Blogging Community AI Archives - Page 2 of 4 - Technologies In Industry 4.0

The Graphical Model in Machine Learning

The Graphical Model in Machine Learning

Introduction The Graphical model is a subdivision of Machine Learning. It uses a graph to signify a domain problem. A graph states the conditional need structure between random variables. These are being used in many Machine Learning algorithms. For example; Naive Bayes’ algorithm The Hidden Markov Model Restricted Boltzmann machine Neural Networks In this article, … Read more

Artificial Intelligence in Buyer’s Hands

Cloud TPU programming modelCloud TPU programming model

Introduction Artificial Intelligence in Buyer Hands has unveiled a star Pixel smartphone. That is powered by its first mobile chip. This is an amazing step to put artificial intelligence in buyer’s hands. Google is driving the focus on the new system on a chip (SoC). That would be inside the new Pixels. This is named … Read more

How Cognitive Computing Works?

How Cognitive Computing Works?

What is Cognitive Computing? Cognitive computing is the use of computerized models to simulate the human thought process in complex situations where the answers may be ambiguous and uncertain. The phrase is closely associated with IBM’s cognitive computer system, Watson. Cognitive computing overlaps with AI and involves many of the same underlying technologies to power … Read more

Artificial intelligence in Cyber security

Introduction Artificial intelligence in Cyber security is the shield of computer systems and networks. This is protection from information revelation, stealing of or damage to their hardware, software, or electronic data, along with the disturbance or misdirection of the facilities they provide. This field is charming and progressively important due to the increased trust in … Read more

Deep learning for text and sequences

Deep learning for text and sequences

Introduction Deep-learning models that would process text either understood as sequences of word or sequences of characters, statistic, and sequence data generally. The two important deep-learning algorithms for sequence processing are recurrent neural networks and 1D convnets. We’ll discuss both of those approaches. Applications of those algorithms include the following: Document classification and statistic classification, … Read more

Cognitive Flexibility

Cognitive Flexibility

“Being ignorant is not so much a shame, as being unwilling to learn.” Benjamin Franklin Introduction Cognitive flexibility is an intrinsic property of a cognitive system often related to the capacity to regulate its activity and content, switch between different task rules and corresponding behavioral responses, retain many concepts simultaneously, and shift inside attention between … Read more

Supervised Learning Algorithms

Supervised Learning Algorithms

 Introduction Supervised learning algorithms are, roughly speaking, learning algorithms that learn to associate some input with some output, given a training set of samples of inputs x and outputs y. In different cases, the outputs y could also be difficult to gather automatically and must be provided by a person’s “supervisor,” but the term still applies even when the training set targets were … Read more