What exactly is Artificial Intelligence?

Artificial intelligence is really starting to shape the world as we know it. The field of AI includes everything that has anything to do with the “intelligence” of a machine; and more specifically, that machine’s ability to imitate a human’s thought process and reasoning abilities.

Artificial IntelligenceWhile artificial intelligence develops programs to help solve problems, the patterns needed for solving a problem via AI is a lot different from the way a human would solve it. In a general sense, these programs that are developed are often designed to interpret, sort through, and provide insight from a vast amount of data. We want these AI programs to handle this data because it can process far more than a human brain ever could.

Four AI abilities

There are four abilities that contribute to artificial intelligence; and without them AI would not be what we expect.

Ability to sense

object-recognitionThe first, the ability to sense, correlates directly with object recognition. In this case, object recognition is the picking out and identification of objects from different inputs such as videos and digital images. Natural Language Processing (NLP) also contributes to the ability to sense, meaning the ability to read text and make sense of it.

Ability to converse

Thinking robotThe second, which is the ability to have a conversation, is the foundation to develop the ability to think. Predictive Analytics sums this up by identifying the likelihood of future outcomes based on historical data and algorithms (machine learning).

Ability to act

Working robotThe third, the ability to act, refers to taking action based on thinking. This is also known as “Prescriptive Analytics,” and determines the best solutions/outcomes among various choices, with known parameters.

Ability to learn

Learning robotThe fourth and final ability, the ability to learn, includes automatically occurring self-improvements. Not only do these improvements need to happen, but we also need to understand how these improvements were made as they occur.

More than sci-fi robots

SophiaThroughout the advancement process of AI, the technology industry has made AI an essential part of its work. The advancement of this field has caused debate over whether AI is a threat to humanity or not. Artificial intelligence is NOT something to fear; and it IS more than just sci-fi robots taking over.

Of course, it’s easy to understand why some may think AI and robots are one in the same, getting some things mixed up. Pop culture can be blamed for this, because robots are often portrayed in such a way that may cause humans to worry about what exactly they may become. In reality, robots are physical machines created to carry out a specific task and artificial intelligence is used to develop programs to solve problems. When AI and robots are integrated, autonomous robots are born.

Practical uses today

Believe it or not, but artificial intelligence systems are seen every day. Interesting Engineering came up with a list of everyday applications of AI, which can be separated into two categories: consumer-focused and enterprise-focused.

Some consumer-focused applications include smart cars, video games, smart homes, and preventing heart attacks.

Examples of enterprise-focused applications are customer service, workflow automation, cybersecurity, and maintenance predictions.

With the increasing advancements in the field of artificial intelligence, we are destined to see more and more practical uses.

Orzota can help!

The Orzota BigForce Docu-AI Solution helps automate document workflows for insurance and finance use cases. It uses sophisticated AI techniques to parse documents (image files, PDFs, etc.), extracting information and key insights while providing instant search and analysis capabilities.

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During the summer of 2016, we had a high school student intern with us. He knew some Java from the Computer Science AP course but was very interested in using machine learning  to predict health outcomes. We were skeptical at first – the prospect of teaching a teenager (even a very smart one) the fundamentals of ML, along with a new programming language and then have him apply it to a real data set … and all in the span of a summer internship seemed like an Herculean task. But seeing how keen he was, we decided to take him on.

Sushant Thyagaraj (that was his name) proved us wrong! He learned R within the first week, following that quickly with various ML algorithms through tutorials and sample exercises. He researched various publicly available data sets that might be suitable for his work, went through several iterations with a couple of the data sets before finally settling on predicting survival for lung cancer patients after thoracic surgery.

Machine Learnign to predict healthHe continued fine tuning his results and wrote a full paper detailing his work (I should add that this last was done after school began). We are pleased to present his paper: Using Machine Learning to Predict the Post-Operative Life Expectancy of Lung Cancer Patients