If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Artificial intelligence is touted to be one of the most impactful trends of businesses today. Around 73% of global consumers said that they are willing to adopt AI provided it makes their life easier. The applications of AI have become a crucial part of our lives, whether we believe it or not. From booking a trip online to receiving a book recommendation on Amazon – it's AI that is lurking in the background. Undoubtedly, artificial intelligence is already transforming everything about life faster than you think.
Toyota will roll out a fleet of approximately 3,700 vehicles for the 2020 Olympics, 90 percent of which will be electrified. The Japanese automaker says it aims to achieve "the lowest emissions target level of any official vehicle fleet used at the Olympic and Paralympic Games." Following the reveal of the Accessible People Mover (APM) specially designed shuttle, Toyota has released details about two models modified for the Olympics: the e-Palette and Concept-i electric vehicles. The e-Palette is battery-electric shuttle with Level 4 autonomous driving capability that supports smooth transport over short distances. It features a low-floor and electrically-operated platform that leaves little to no gap or opening between the curb and the bus at stops.
If you want to understand what's happening with artificial intelligence (AI) and cybersecurity, look no further than this week's news. On Monday, Palo Alto Networks introduced Magnifier, a behavioral analytics solution that uses structured and unstructured machine learning to model network behavior and improve threat detection. Additionally, Google's parent company, Alphabet, announced Chronicle, a cybersecurity intelligence platform that throws massive amounts of storage, processing power, and advanced analytics at cybersecurity data to accelerate the search and discovery of needles in a rapidly growing haystack. So, cybersecurity suppliers are innovating to bring AI-based cybersecurity products to market in a big way. OK, but is there demand for these types of advanced analytics products and services?
Moving forward, let's start with our basic imports: Let's say you want to make a model that is either a classification or regression based. How would you know which is the best model & which should you apply to your data set. In order to answer this, you need to fully understand what data you're trying to apply data science concepts to. My Cybersecurity data science project was a unbalanced classification problem. So I would decide to use a classification neural network model on the data.
Kaggle Learn bills itself as "Faster Data Science Education," a free repository of micro-courses covering an array of "[p]ractical data skills you can apply immediately." As I'm sure you are well aware, there are all sorts of free and low-cost data science education alternatives available via numerous online platforms. So why am I feeling it necessary to write about another data science learning resource? As I plan to embark on a fresh fall learning initiative -- once Those Lazy-Hazy-Crazy Days of Summer are out of my system -- I wanted to first find some concise review material for concepts I have previously learned and skills I have already acquired but which may have gone a bit rusty on me. To be clear, Kaggle Learn does not bill its micro-courses specifically as review material; however, I am so far finding that they fit this requirement for me rather well (though, admittedly, I'm still early in the process).
Recently, in cognizance of this seismic shift, the world's top AI researchers met in Asilomar, California to deliberate on AI principles and goals. In doing so, this eminent artificial intelligence society gifted humanity a framework of how to own the future. It is only by navigating AI ethical dilemmas, that we will avail the life saving technologies of applied artificial intelligence. The EU in its Responsible Research and Innovation initiative calls for investment in legal, social and ethics [LSE] research. Investment in LSE research will generate knowledge that can match artificial intelligence goals and society's needs.