In Brief At its I\/O '17 conference this week, Google shared details of its AutoML project, an artificial intelligence that can assist in the creation of other AIs. By automating some of the complicated process, AutoML could make machine learning more accessible to non-experts. Googles AutoML <\/p>\n
One of the more noteworthy remarksto come out ofGoogle I\/O 17 conferencethis week was CEO Sundar Pichai recalling how his team had joked that they have achieved AI inception with AutoML. Instead of crafting layers of dreams like in theChristopher Nolan flick, however, the AutoML system layers artificial intelligence (AI), with AI systems creating better AI systems. <\/p>\n
The AutoML project focuses on deep learning, a technique that involves passing data through layers of neural networks. Creating these layers is complicated, so Googles idea was to create AI that could do it for them. <\/p>\n
In our approach (which we call AutoML), a controller neural net can propose a child model architecture, which can then be trained and evaluated for quality on a particular task, the company explains on the Google Research Blog. That feedback is then used to inform the controller how to improve its proposals for the next round. We repeat this process thousands of times generating new architectures, testing them, and giving that feedback to the controller to learn from. <\/p>\n
So far, they have usedthe AutoML tech to design networks forimage and speech recognition tasks. In the former, the system matched Googles experts. In the latter, it exceeded them, designing better architectures than the humans were able to create. <\/p>\n
AI that can supplement human efforts to develop better machine learning technologies could democratize the field asthe relatively few experts wouldnt be stretched so thin. If we succeed, we think this can inspire new types of neural nets and make it possible for non-experts to create neural nets tailored to their particular needs, allowing machine learning to have a greater impact to everyone, according to Googles blog post. <\/p>\n
AutoML has thepotential to impact many of the other AI and machine learning-driven softwares that were discussed at the conference. It could lead to improvements inthe speech recognition tech required for a voice-controlled Google Home, the facial recognition software powering theSuggested Sharing feature in Google Photos, and the image recognition technology utilized by Google Lens, which allows the user to point their Google Phone at an object (such as a flower) in order to identify it. <\/p>\n
Truly, AI has the potential to affect far more than just our homes and phones. Its already leading to dramatic advancements in healthcare, finance, agriculture, and so many other fields. If we can use an already remarkable technology to actually improvethat same kind of technology, every advancement made by humans can lead to machine-powered advancements, which lead to better tools for humans, and so on. The potential of AI then draws to mind the title of another sci-fi film: limitless. <\/p>\n
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