From Data to AI: How Data is is the fuel moving the Artificial Intelligence Wave.

This article is intended to explain a little on a matter that is pertinent to the Artificial Intelligence community, this is that from Data Science to Artificial Intelligence, Data is the fuel. Taking a quick delve into this matter, I will pick briefly from the knowledge and words of Andrew Ng an awesome AI role model for many, he has explicitly said in many of his talk that Data is the new oil. This is so because the recent advances in Deep Neural Network models which are the backbone of most Artificial Intelligence breakthrough stem from the realization of the fact that with more data these models work incredibly well.

Dissecting further into what Ng means, right now businesses are massively using Machine Learning to make business decisions in predicting fraud models, risk management and smart business intelligence to mention but a few. They are harnessing a lot of customer data to generate a better customer experience with the end result of making more money and it’s working.

Taking a closer look at the concept of Artificial Intelligence relative to data!

The term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving” — Wikipedia

This, in simple terms means, we try to make machines behave like humans. Looking critically at how humans learn. We perceive our environment, make mistakes from it, learn from those mistakes and mistakes of others and we become wise along the way. The curious reader can check out this wonderful article.

Some few points I am extracting from the article:

• Our capacity to learn is largely determined by the level of our conscious attention to our senses. The more we are aware of what we see, smell, taste, hear, touch, or gather from the tone or mood of a situation, the more likely we will process information on a thoughtful level.
• central nervous system rapidly gathers, organizes, interprets, and makes sense of the inputs, to prepare our body and mind (peripheral nervous system — sensory neurons, clusters of neurons, and nerves) to adapt and take action based on need or circumstance.
• Our working memory “draws” from long-term memories to seek connections, make new meanings, create mental visualizations, and recognize familiar patterns, which in turn prepares the brain to establish relationships, organize information, create categorize, and consider new understandings.
• When learning environments and conditions engage multiple connections to the brain, humans are more likely to make greater attempts to process, take action, and apply new learnings.

I will take turns to explain this four points in the concept of Artificial Intelligence and it’s reliance on Data.

1. Machine learning algorithm, when exposed to the right set of data and features, has proven time without number to produce incredible results. At the other end, machine learning when fed with untreated data returns — well garbage in, garbage out.
2. Machine Learning models which are currently making waves in the world of Artificial intelligence have a pre-processing pathway that tends to organize the data before the Algorithms learn. Okay, cutting the shit, Machine learning algorithms are a bunch of vector applications that pick up salient part of a data and come up with recognition around the pattern that describes the dataset. Hence, they are supersmart in pattern recognition when the data is well organized.
3. Lately, badass Algorithms that are mainstream in core Artificial Intelligence — talking about Deep Learning Algorithms have learnt to retrain stuffs for particular amount of time, transitioning that memory to realizing many new things to come. It’s supercool.
4. And on the final note, when algorithms have finally learned from this data, they do well on new data or let’s put it in the context of point 4, they do well in new environments!

In all these, we have seen that data is the bedrock of Machine Learning through to Deep Learning that lines latest development in Artificial Intelligence. In further articles, we will be dissecting principles of Machine Learning and Artificial Intelligence through the fundamental concept of “Learning from Massive Data”