Google and other engines not only are indexing data and scoring it based on relevance, but they’re now anticipating our intent based on vast amounts of information they can access about us. This is how we find ourselves typing one character in the Google search box and uncannily getting suggestions for exactly what we were searching for. While in the past these search algorithms were based on sophisticated and effective logic that was nonetheless narrow, they now increasingly rely on AI-like processes of machine learning and deep learning. Typically, search engine algorithms are proprietary and use a combination of many technologies. Here, we’re taking Google, Bing, or systems like Amazon’s own site search. Search engines, recommendation engines, and content curation This technology is also applied in DAM (Digital Asset Management) systems, in which your company’s digital asset library might be handily tagged and categorized, thus saving a human hundreds of hours of tedious manual organization. How does Facebook know that your friend Alice is in the picture you just uploaded? And how does Google Photos know which of your pictures were taken in a park or in a living room or have a dog in them? This is done using the concept of computer vision, which applies machine learning and deep learning in order to analyze patterns in pixels and clusters of pixels in billions of photographs, and quickly identify the objects therein. With a basic understanding of the concepts involved in AI, we can start to grasp its application to some of the digital tools we already use as marketers, technologists, and in our daily lives as consumers. The machine’s act of acquiring knowledge from neural networks is called “ deep learning.” Neural networks are artificial structures built and programmed to behave like the neurons in the human brain and, based on vast amounts of data and logical reasoning processes similar to those our own brains perform, derive learning and insights that drive decisions. We’re not there yet, but if and when we get there, you can be sure we’ll be arguing about whether these AIs deserve their own social security numbers.ĪIs can “learn” through a process referred to as “ machine learning” in which the machine has access to vast amounts of data and is programmed to identify patterns and make correlations that help answer certain questions or perform certain tasks. Strong AI, on the other hand, is artificial intelligence that displays all the features of human intelligence (including reasoning, creativity, and sentience)- Blade Runner or Westworld level stuff. But when challenged with multi-step tasks or deriving conclusions from the data they have access to, they’ll delegate to Google or politely tell you to take a hike. Think Siri or Alexa - those systems are definitely impressive in their ability to parse human speech, look up information or control devices and media around the house. Weak AI is an artificial intelligence that is built for a fairly narrow purpose. In defining AI, we also need to make the distinction between “weak” AI and “strong” AI. But again, at least the definition of AI itself is simple enough. When even the experts in the field can’t agree on standard definitions for these things, it’s no wonder we lay people can feel intimidated by this domain and eventually grow existential and depressed. That discussion then forces us to try to define “learning” and, eventually, “consciousness,” “sentience,” and “self-awareness”. And as our machines get more “intelligent” and approximate human intellectual capacity in new realms, experts also keep moving the goalpost for what defines true intelligence, which complicates matters. When the discussion gets heady, philosophical, and esoteric is when we try to define what “intelligence” means. It also helps us appreciate AI’s impact and potential.ĪI itself can be roughly defined as the appearance of intelligent behavior in machines. But rather than brace for a dystopian future of mass unemployment, where machines rule over their feeble-brained human creators, our minimum due diligence as marketers and technologists is to familiarize ourselves with the basic concepts involved in AI and embrace a near future where AI empowers greater human communication and improves the quality of human lives.Ī basic grasp of the principles involved in AI keeps us from drifting into science fiction territory and tuning out altogether. The concept of Artificial Intelligence (AI) has been around for more than five decades but the chatter (and thoughtful discussion) about it has ramped up in recent years as more of the tools and systems we use move toward using increasingly powerful AI-like technology.
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