![]() The volume and complexity of data that is now being generated, too vast for humans to reasonably reckon with, has increased the potential of machine learning, as well as the need for it. The algorithms also adapt in response to new data and experiences to improve their efficacy over time. These algorithms can detect patterns and learn how to make predictions and recommendations by processing data and experiences, rather than by receiving explicit programming instruction. Machine learning is a form of artificial intelligence based on algorithms that are trained on data. Learn more about McKinsey’s Digital Practice. But ultimately, the value of artificial intelligence isn’t in the systems themselves but in how companies use those systems to assist humans-and their ability to explain to shareholders and the public what those systems do-in a way that builds and earns trust.įor more about AI, and how to apply it in business, read on. By using artificial intelligence, companies have the potential to make business more efficient and profitable. You’ve probably interacted with AI even if you didn’t realize it-voice assistants like Siri and Alexa are founded on AI technology, as are some customer service chatbots that pop up to help you navigate websites.Īpplied AI-simply, artificial intelligence applied to real-world problems-has serious implications for the business world. Computers and other devices are now acquiring skills and perception that have previously been our sole purview.ĪI is a machine’s ability to perform the cognitive functions we associate with human minds, such as perceiving, reasoning, learning, interacting with an environment, problem solving, and even exercising creativity. Some computers have now crossed the exascale threshold, meaning that they can perform as many calculations in a single second as an individual could in 31,688,765,000 years. Those smart machines are getting faster and more complex. Machines- smart machines at that-are now just an ordinary part of our lives and culture. Personal calculators became widely available in the 1970s, and by 2016, the US census showed that 89 percent of American households had a computer. ![]() The work of Turing and others soon made this a reality. Twentieth-century theoreticians, like computer scientist and mathematician Alan Turing, envisioned a future where machines could perform functions faster than humans. This curiosity has helped turn science fiction into actual science. And yet, despite their seemingly endless utility, humans have long feared machines-more specifically, the possibility that machines might someday acquire human intelligence and strike out on their own.īut we tend to view the possibility of sentient machines with fascination as well as fear. ![]() From the wheel that revolutionized agriculture to the screw that held together increasingly complex construction projects to the robot-enabled assembly lines of today, machines have made life as we know it possible. Our species wouldn’t have gotten very far without our mechanized workhorses. Humans and machines: a match made in productivity heaven. ![]()
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