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.
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