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AI Successes and Failures
Most of us have used artificial intelligence (AI) whether we are aware of it or not. If you have ever used or interacted with applications and services such as online shopping, smart phones, Google assistant, Amazon alexa then you have used AI without a doubt.
AI market value is expected to reach $60 billion by 2025 with the race between the USA and China being the most prominent. AI digital assistants are expected to see the highest growth rate over the next 5 years. Looking over the period 2019-2024, autonomous robots, digital assistants and neurocomputers have the highest share of the smart machine market.
However, are AI applications always successful? Are there failures? How can we avoid failures? What are the top rules for AI success?
AI contribution to Trading and Shipping: a myth or reality?
There is a lot of hype around AI in business. Trading and Shipping are no exception. AI contribution ranges from trading operations to regulatory compliance, however there are downsizes too.
What is artificial intelligence?
AI is defined as “the science and engineering of making intelligent machines.”- John McCarthy, 1956. It is based on several foundations such as mathematics, statistics and neuroscience. In 1956, a programme called Logic Theorist was the first artificial intelligence programme created. It has proved 38 of the first 52 theorems in chapter 2 of the Principia Mathematica.
However, rapid advances in data storage and computer processing power have significantly increased the rate of acceleration of artificial intelligence.
Is deep learning a friend or a foe?
The hype around AI continues. Deep learning has become almost a synonym for AI despite the so many other techniques that exist within the machine learning field.
So, if you are trying to apply deep learning, would not you want to know if deep learning is appropriate for your application? In this article you will learn about deep learning and the three simple questions to ask before you start.
What is deep learning?
Deep learning is a subset of machine learning. It is based on artificial neural networks that mimic biological neural networks of the human brain. At the basic level is the perceptron and the mathematical representation of a biological neuron.
Is artificial intelligence a waste of time?
There is a lot of hype around the future of AI, the debate is split between the optimists who see AI as the solution to everything and the pessimists who see AI as a major threat. The ones in the middle remain silent as they are confused and don’t know where to start.
So, if you are a business looking to apply AI to drive value: how can you ensure that your endeavor does not turn into a big failure? In this article you will learn about AI successes & failures and how to avoid wasting your time by following few simple rules.
Most of us have used artificial intelligence whether we are aware of it or not. If you have ever used smart phones, Google assistant, Amazon Alexa then you have used AI without a doubt. AI has been used in several applications such as: voice recognition, medical diagnosis, automotive and manufacturing.
Demystifying Machine learning and R
Artificial intelligence is based on several foundations such as mathematics, statistics and neuroscience. Its main objective is to study agents that perceive their environments and make decisions. Artificial intelligence includes several fields such as machine learning, natural language processing and robotics.
Machine learning is a subset of artificial intelligence and it is a key enabler to achieve artificial general intelligence. This article describes the basics of machine learning and discuss how R can be used to build models and algorithms.
Machine learning algorithms find natural patterns in data, which helps generate insight and make better predictions and decisions. They are used in different applications such as: