I'm reviewing my notes learning and becoming a Artificial Intelligence (AI) Engineer to extend my job skill set to support the growth of my consulting business. I am already learning to become a Data Scientist which is one very important role in analyzing data part of Machine Learning workflow which I will explain later on this article.
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Let's get started before I forgot about it. Things that you need to know about Artificial Intelligence.
First, Artificial Intelligence is the "intelligence" that control the machines and the capability of a machine to imitate human behavior. Yes, we the human are capable of building something like it.
Not so fast, we are still transition from the basic programming, advancement of computers that help produce results that we want to see or made it transform to something special. As of this time, there are three AI stages.
The 1st is Artificial Narrow Intelligence (ANI) limited to one or two functional areas, not self-aware or self-conscious, making decisions based on statistics or math computation. Examples of ANI are smart phone apps, chess games, image identification tools, speech, self-driving systems, translation and spam filters.
The 2nd AI is Artificial General Intelligence (AGI) a level up that covers more than one functional areas, such as reasoning, problem-solving and abstract thinking. Examples are multipurpose systems, systems with human-level intelligence, reasoning, thinking, decision-making, systems that synthesize diverse information and decide actions. We are not there yet, close and it's coming very soon.
And Artificial Super Intelligence (ASI) will surpass human intelligence. Examples are Super Intelligent AI agents and systems that are masters at every skill, subject, or discipline and are faster than the smartest humans.
To easily remember the differences of AI, here's the summary.
What these Artificial Intelligence really do? That's a good question. Sometime, I also ask myself why build something like it. Just to name a few applications of AI include image recognition, speech recognition, natural language processing, translation, product analytics, A/B testing, and analysis.
And if we do it right AI contributes to the society by enhancing throughput and efficiency, adding jobs (and losing too), strengthening the economy, increasing human efficiency, enhancing the lifestyle, solving complex social problems, and benefiting multiple industries.
Continue reading other articles here: https://que.com/tag/artificial-intelligence/
Thank you for reading.
@Yehey
