Artificial Intelligence (AI) is a buzzword in today’s world. I have been actively working in cutting-edge research in this field for few years now and I can assure you that all the hype around the technology is worth it. We are still just scratching the surface in the field and the impact and opportunities in this field will exponentially grow over the next decade.

‌What‌ ‌is‌ ‌Artificial‌ ‌Intelligence?‌

So, what exactly is Artificial Intelligence and why is it such a big deal? As the name suggests, Artificial Intelligence deals with making artificial things more intelligent. These could be refrigerators, cars, robots, mobile applications, computer softwares, etc. A lot of AI is being powered by a technique called machine learning, which basically gives the decision making power to the machines. Most common type of machine learning is basically a computer program that learns patterns within huge amounts of data by itself. For example, consider I give you the following data about the movies I like:

Avengers - Like
Spiderman - Like
Titanic - Dislike
Ironman - Like
Fight Club - Dislike

Now, if I ask you what kind of movies I like, you could probably guess that I like Superhero movies. Or if I asked you to predict which of the following two movies I would like to watch: Batman or Shawshank Redemption, you can probably guess it would be the former. So like you were able to find a pattern within the data, ML models can do the same. Such type of ML models are routinely used in YouTube, Netflix, Hotstar for recommending the movies or TV shows on your home page based on your watch history and upvotes.

Common techniques within machine learning include Deep Learning and Reinforcement Learning.

Some of the highly impactful use cases of ML & AI are:

1. Self-driving cars: These cars use advanced ML techniques to understand the surroundings using state of the art cameras, sensors, and other information gathering systems and continually take decisions on what to do (accelerate, brake, turn, etc.)
2. Recommendation system: These systems suggest the next item in YouTube, News article, etc.
3. Payment fraud detection: Fraud detection models predict credit card fraud by evaluating any suspicious pattern within the transaction.
4. Language Translation: Translation models suggest best translation for a phrase in a different language.
5. Many more...

Job‌ ‌opportunities‌ ‌in‌ ‌the‌ ‌AI‌ ‌field.‌

The jobs and research opportunities in this field have proliferated significantly in last 5 years and will continue to grow exponentially over the next decade. Some of the jobs in the field are :

1. Data Scientists: These focus on evaluating large data sources, finding patterns within them and using machine learning to build predictive models.
2. Machine Learning Software Engineers: These are hybrid of software engineers and machine learning experts. These more or less do everything that a Data Scientist does but are also well versed in building the necessary backend infrastructure required for serving the models.
3. Hardware Engineers:These work primarily on hardware components of machines (eg: Robots, phones, etc.) and interface closely with ML engineers.
4. Research Scientists:These work primarily in advancing the state of the art in the field of ML and AI. They try to come up new techniques in the given field and publish research papers in conferences and journals.

How to tinker with AI?

Easiest way to tinker in this field is running through a few online courses on Coursera or Udacity. I would recommend starting with a basic Python coursework (if you are new to programming) followed by a Data Science in Python course. These courses will give a good understanding of working with large sets of data in Python. Following that I would recommend studying or reviewing basics of Machine Learning through an Introduction to Machine Learning type course. Finally, if you want to go deeper, I would recommend using TensorFlow and doing the Deep Learning online course by Stanford University.