You’ve probably heard the terms Artificial Intelligence (AI) and Machine Learning (ML) recently in the news. It seems to be the new buzzwords, just like cryptocurrency not long ago. Bitcoin is not making headlines anymore, making people question, was it only a clickbait buzzword and is AI the same? What are these new technologies and why should we, the common people, the non-technical people, care? Reality is— our society is on the brink of a technological revolution, and Artificial Intelligence is at the core the Fourth Industrial Revolution which will fundamentally alter the way we live and work. It will affect all of us.
Leading technology giants Facebook, Google, Amazon are all excited about Artificial Intelligence. Google CEO Sundar Pichai emphasized in 2017 just how important AI is to the future of the company by saying:
“I’m really happy with how we are transitioning to an AI-first company. The Google Assistant is one of our first steps towards that future…Advances in machine learning are helping us make many Google products better… Beyond that, we continue to set the pace in machine learning and AI research.”
Even though we hear about it in the news, and see headlines, how many of us really know — what is AI? Why is it important? Let’s face it, there are not many people who truly understand what AI and ML are, it’s relatively new, but as it will have a huge impact on our lives in the future, we should aim to have at least a basic understanding of it. I would suggest to pay attention especially if you are still in the early days of your career. Chances are, it will deeply influence the future of work and your career as a result, no matter the industry you are in.
So — what is AI?
I have been really interested in everything related to the future and especially the technology that will shape it. But I have to admit, I also lacked a clear understanding of AI, even though I’ve known for a very long time about the massive importance of it.
During my University years, I always attended workshops around entrepreneurship and got the habit of going to one of the biggest tech conference in the Nordic, Slush, every year. Even though I studied business, I always tried to widen my perspective and educate myself in those topics that weren’t directly related to my studies. It is a shame business and technology studies are not integrated more, as it often is in the “real” world. So, I have been learning on my own, mostly because, well, I can. As I wrote in my previous article, it is up to us how we use the power that is access to unlimited information that is available thanks to the internet. I really find technology fascinating and over time, got over the limiting belief that only tech people need to know this stuff. I’m not a tech-head — what I am is a person of curiosity, ideas and dreams.
We cannot wait until someone or something (university) will give us the information we need, we need to educate ourselves. Taking matters in my own hands to learn about these concepts that are already major and will only get more significant in the future, I did what any other person would do — I Googled it.
Okay, so what about artificial intelligence?
By now you will have a solid foundation of knowledge in machine learning. However, this is only the tip of the iceberg – machine learning at its most basic provides a very limited form of artificial intelligence.
Advances in artificial intelligence are possible through ever more powerful algorithms – artificial or deep neural networks – that have additional layers of complexity (quite literally additional neurons).
These are the algorithms that are used to power sophisticated applications and tools. From image recognition to image identification, through to speech to text and machine translation, the applications of these algorithms are radically transforming our relationship with technology.
But you probably already knew that. The important question is how you actually go about doing it.
Well, luckily in many ways, if you know the core components of machine learning, more advanced elements of deep learning and artificial neural networks shouldn’t actually be as complex as you might at first think.
There are, however, a couple of considerations that become more important as you move deeper into deep learning.
Here are some of the results to what is AI:
· AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
· Artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.
· Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.
· Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans.
From this simple Googling experience, I already noticed that AI means different things to different people, and I had to go deeper in the attempt to better understand it.
Google is a good start. You can find many online courses and workshops organized all over the world if you live in a bigger city. Some of them might cost a lot of money since it really is a hot topic at the moment.
Free quality online education Finland style
Here’s where the Finnish education delighted me once again. I learned about an online course created by the University of Helsinki and Reaktor, called The Elements of AI. I saw many people in my professional network endorsing it on social media, so I didn’t hesitate for a moment to take this course.
I took the first module yesterday and I’m impressed. It’s mind blowing how this quality of teaching is free and accessible to anyone. The teaching material itself is amazing and equally importantly, the way it’s delivered is what the future of higher education can and should be.
The course is divided into 6 modules:
· What is AI?
· Solving problems with AI
· Real world AI
· Machine learning
· Neural networks
· Implications
Conversational AI Startups
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