Udacity is tuning their Nanodegrees to the most exciting fields of Technology right now. Their Self-Driving Car or Flying car Nanodegrees
, for example, are drawing massive success (18.000 Nanodegree graduates, 4x up from 2016
The key to their success is double. They’re teaching applied Artificial Intelligence use cases, instead of just the dry mathematical approach taken by traditional universities. Also, they’re enrolling the top experts in the industry to give the classes and showcase their work. These are the same experts, big tech giants, are looting from university R&D labs.
Technology organizations are getting involved on these Nanodegrees, both with talent and money. Their goal is to hire the junior students of such Nanodegrees to populate their labs. Companies like IBM Watson, Google or Didi Chuxing, are betting on this approach.
Other companies, like WeWork
, the global coworking company, are buying boot camp schools altogether
. This way they’re able to offer a new source of talent to their customers. It seems that the industry is investing heavily in alternative talent pools
The question is, for all those incumbents out there, what exactly are they doing to foster talent?
While technology corporations might seem to be fixed in their industry, they’re expanding and owning adjacent sectors at a rapid pace.
As the education moves from “open” to scarce, limited and expensive, how can we retrain minorities and other at-risk groups
? Ignoring this rift will only increase the chasm between the technology elites and the rest of the population
The gap between the capacity of technology corporations to amass talent and all the rest is widening exponentially every month. The more it swells, the harder it will be for other industries to compete with them. And while technology corporations might seem to be fixed in their industry, they’re expanding and owning adjacent sectors at a rapid pace.
Incumbents should invest in supporting alternative talent pools for their purpose. They should embrace challenging projects that can be interesting to potential candidates.
Despite all this, the truth is that the automation of many jobs is accelerating the rate at which we destroy jobs. While automation also creates new job positions, the speed imbalance between both is increasing too.
The problem is so acute that some organizations are, paradoxically, investing in even more automation. Two reasons are driving this. It’s harder than ever to find the talent they need. And the complexity of the new products requires a super-specialized workforce. A workforce that’s impossible to grow and train at the industry’s rate.
Previous versions of AlphaGo initially trained on thousands of human amateur and professional games to learn how to play Go. AlphaGo Zero skips this step and learns to play simply by playing games against itself, starting from completely random play.
It is able to do this by using a novel form of reinforcement learning, in which AlphaGo Zero becomes its own teacher.
(Mastering the game of Go without human knowledge, Nature 550.)
I wouldn’t be surprised that, as I mentioned in the Quantum Computing article
, more companies turn to AI-based employees, instead of training humans.
The development of such algorithms isn’t trivial and requires extensive mathematical knowledge. Something that isn’t common. […] As a side note, I wonder if the current Deep Learning models can’t be applied to the task of developing new Quantum Algorithms.