The Turing test was created by Alan Turing in the 1950s to examine a machine’s ability to exhibit human-level intelligent behaviour. He called it the imitation game. Here’s what it’s all about.

The test involves a human evaluator exchanging conversations with two entities. One would be another human, and the other would be a machine. If the human evaluator cannot distinguish the human from the machine, then the machine would have passed the Turing test.

The original Turing test proposed that the conversation happens through text channels to avoid the machine having to generate spoken words or look like a…

Different families of algorithms solve different problems. We don’t necessarily need to be experts in the details of each one, but having a grasp on what problems they can solve, and how they generally work, equips us with more tools when making decisions.

Grokking Artificial Intelligence Algorithms, Manning Publications

Traditional search algorithms are useful where several actions are required to achieve a goal, like finding a path through a maze. These algorithms evaluate possible states and attempt to find an optimal path . Typically, we have too many possible solutions to brute-force.

History is filled with myths of “mechanical men” and “autonomous thinking” machines. Looking back, we’re standing on the shoulders of giants in everything we do. Here’s a brief look back at some AI history.

1950s: The term “Artificial Intelligence” is coined. The concept of artificial neural networks is introduced. The model of the Perceptron is invented. The LISP programming language is invented. Alan Turing proposes the Turing Test.

Algorithms are like a pita bread recipe. There’s a problem being solved (making good pita bread), ingredients required (pieces of input), a sequence of steps to follow (recipe instructions), and the resulting output, in this case, pita bread of a certain quality.

Grokking Artificial Intelligence Algorithms

Algorithms can provide the same output given a specific input, always — these are called deterministic algorithms; or they can result in a different output when the steps involve an element of randomness or uncertainty — these are called stochastic algorithms.

The algorithm for a .max(x, y) function might involve comparing two numbers to find the maximum. …

Data is everywhere. Data is defined as “information, especially facts or numbers, collected to be examined, considered and used to help decision-making”. We’re unconsciously using data all the time — you’re consuming this piece of data right now.

Grokking Artificial Intelligence Algorithms

Data comes in different shapes and sizes — the temperature right now at at the Arctic, the number of red wolves left in existence, the texture of the pasta I had for dinner.

It’s interesting that we can measure temperature in something we all agree on, like degrees Celsius, but measure the texture and taste of pasta entirely differently. …

Intelligence is a mystery — the more you learn, the more questions you have. Scientists, philosophers, and engineers all have different opinions about the phenomena that are both esoteric to some and seemingly simple to others. How do we build AI without knowing what the I is?…

Intelligence might mean solving problems — applying skills and experience to solving specific or general problems. I can make a sandwich because I learned the skill. Within that skill, there are finer skills, like how to pick up and use tools.

Intelligence might mean identifying problems — do I wait for instruction or…

Learn more in Grokking Artificial Intelligence Algorithms by Rishal Hurbans and Manning Publications.

Charles Darwin proposed a theory of evolution that centers on natural selection. Natural selection is the concept that stronger members of a population are more likely to survive due to being more fit for their environment, which means they reproduce more and, thus, carry traits that are beneficial to survival to future generations — that could potentially perform better than their ancestors. …

I spent over 50 hours travelling to Australia and back to speak at NDC Sydney. It was a few long and tiring plane rides, but it’s taught me one thing about flying — after this trip, any flight is going to be okay in comparison.

Touch down in Sydney. The weather resembled something similar to my home country, South Africa, but it had a sense of uncertainty. It was warm, it rained, it was cold, it was almost every possible season in just a few days. I missioned to the hotel in the central business district, where I was staying…

In 2017 I was approached by Intel to join their Innovator Programme. After a couple interviews I was inducted as an Intel Innovator in the AI space. The idea of the initiative is to support technologists around the world involved in the community by providing cutting edge hardware, speakership opportunities, and a platform to promote their work and engage with more people.

Intel sent me a Movidius Neural Compute Stick. It’s a USB stick a little larger than a thumb drive that is specifically designed to train and primarily run neural network graphs, which is particularly useful in running networks…

I flew all the way from South Africa to New York to present a talk introducing machine learning and artificial neural networks to developers at Developer Week NYC. Here’s a snapshot of my epic experience.

The conference was held at the Brooklyn Expo Centre. The thought of staying in Brooklyn worried me a little, my understanding of the city was lyrics from the legend, Notorious B.I.G. However, I was pleasantly surprised with my experience. The area has been through a drastic transformation. It’s become a vibrant neighbourhood with lots of things to do, spots to see, and it’s safe. …

Rishal Hurbans

Tech, people, and ideas. Author of Grokking AI Algorithms with @ManningBooks. Solutions architect​ at @Entelect. Founder at @viszentech and @ProlificIdea.

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