The world is fast evolving, with Artificial intelligence (AI) at the forefront in changing the world and the way we live. AI is everywhere — at our workplace, in our homes, cars, in our phones and laptops — in short, in the things that have become integral in our lives. Moreover, AI devices know what kind of TV shows and movies we like, what we buy, and how we operate. Let’s explore this world a little deeper…
AI By Definition
It is the ability of a computer to imitate how we think. It is accomplished by learning from previous experience, object identification, language mastery, decision making and problem resolution. These and other capabilities can be combined to perform functions that would be performed by a human. Like a human, with AI, machines can combine input from multiple sources (sensors, digital), analyze information and act on analysis results. Designed by humans, these machines are expected to reach conclusions based on real-time analysis.
Today AI applications are not “artificial,” but focused and contained in functions and features we experience daily such as: word completion while typing, travel directions, eCommerce buying, and television watching recommendations. Although the value of these AI applications is taken for granted, there’s some degree of confusion on terminology. Key terminology that is used includes:
- Artificial Intelligence –used when discussing any computing alternative that demonstrates some human intelligence capability.
- Machine Learning – a subset of AI applying input data to a machine improving its mastery in completing a specific task.
- Deep Learning – a type of machine learning, without human intervention, is self-teaching in completing a specific task with greater proficiency.
AI runs the gamut of specific task completion to duplication of human activities by choosing and solving multiple problems without human intervention. The former we experience daily with new applications enabling humans to complete tasks with ever increasing efficiency and accuracy. The latter is currently theoretical and exists only in the realm of the TV series Next.
AI has found its way into our daily living. Some great examples include:
- Speech Recognition – enabling fast and accurate speech transcription in multiple languages for a variety of use cases as seen with IBM Watson
- Natural Language Processing – understanding, interpreting, and generating text, think of email filters, smart assistants, search results, and predictive texts. Learn about a more few prominent examples.
- Machine Vision – identifying/classifying visual images. As a fun example, consider a fill-level inspection system at a brewery. Each bottle of beer passes through an inspection sensor, which triggers a vision system to flash a strobe light and take a picture of the bottle. If the system detects an improperly filled bottle—a fail—it signals a diverter to reject the bottle to then be filled properly.
- Recommendations – suggest purchases/media based on past purchases/viewing. Do you ever wonder why your favorite stores or Amazon suggest certain products or why Netfllix curates certain shows for you? Recommendation engines play a huge role with collaboration filtering.
These use cases depend on machine learning and data analytics combined to deliver intelligent decisions. To remain relevant, they learn from and adapt to information changes in their environment.
Imagination is the only limitation where AI can improve lives but many questions remain.. What is machine intelligence? What tools are most appropriate for different AI use cases? What is the right balance of replacing humans performing tasks vs. supporting them? Want to know what comes next and how to balance the future of machine learning? Let us help you navigate your business with AI driven solutions.