

WHAT IS ARTIFICIAL INTELLIGENCE (AI)?

Artificial intelligence can be considered as the intelligence displayed by scientific machines as opposed to the natural intelligence displayed by humans and animals. Artificial intelligence is sometimes called that intelligence exhibited by programmed scientific gadgets such as robots, whereby they can perform like humans in terms of cognition that they perceive its environment and take steps helps it achieve its goal.

Artificial intelligence is sub-divided into different sections such as reasoning, knowledge representation, planning, machine learning, natural language processing, perception, and the ability to move and manipulate objects. Most work in the 21st century in a developed society is done by most AI machines and the has helped in more production of things in the world.

Artificial intelligence and Machine learning

AI nuclear energy background, future innovation of disruptive technology

BENEFITS OF AI TECHNOLOGY:

AI technology has been one of the developments of modern society since its inception in the 90s. most of the companies and manufacturing hubs in the developing countries make use of AI technological machines in production and this has made the product to be much easier easing the stress of manual labor and advancing their production such that they produce more products with ease.

AI has also helped us in terms of our internet networking and normal life activities this has been proven by the establishment of mobile gadgets such as mobile phones, laptop, game console, etc. these appliance has made life so easy for us that we don’t need to travel miles to pass a piece of information to someone, stress our brains so much on school activities and we still get relaxed fro our home through the use of game consoles.

CHALLENGES OF AI TECHNOLOGY:

In as much as we agree the world is being developed through the innovation of AI technology, we also consolidate the fact that it is also affecting our lives and making some people impoverished. The AI technology brought about unemployment in terms of manufacturing companies to those people who filled their position in the companies thus increasing the rate of unemployment in the employme3nt market.

AI technology has also brought about laziness especially in the youth such that they are not ready to use their initiative in most things being done rather spend most of their time on social media and depend 80% on the internet for most things they ought to do such as assignment, projects, etc. AI technology has brought challenges to our normal activities though.

WHAT IS MACHINE LEARNING?

Machine learning is a branch of artificial intelligence that makes use of algorithms to make machines work on their own, to be able to perform the task on their own without total control from the programmer. Machine learning algorithm builds a model known as training data, to make predictions or decisions without being explicitly told or programmed to do so. Most contemporary robots make use of machine learning, such that they can perform a task without a direct order from the programmer. It involves the computer learning how to perform tasks from the data provided for them.

APPROACHES TO MACHINE LEARNING

SUPERVISED LEARNING:

Supervised learning is the algorithm that builds example data input and the desired output required from the computer. The data is known as training data and consists of a set of training. These examples are represented by an array, while all data are represented by a matrix.

UNSUPERVISED LEARNING:

Unsupervised learning algorithms take only inputs data and find structure in the data like grouping or clustering of data points. The algorithms learn from test data that has not been labeled, categorized, or classified. The algorithm does not give feedback after the inputs rather identify the commodities and act depending on the presence and absence of the commodities in a new set of data.

REINFORCEMENT LEARNING:

Reinforcement learning is an approach of machine learning where software agents will have to take action to maximize some notion of cumulative reward in an environment. The environment is typically represented as a Markow decision process (MDP) when it comes to machine learning. Most reinforcement learning algorithm makes use of dynamic programming technique. It is used in autonomous vehicles or in learning to play a game against the opponent.

HOW OFTEN ARE ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING USED?

These two concepts work hand in hand with each other as one is part of the other. You cannot talk about using a machine learning algorithm without talking about using it under artificial intelligence, as it is part of artificial intelligence.

These two concepts are being used in almost all technological devices that we use in contemporary society. For instance, the vehicles we drive were built based on artificial intelligence and machine language such that we leave the car open for a long time, it will get locked by itself. Other instances are the phone and laptops we use, when not used for a long period will sleep by themselves without any touching them. Also, it is made evident in the video games we play.

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