Definitions: What Is and Is Not AI
Understand the differences between AI and ML, the problem areas of AI marketing, and the future of AI.
Birth of AI
In 1950, mathematician and World War II hero Alan Turing asked a simple question in his paper, Computing Machinery and Intelligence: can machines think? Today, we’re still grappling with that same question. Depending on who we ask, AI can be many things. Many maps exist out there on the internet, from expert systems used in healthcare and finance to facial recognition to natural language processing to regression models. As we continue with this section, we will cover many of the facets of AI that apply to products emerging in the market.
For the purposes of applied AI in products across industries, in this course, we will focus primarily on ML and DL models used in various capacities because these are often used in production anywhere AI is referenced in any marketing capacity. We will use AI/ML as a blanket term covering a span of ML applications, and we will cover the major areas most people would consider ML, such as DL, computer vision, natural language processing, and facial recognition. These are the methods of applied AI that most people will come across in the industry, and familiarity with these applications will serve any product manager looking to break into AI.
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