The Egyptian empire. For more than 3000 years it stood as a tall and mighty civilization. They built pyramids, worshiped mysterious gods, and created legends.
But their stories and culture were all recorded in hieroglyphs. An extinct language.
No one knew what those symbols meant, it was impossible to decrypt. Just think about it, 3000 years of history and treasures locked away just out of our reach.
And the same can be said about our DNA.
What would you do with a humanoid robot? Get it to go to work for you? Create the next trillion-dollar company? Or take over the world?
(Un)Fortunately, our technology isn’t advanced enough to create those robots. But we can definitely make progress toward it! One start is the physical appearance of the robot — and with Generative Adversarial Networks (GANs) we can create hyper-realistic faces.
Take, for example, the image below. There are 3 humans and 1 generated human. Which one is it? (Scroll slowly)
This is Imani. Growing up in an immigrant family, she dreamed of going to Harvard. She worked hard, studied those long nights, and one day she got in. There, she toiled and drove herself to graduate with honours. With her prestigious degree in computer science, along with an increasingly open job market, Imani expected to land a job easily. But no one got back to her. Days turned into weeks and Imani didn’t get a single interview.
The reason can be traced back to this study, which found that African Americans have a 52% lower chance to be employed compared to their white counterparts. …
Stop. Close your eyes and think: What’s the meaning of your life?
So, what did you come up with? Nothing right? Yeah! That’s exactly what I felt a few months ago. I was preparing for an interview when it hit me. I asked myself this question over and over again trying to get an answer out of me. What is our purpose in this universe?
So I asked my family and friends and they responded just as I had. How come? The problem was that none of us ever stopped to think about these kinds of meta-questions. …
What’s the most flexible thing in this universe? A slinky? An acrobatic? Stretch Armstrong? Wrong! It’s actually something you’re using right now — the 🧠!
Just think about it, we humans are able to do crazy things! We can calculate the motion of heavenly bodies, diagnose diseases, and invent new technologies, all with the human mind. In fact, the hardware in your skull can do anything that any other human has done before!
What would you do with an artificial brain? Do your homework? Beat the stock market? Take over the world? The possibilities are endless. What if I told you that humans have already built an artificial brain?
In fact, we have! — well kinda. It’s not as complex as our brains, but they’re extremely powerful tools that have the power to change the world. They’re called Neural Networks.
A Neural Network (or NN for short) is a group of connected nodes that are able to take in information, process it, and then produce an output.
One example of a NN would be our brains! It consists of lots and lots of connected biological neurons that take in information (words on the screen), processes it, then produces an output (understanding the words and storing the information). …
You hear the words “Machine Learning” and “Artificial Intelligence” tossed around all the time nowadays. News articles pop up about how Artificial Intelligence (AI) is being used for predictive policing. You hear how companies are rushing to implement Machine Learning (ML) into their products. But what are AI and ML? How does it work? Read on to find out.
In everyday life, we use ML interchangeably with AI, but they’re different! AI is the whole domain whereas ML is a specific field in AI. In other words, AI is to math as ML is to geometry.
So what are they? AI is the act of getting a machine to do actions that typically require human intelligence. This is a broad definition because it’s the definition for the whole field. AI applications range from chatbots, to composing music, to designing airplane parts! …
What do you think about when you hear the words “Artificial Intelligence”? Killer Robots? Tesla? Peanut Butter Sandwiches? All of these things are definitely related to AI, but they aren’t AI itself.
So what is AI? The definition is: artificial systems learning, by themselves, to do tasks that require intelligence. The definition is quite vague, but that’s because AI has many sub-fields and applications that it encapsulates.
But before we move on, a misconception must be cleared up! AI is actually, on a higher level, divided into two categories: Artificial General Intelligence (AGI) and Artificial Narrow Intelligence (ANI). Killer robots, omnipotent beings, and super intelligent gods are all fantasies of AGI in movies and books. But almost no one works on AGI because it’s seen as a “pie in the sky” idea in most of the AI world (and because we have no idea how to build it). What everyone actually works on is ANI. Tesla, Siri, Netflix and Uber are all examples of this type of AI helping us humans. …
Your deadline is due tomorrow and you rush to finish it.
The pieces start falling into place: you’re working at a ferocious pace, ideas pop into your mind, and people react in just the way you want them to.
When you’re finished your work, you feel the rush of euphoria for completing such a daunting task in such a short amount of time. Wouldn’t it be great if you could always work this effectively?
What you’ve just experienced is a touch of Mastery. Achieving Mastery is the ability to be in that flow state all the time. …