It is questionable if with January 1st, 2020 a new decade is starting but it is undoubtedly what are the hottest trends in AI & Data Analytics. Hristo Hadjitchonev, CEO of A4Everyone is sharing his own Top 6 for 2020. Just take a look and do not hesitate to use the comment form if you think he might have missed something interesting.
Have you ever heard about Moore`s law? In 1965, Gordon Moore, who would later become one of the founders of Intel, wrote a paper claiming that the number of electronic components, which could be placed into an integrated circuit, will double every year. This exponential became known as Moore`s law and turned out to be the foundation of the digital world.
It was 1997 when the Deep Blue computer beat the world chess champion, Garry Kasparov. It was the first machine over human victory while playing the mother of all strategic games. Well, even though the Deep Blue computer was created specifically to play chess versus human, it took just a few years more for standard desktop computers to dominate our brains on the chess board. Now there are smartphone chess apps have been able to defeat exceptionally good players.
This was the first time when the machine ‘outminded’ humans. By declaring that AI software scored a better result than humans in a large-scale reading and comprehension test, it seems we are witnessing the second breakthrough.
Worldwide known data science community Kaggle did something nice and sweet as industry-wide survey sharing interesting and valuable information on data scientists from around the globe. More than 16 000 data scientists, analysts, experts, and statisticians joined the Kaggle survey which is full of interesting insights. Among the most important is the fact that 3 of every 4 participants rely on Python, followed by R and SQL and the logistic regression is the most commonly used data science method, followed by decision trees and random forests.
As data analytics company, at A4E we are more than familiar with the capabilities and potential of Artificial Intelligence widely known as AI, especially combined with some kind of automation. As society members, just like you, we also know that the fake news is not just pieces of information heavily disliked by politicians with disputable reputations. This is why we are curious whether AI is capable to help users and media businesses to distinguish the real news out of fake ones.
Named as one of the best currently active football players in the world, Lionel Messi is also one of the best paid among them all. His Barcelona contract alone is securing him a payment of €40 M per year or €770 000 per week.
Well, recently performed data analytics model confirmed what we all suspected. Even though Messi should be the best paid, he is extensively overpaid. The model and its results are described in a study conducted by a team of Lawrence Technological University in Michigan, which used machine learning and data science to analyze the salaries of 6082 professional football players in Europe. The salary of each was compared to a set of 55 attributes, reflecting each player`s skill set. The model is evaluating scoring and passing accuracy, aggression and vision on the field, speed, acceleration, ball control, physical condition, etc.
Elon Musk and his Tesla Model S started it all. The premium electric sedan was equipped with advanced and self-learning Autopilot system, which can take the chauffeuring work out of the driver. It was a complete breakthrough because if it works as good as it should; it is going to change driving forever. It is all because of Artificial Intellect (AI) and the way it works fueled by data sensors and powered by video analytics. And since we have, to be honest, it wasn’t started by Elon Musk but the automotive industry itself. It doesn’t matter if we talk about rain sensing wipers (Cadillac) or adaptive cruise control (Mitsubishi) or lane departure systems (Mercedes-Benz). Such systems work with predefined events with some variables in the input data and one particular, predefined outcome.
Nowadays, mankind possesses a tremendous number of data, regarding many real-life phenomena. The availability of such a source of information is the main premise for the wide spread usage of the data-driven modelling. When account for more factors in the model development, this usually leads to a better ability of the model to represent the specifics of investigated system. Naturally, in fields like economics, society, medicine, etc. the models are with many inputs and many outputs (MIMO).