Now, Google has declared that AutoML has defeated the human AI engineers at their own game by setting machine-learning software that’s more effective and powerful than the best human-designed systems.
An AutoML system recently broke a record for classifying perceptions by their content, scoring 82 percent.
While that’s a relatively simple task, AutoML also beat the single-built system at a more complex task key to autonomous robots and augmented reality: showing the location of multiple objects in an image.
For that task, AutoML scored 43 percent versus the individual-built system’s 39 percent.
These results are important because even at Google, few people have the needed expertise to build next-generation AI systems. It takes a rarified skill set to automate this area, but once it is achieved, it will break the industry.
“Today these are handcrafted by machine learning scientists and literally only a few thousands of scientists around the world can do this,” News tells Google CEO Sundar Pichai said.
“We want to enable numbers of thousands of developers to be able to do it.”
As it becomes natural for AIs to design new systems with improved complexity, it will be great for humans to play a gatekeeping role. AI systems can easily make biased agents accidentally such as associating ethnic and gendered names with negative stereotypes.
However, if human engineers are killing less time on the grunt work involved in creating the systems, they’ll have more time to apply to oversight and refinement.
Ultimately, Google is aiming to hone AutoML until it can perform well enough for programmers to use it for possible applications. If they succeed in this, AutoML is likely to have an impact far beyond the walls of Google.