In a few decades, we've gone from machines that can execute a plan to machines that can plan. We've gone from computers as servants to computers as collaborators and team members.
AI began by understanding actions as humans performed them. Routine tasks with predictable decision points became computer-controlled through programs based on extracting expertise through observation or questioning human experts. Programmers captured the "how" of human behavior in rules that machines could follow. Automated machines could do it faster, with fewer errors, without fatigue. Humans can explain this type of AI.
Enter machine learning - the capacity of computers to leverage massive amounts of data to act without specific human instruction. By looking at examples, extracting the patterns, turning them into rules, and applying those rules, machine learning now captures the "what" of human behavior to provide artificially intelligent answers for complex tasks - such as visual perception, speech recognition, translation and even decision-making,. AI now does things that humans find difficult to explain.
Join us on November 1st as Thought Leaders from the mediaX community will discuss:1. On which tasks will machines with AI be able to out-perform humans?2. What do we know about people and technology that will help us establish confidence, certainty and collaboration in the new partnerships between human and artificial intelligence?
And, most importantly:3. How can intelligent machines truly enhance the human experience?
Stanford faculty, staff or student of Stanford, please email Addy Dawes for a special registration code.