I took Andrew Ng's course and dropped it half-way upon discovering that it was nothing mind blowing beyond the 'constraint optimization' courses I took in grad school when I attended Carnegie Mellon. I strongly remembered enjoying the introduction lectures but realized that it wasn't what I was looking for once a 'cost function' was mentioned. 'Constraint optimization' was before people slapped : machine learning, deep learning, NN, CNN, and A.I on every gradient descent algorithm.

I have no faith that Strong A.I/AGI will come from the above efforts as they are anything but General. The whole is greater than the sum of the parts and the current crop of weak A.I algorithms are a small part of a bigger whole.

As far as fear of AGI/Strong A.I. Listen, you can't stop something whose time has come. When it comes and it will, no million dollar consortium of businesses who have leveraged weak A.I to line their pockets will be able to stop it. We can postulate to the ends of the earth about what it will be and how we must prepare for it or we can focus on creating it.

Those who are most likely to create it aren't worrying to the ends of the earth about its dangers. They aren't funding million dollar initiatives to make 'tests' for something that isn't even understood yet. They are out there thinking deep and far and working through what it takes to create it... Likely : Thinking Different than the current crop of people centered on capitalizing (increasing profit margins) on a very productive discovery : Weak A.I. The fear that arises from this group is in knowing that AGI will trump Weak A.I (their cash cow). Thus, the fear propaganda.

So, where do I feel AGI will likely crop up from? The basement dwelling loner asking the deep and general questions about life, matter, energy, information without a particular profit maximizing goal in mind. Their goal being to more deeply understand the very nature/fabric of life, intelligence, and this universe...

Otherwise, hey.. I could sit back and believe that wisdom just emerges when you've dumped enough money in the laps of A.I experts.

Think different. You're not going to achieve anything new and ground breaking thinking and looking at the problem the same way everyone else is. Sure, there will be many failures but therein lies the risk/reward of going beyond the herd.