JUDY WOODRUFF: The continent of Africa does not now hold many internationally well-known universities, but one man is trying to change that, a one-time Microsoft executive who was educated in the United States, Patrick Awuah. As special correspondent Fred de Sam Lazaro reports, as part of his Agents for Change series, one special focus of classes is to teach Africa's next generation of leaders about ethics. FRED DE SAM LAZARO: It looks like a pretty typical college campus, with students working in computer labs, studying at the library, or hanging out with friends. But Ashesi University, in the West African nation of Ghana, has embarked on an experiment which its founder hopes will help start to fundamentally change the entire continent. PATRICK AWUAH, President, Ashesi University: In the next three decades or so, the population of Africa is going to double, and something like 40 percent of working-age people are going to be Africans in the world.

Currently, I am an IT student in college. This semester, I had a really interesting course which I choose my own topic to study, and create my own project. So I decided to learn and work on something very interesting and unique. While I was exploring various topic, I found a video tutorial about Neural Network, and I was really interested in learning this topic. After watching the tutorial video, I come up with an idea to implement a neural network program that learns how to play Flappy Bird game.

MIT loves numbers, so let me drop a few to illustrate the popularity of a course called 6.036. It is overseen by four instructors and 15 teaching assistants. Lectures are held in 26-100, the school's largest auditorium, with 566 seats. But this semester, about 700 students signed up for the course -- also known as Introduction to Machine Learning -- according to Tommi Jaakkola, the computer science professor who created it. So at the first lecture, more than 100 students watched on a video screen in an overflow room.

A high school teacher in a black coat enters the classroom. "Good morning," he says to the students before starting his lecture, with his right hand busily scribbling something on a blackboard and his left holding a physics textbook. Then, while holding the chalk and the textbook, he points at a female student and asks a question. "OK, that's correct," he says, giving her the OK sign with his third hand. The 28-second YouTube video titled "Three-handed Sensei" (jtim.es/OFd530aIiZV),

The first thought is about open sourcing technologies. I have already written on this trend, which is quite unusual at a first look if you think about it, but my thinking around open source has been highly stimulated by the talk given by Wes McKinney -- for who doesn't know who he is, well, he is definitely not a random guy but is THE open source guy (creator of pandas and author of Python for Data Analysis). The open source model is quite hard to be reconciled with the traditional SaaS model, especially in the financial sector. However, we are observing many firms providing cutting-edge technologies and algorithms for free. While in some cases there is a specific business motivation behind it (e.g., Google releasing Tensorflow to avoid conflict of interests with their cloud offering), the decision of open sourcing (part of) the technology actually represents an emerging trend.

TORONTO – When we see artificial intelligence (AI) in fiction, it usually encompasses the AI functioning just like a human. That's called'strong AI' and well, we aren't there yet. There are two types of AI: strong AI, the aforementioned AI that function as a human would; and weak AI, the type of AI we see today. For example: robotics in a manufacturing plant that function autonomously to complete one task is an example of weak AI. "That's where we are [with weak AI], but I think we are trending towards strong AI," said Wayne Thompson, the chief data scientist at SAS, at the analytics vendor's event in Toronto. "We are trending towards what I consider modern machine learning."

A new website that predicts congressional bills' success foresaw the Affordable Care Act replacement bill would be shelved instead of passed – awarding it only a 15 percent chance of being enacted. Users can look up any pending bill on PredictGov or find predictions through its partner, legislation tracker GovTrack, which now includes a "prognosis" line in its overview of each bill. Vanderbilt University law Professor J.B. Ruhl is a co-founder in bill forecasting site PredictGov. PredictGov, which uses big data and artificial intelligence to reach its conclusions, is the invention of Vanderbilt University law Professor J.B. Ruhl; computer scientist and doctoral candidate John Nay, and their team. It pulls from decades of congressional data plus hundreds of variables, including the bill's sponsor, amendments, economic trends and political shifts.

University teaching is under the microscope as institutions brace themselves for the first Teaching Excellence Framework, which will accord them gold, silver and bronze status. The biggest developments in university teaching are being driven by technology. The old techniques of talk and chalk are being challenged by lecture capture, flipped learning and decision-making based on data analysis. But technology can have worrying consequences. One (unnamed) university was recently brought under attack by its smart devices – a network including vending machines and light sensors was hacked, wreaking havoc with internet speeds across campus. And then there are the concerns about privacy raised by such developments.

Prediction has always been a curious topic in life due to a key attribute – the extreme human desire to know what is coming next. Let's ponder over our thoughts to answer a simple question – "Where is prediction most relevant in your life today?" Predictions are central to every aspect of our life, whether we realize it or not. During school days, it was predicting what we would love to do in the future to choose a career path, checking the weather today to determine how should I dress, evaluating inventory numbers for the next day, to less important predictions made daily during our interactions with other people – like doing time management and getting into classes for a student, to dining, socializing, etc. A prediction or forecast, is a statement about the future.

Artificial intelligence is one of the most exciting scientific developments in human history. Only a decade ago, AI was a far-fetched fairy tale. Advancements in deep learning have propelled AI enthusiasts' wildest dreams into reality. In fact, artificial intelligence is already a part of our everyday lives, whether it be in the form of your email app that learns what messages you frequently trash or the digital assistant tracking your speech patterns. AI is more than a passing fad or unfortunate bubble.