What is it?
At it’s core, Artificial Intelligence (AI) is the science of creating smart machines that can learn on their own, rather than being constructed to perform a specific set of commands. AI is transforming our world; we’ve seen it pervade into almost every industry thus far. However, it’s been around for decades. Alan Turing built the first “intelligent machine” World War II to break the famous Enigma encryption algorithm used by the Germans to transmit secret messages. It’s due to the dramatic increase in computer performance and processing power that AI is now getting the attention it deserves.
AI is a high level concept. Consider artifical ingelligence like a symphony, which is a coordinated composition of different instruments to produce harmony. Let’s go into more detail about each component.
Machine Learning (ML)
True machine learning is software that possesses an ability to learn from previous data and make decisions based off these learnings. It relies on pattern recognition and previous computations to produce reliable and repeatable decisions. This is why we can say that the machines are “learning” from previous datasets.
Deep Learning (DL)
Deep learning is a branch of machine learning. Artificial neural networks are algorithms inspired by the way neurons work in the brain. They work by finding patterns in raw data and combining layers of artificial neurons. As the layers increase, so does the neural network’s ability to learn increasingly abstract concepts. Some examples of Deep Learning used today are:
- Facebook uses ML/DL to analyze photos and provide a dynamically generated description based on image analysis.
- Spotify’s “Discover Weekly” playlist analyzes songs you’ve listened to or like to recommend tunes.
- Netflix’s “Recommended For You” section is shaped by the previous TV shows or movies you’ve watched.
- Amazon’s “Recommended Products” … You get the point.
This is why your data is so precious and expensive to these companies. The more they know about you, the more they can tailor and personalize the experience.
Natural Language Processing (NLP)
To be most effective, AI must communicate with humans as naturally as humans can communicate with humans. In AI, we call this level of understanding Natural Language Understanding. Human communication a complex web — random, out-of-order, peppered with humor, emotion and conflict — and it depends hugely on context. Because communication is not straightforward, it makes NLP rather difficult. Once AI conquers the challenge of human communication, decoding complex questions (natural language queries), making connections, and giving answers that make sense, radical progress in Articifical Intelligence is not far behind.
Like a human assistant, an AI assistant can only be as smart as the information — the context — you give it access to. If your assistant — human or artificial — has the ability to see your calendar and reservations, but not your contact list and location data … well, that’s not a very helpful assistant. Context is king when it comes to complex tasks. It’s true of humans and it’s true of AI. Every section of data and context needs to be tuned perfectly to play a different note in the symphony of AI. Again, the more the intelligence platform knows about you, the more powerful it becomes. It’s as smart as the data it receives.