If you enjoy streaming your favorite films on Netflix, then you know that Artificial Intelligence (AI) is here with us and is already making a huge difference in our lives. Apart from Netflix, there are countless more AI applications. Yes, this is just a tip of how one of the most significant technological inventions of this century can be used. As per the projections of Google’s Director of Engineering Ray Kurzweil, computers will be as smart as humans by 2040. It turns out that an artificial intelligence engineer will be more sought after than ever.
What is AI?
In layman’s terms, artificial intelligence, popularly known as machine intelligence, is the field of technology that is concerned with designing a computer program to perform tasks like humans. In other words, making computers intelligent. Such tasks include:
- Speech recognition
In fact, AI has already become part of humans in one way or another. Consider this, you want to look for information on Google. You type the first word on Google search engine and voila, the search results produced seem to match what you are looking for before you even finish typing the entire phrase or sentence. This is just one among countless illustrations of AI applications.
Down to why AI exists in the first place. How do you feel when the results of your search are out before you are done typing your query?
Like things have been made easier, more personalized, and your experience with this search engine is better, right?
Well, this is what it boils down to ultimately – an easier way of doing things and a memorable customer experience. This explains why futuristic businesses will not think twice about investing in AI.
AI Now and in Future
AI is already here with us. People are always on Google, other search engines, or social media platforms. Others with Apple products are well familiar with Apple’s revolutionary voice recognition program known as Siri. Businesses are using predictive maintenance for their facilities. Let’s put the numbers into perspective.
- The year 2014 was the year that saw up to $300 million plowed into AI startups, which marked a 300% increase from the previous years as revealed in a report by PWC.
- In a research paper published by Gartner in April 2015, it was projected that by 2018, digital assistants would have evolved to recognizing customer face and voice.
- A report by Narrative Science revealed that in the year 2017 alone, the adoption of AI grew by more than 60%.
- Gartner’s research has projected that by the year 2020, 20 billion things will be internet-connected in the IoT front.
- In a report by Big Market Research published in 2016, AI in the healthcare sector alone was worth $ 1,441 million in 2016 and was projected to grow to an unprecedented $22,790 million by the year 2023.
- However, the AI robots market is huge compared to the healthcare market. By 2018, the AI robots market was already worth $ 3.49 Billion and was expected to grow to $ 12.36 Billion by 2023 with machine learning being the most in-demand skills.
AI is broad in itself. Some major facets of AI include:
1.The Internet of Things (IoT)
This disruptive technology has completely revolutionized the way things are done on a personal and industry level. While IoT is internet and data-centric, AI is ‘intelligence’ based. When these two are brought together, the predictive and prescriptive technologies used in solving everyday problems will be enhanced.
2.Speech and Face recognition
A while ago voice (a branch of speech recognition) and face recognition technologies were two separate items. In the latest development, Artificial intelligence is actually using human voices to generate their faces. This aside, there is a lot that businesses have to gain from voice and face recognition technologies.
Face recognition is a significant development in the industry as far as efficiency and security are concerned. Boston and Dublin airports, for instance, are already testing the facial recognition technology. With a customer’s photo, they can monitor their whereabouts and travel history virtually without grilling the client with too many questions.
In speech recognition, Alexa, Google Assistant, and Siri need no introduction. Speech recognition has been associated with convenience and improved customer experience when placing orders for goods and services. More advanced technology exploring automatic speech recognition utilizing deep learning can be integrated to generate more accurate captions on videos. There are certainly more applications for this technology than you can imagine.
3.Automated Machine Learning (AutoML)
Traditionally, it would take a data scientist to identify a problem, gather and sort data, extracting features from the data, choose an analysis model, then train and analyze the performance of the selected model. First, if you are not a pro in this field, this process will be more difficult than achievable. Secondly, it is time-consuming.
The introduction of AutoML has transformed this scene, and the traditional machine learning processes are now evolving. Automation involves automating the entire machine learning process to make its application simpler and less time-consuming for users. This way, businesses can focus on solving problems in a more enhanced and cost-effective manner.
Getting Started with AI
AI is an emerging technology that brings together several disciplines including computer science, psychology, Data science, math, Natural language processing, Programming language, Machine Learning to name a few.
AI is a broad field, and those who want to venture into it have several options that they can pursue.
Here are some tips to get you started on AI
- Have a basic knowledge of mathematics and computer science. If however, you are conversant with engineering and data science, this will be an added advantage.
- Get the basics of machine learning.
- Decide exactly what you want to do. As mentioned earlier, AI is very broad, so you need to have done your research and know what you want to build. This way, you can identify and tap into the appropriate resources.
- Practice. Look for websites like Scikit-Learn that will give you practical AI experience. This and others like NLTK, PyBrain, and Numpy are libraries in Python Programming that you can use to learn how to come up with machine learning algorithms.
- Read widely. Remember that machine learning is fast evolving and there are new developments coming up every now and then. Resources like the open AI Blog and DeepMind Blog, books like Artificial Intelligence: A Modern Approach (Stuart Russell & Peter Norvig), Introduction to Artificial Intelligence (Philip C. Jackson), and The Quest for Artificial Intelligence (Nils J. Nilsson) are packed with AI insights. Newsletters like Import AI, Wild Week in AI, Morning Paper, and MIT Tech Review are excellent AI resources.
- Take part in contests like Kaggle and coding game to hone your skill and evaluate your ability.
- Take an online course to brush up your knowledge. A course like ‘Introduction to Artificial Intelligence and Machine Learning’ should be a great place to begin. While at it, consider getting tutorials and lectures in line with your specialization. There are plenty of them on YouTube that you can use.
- Consider a career in AI where you will apply the knowledge you have acquired professionally. If you are already familiar with the fundamentals and would like to build a solid career in AI, an Artificial Intelligence Course will be a good course to pursue.
- Be part of a community. Consider being part of groups like Google Brain and FAIR. Apart from gaining insight from experts in the field, you will also have access to meaningful discussions that you can take part in and have your questions answered.
- Finally, identify professionals whom you can link with and follow on social media platforms like Facebook, Twitter, and LinkedIn. Check and join the groups that they are part of on these platforms. You can even go a step ahead and approach one to be your mentor.
There is no end to learning and acquiring skills for as long as AI continues to evolve. In fact, the future of AI would rightly be summed up in Marios Savvides, director of the CyLab Biometrics Center at Carnegie Mellon University words that “We live in a time where AI can surpass the human brain’s capability”.