Self-driving or driverless cars are vehicles that can travel along a pre-established route with no human assistance. Most self-driving cars in existence today do not rely on a single sensor and navigation method and use a variety of technologies such as radar, sonar, lidar, computer vision, and GPS. As...
Wednesday, September 30, 2020
Tuesday, September 29, 2020
Digital personal assistants and chatbots
Unfortunately, it is still all too common for some call centers to use legacy Interactive Voice Response (IVR) systems that make calling them an exercise in patience. However, we have made great advances in the area of natural language processing: chatbots. Some of the most popular examples are:Google...
Monday, September 28, 2020
DEEP NEURAL NETWORKS
A deep neural network (DNN) is an ANN with multiple hidden layers between the input and output layers. Similar to shallow ANNs, DNNs can model complex non-linear relationships.The main purpose of a neural network is to receive a set of inputs, perform progressively complex calculations on them, and...
Saturday, September 26, 2020
The machine learning systems
Machine Learning is another drifting field nowadays and is the utilization of artificial knowledge. It utilizes specific statistical algorithms to make computers work with a particular goal in mind without being unequivocally customized. The algorithms get an input worth and anticipate an output for...
Friday, September 25, 2020
The societal implications of AI- Changing work
When an early human learned to use a sharp rock to crack open bones of dead animals to access a new source of nutrition, time and energy was released for other purposes such as fighting, finding a mate, and making more inventions. The invention of the steam engine in the 1700s tapped into an easily...
Thursday, September 24, 2020
The societal implications of AI- Seeing is believing — or is it?
We are used to believing what we see. When we see a leader on the TV stating that their country will engage in a trade-war with another country, or when a well-known company spokesperson announces an important business decision, we tend to trust them better than just reading about the statement second-hand...
Wednesday, September 23, 2020
The societal implications of AI - Algorithmic bias
AI, and in particular, machine learning, is being used to make important decisions in many sectors. This brings up the concept of algorithmic bias. What it means is the embedding of a tendency to discriminate according ethnicity, gender, or other factors when making decisions about job applications,...
Tuesday, September 22, 2020
Predictions of AI - Terminator isn't coming
One of the most pervasive and persistent ideas related to the future of AI is the Terminator. In case you should have somehow missed the image of a brutal humanoid robot with a metal skeleton and glaring eyes...well, that’s what it is. The Terminator is a 1984 film by director James Cameron. In the...
Monday, September 21, 2020
About predicting the future - how AI will transform our lives
While some forecasts will probably get at least something right, others will likely be useful only as demonstrations of how hard it is to predict, and many don’t make much sense. What we would like to achieve is for you to be able to look at these and other forecasts, and be able to critically evaluate...
Sunday, September 20, 2020
Generative adversarial networks (GANs)
Having learned a neural network from data, it can be used for prediction. Since the top layers of the network have been trained in a supervised manner to perform a particular classification or prediction task, the top layers are really useful only for that task. A network trained to detect stop signs...
Saturday, September 19, 2020
Convolutional neural networks (CNNs)
Why we need CNNsCNNs use a clever trick to reduce the amount of training data required to detect objects in different conditions. The trick basically amounts to using the same input weights for many neurons – so that all of these neurons are activated by the same pattern – but with different input pixels....
Friday, September 18, 2020
A simple neural network classifier
To give a relatively simple example of using a neural network classifier, we'll consider a task that is very similar to the MNIST digit recognition task, namely classifying images in two classes. We will first create a classifier to classify whether an image shows a cross (x) or a circle (o). Our images...
Thursday, September 17, 2020
Putting neurons together: networks
A single neuron would be way too simple to make decisions and prediction reliably in most real-life applications. To unleash the full potential of neural networks, we can use the output of one neuron as the input of other neurons, whose outputs can be the input to yet other neurons, and so on. The...
Wednesday, September 16, 2020
Perceptron: the mother of all ANNs
The perceptron is simply a fancy name for the simple neuron model with the step activation function we discussed before. It was among the very first formal models of neural computation and because of its fundamental role in the history of neural networks, it wouldn’t be unfair to call it the “mother...
Tuesday, September 15, 2020
How neural networks are built
The basic artificial neuron model involves a set of adaptive parameters, called weights like in linear and logistic regression. Just like in regression, these weights are used as multipliers on the inputs of the neuron, which are added up. The sum of the weights times the inputs is called the linear...
Monday, September 14, 2020
What is so special about neural networks?
The case for neural networks in general as an approach to AI is based on a similar argument as that for logic-based approaches. In the latter case, it was thought that in order to achieve human-level intelligence, we need to simulate higher-level thought processes, and in particular, manipulation of...
Sunday, September 13, 2020
What are neural networks?
A neural network can mean either a “real” biological neural network such as the one in your brain, or an artificial neural network simulated in a computer. Isolated from its fellow-neurons, a single neuron is quite unimpressive, and capable of only a very restricted set of behaviors. When connected...
Saturday, September 12, 2020
The limits of machine learning
In addition to the nearest neighbor method, linear regression, and logistic regression, there are literally hundreds, if not thousands, of different machine learning techniques, but they all boil down to the same thing: trying to extract patterns and dependencies from data and using them either to...
Friday, September 11, 2020
Logistic regression
Linear regression is truly the workhorse of many AI and data science applications. It has its limits but they are often compensated by its simplicity, interpretability and efficiency. Linear regression has been successfully used in the following problems to give a few examples:prediction of click rates...