A machine that can think the way people think.
Giving computers or machines the ability to learn without being explicitly programmed. Think movie recommendations from Netflix or product recommendations from Amazon based on your viewing or purchase history, reviews, likes, shares, etc.
It’s the part of machine learning that that’s meant to ingest large amounts of data and form abstracts and concepts. Think about a computer being able to tell apart a dog from a cat after ingesting large number of animal pictures.
Just another (less scary) term to define AI. IBM prefers the term CC over AI.
A computer system inspired by the living brain. Think AlphaGo AI beating Lee Sedol, the human Go champion.
Set of rules to be followed in calculations or problem-solving. Think Google’s algorithm for ranking websites when presenting search results.
Natural Language Processing
An area of AI dedicated to understanding and interpreting how humans speak. Think about the many different ways you can ask for weather related information of Google, Siri or Alexa. E.g. “What’s the weather in Boston?” or “Will it rain in Boston today” or “Boston weather today?” Add to that different languages, nuances, regional accents, cultural tones and you begin to understand that achieving accuracy with NLP is extraordinarily challenging.
A robot, a virtual assistant or an interactive agent that can carry on a conversation using Natural Language Processing. They’re the modern-day equivalent of the IVR systems of the mid-to-late nineties. They’re used to complement task processing or augment the customer experience without the need for additional resources.
The “data” part refers to large underlying data sets. The “mining” part means scouring for patterns. Data mining is about scouring large amounts of data in an attempt to find patterns. For example, understanding how well a new product performed in a specific geography or how a particular set of demographics affected the outcome of a vote.
Being able to mine and learn from historical data and predict an outcome with a certain degree of confidence. For example, being able to generate a sales forecast based on sales data from the past 10 years. Or, when used in email marketing, to suppress potential non-performing audience segments for better deliverability.
It’s the hypothesis that AI will trigger runway technological advances reaching a point where it overtakes human intelligence. Experts like Elon Musk and Masayoshi Son predict it will happen by the mid 2030s.