Artificial intelligence has been in the news a lot lately, specifically related to machines’ ability to deep learn, or more closely mimic the actions of a human brain. In the near future, will a computer’s algorithms be able to do the project manager’s job as well as you can?
It started in 2011. Stanford professor Andrew Ng holed up at the Google X Lab at the company’s Silicon Valley headquarters and initiated a project dubbed “Google Brain.”
Google Brain encompassed a connected network of 16,000 computers programmed to mimic aspects of human brain activity by looking for recurring patterns on the Internet. In a period of three days, the Brain had successfully trained itself to recognize a cat based on 10 million digital images taken from YouTube videos.
Google Brain was an example of an artificial neural network, designed after the densely interconnected neurons of the human brain. Possessing about a million simulated neurons and a billion simulated connections, Google Brain was ten times larger than any deep neural network before it, and in the last few years, Ng has made networks that are ten times larger than the original Brain.
The Google Brain and its subsequent neural networks represent what many consider to be the new frontier of artificial intelligence – deep learning. Deep learning trains computers to recognize patterns in data and then classify and categorize them as a human brain could do instantaneously. At present, deep learning in the form of image and speech recognition is used in applications such as Facebook’s tagging feature and the iPhone’s Siri. AI experts are already working on computational linguistics applications that will allow machines to easily decipher the variety of human languages – both spoken and written.
Machines may elbow their way in…
The maturation of deep learning along with machines’ ability to perform more complex algorithms will be a powerful combination. Within the next five years, we could see computers undertaking the following project management functions:
- Defining the scope of a project
- Aligning with other business areas
- Analyzing risks
- Developing project schedules, timelines, and budgets
- Assigning tasks to the appropriate resources
- Implementing software and other technical components
- Documenting project progress
- Assessing project outcomes
For more about AI and deep learning, review the rest of the post at QuickBase's Fast Track blog.