In May 2017, Google Brain announced the creation of AutoML, an A.I. that can help them create new A.I.s. AutoML focuses on deep learning, and more specifically reinforcement learning, that involves passing data through neural network (imitating how the human brain works). We will be talking about deep learning and neural network later in the term.
AutoML can essentially create a "child" that can perform a particular task. “In our approach, a controller neural net can propose a ‘child’ model architecture, which can then be trained and evaluated for quality on a particular task,” Google says in their 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.” You can read more about AutoML and the details of the algorithm here.
Last November, Google used AutoML to make NASNet, a computer vision system that has already broken the record for the most accurate image recognition, as seen in the graph below. They tested the program on the ImageNet image classification and COCO object detection data sets, which Google claims to be “two of the most respected large-scale academic data sets in computer vision” and it outperformed all other human-made systems.
There are a number of potential application for NASNet, some of them include faster and safer self-driving cars, facial recognition to replace passports (like in Australia) and even helping visually-impaired people to regain sight. However, on the other hand, there are also some potentially detrimental application, like robots "reproducing" so fast that humans cannot keep up. The question now becomes how do we ensure that the parent does not pass down biases to the child system and, most important, how do we make sure that the systems are used ethically. It is easy to imagine how people can take advantage of this technology for evil ends, such as recognizing faces on the street and following them. This concern seems to be so pervasive that Amazon, Facebook, Apple and other big companies have created a "Partnership on Artificial Intelligence to Benefit People and Society". The Institute of Electrical and Electronic Engineers has also created ethical standards for AI.
Last November, Google used AutoML to make NASNet, a computer vision system that has already broken the record for the most accurate image recognition, as seen in the graph below. They tested the program on the ImageNet image classification and COCO object detection data sets, which Google claims to be “two of the most respected large-scale academic data sets in computer vision” and it outperformed all other human-made systems.
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| Image Credit: Google Research Blog |
There are a number of potential application for NASNet, some of them include faster and safer self-driving cars, facial recognition to replace passports (like in Australia) and even helping visually-impaired people to regain sight. However, on the other hand, there are also some potentially detrimental application, like robots "reproducing" so fast that humans cannot keep up. The question now becomes how do we ensure that the parent does not pass down biases to the child system and, most important, how do we make sure that the systems are used ethically. It is easy to imagine how people can take advantage of this technology for evil ends, such as recognizing faces on the street and following them. This concern seems to be so pervasive that Amazon, Facebook, Apple and other big companies have created a "Partnership on Artificial Intelligence to Benefit People and Society". The Institute of Electrical and Electronic Engineers has also created ethical standards for AI.
In my opinion, using A.I. to help us better create A.I. is a great use of our resources. It would take us a much larger amount of time and energy to do what AutoML does so "easily". I do agree that there are a number of ethical issues at stake here and it does sound straight out of a science fiction movie. However, if researchers don't have to spend so much time on the grunt work, they will have time to perfect the systems and oversee them to make sure the biases are not passed down. Moreover, if society can recognize that A.I. technology is exponentially developing, then it should create rules and regulations right now to make sure that nothing gets out of control (which they are starting to do). All in all, I think there are more benefits than harms in this and I think it is a genius idea from Google.
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I do think that this is a very interesting application of AI. However, this is almost like changing a few parameters (hyper-tuning) so that the general structure is modified to better suite some specific problems. It may be more complex but not more interesting than setting up an alarm for a clock.
ReplyDeleteThis is very cool, maybe soon AI can just think everything and we don't need Computer Scientist anymore. Well, probably not that, but I think this is a great accomplishment. I think this AI still have limitation, but maybe that we now can focus on develop better general AI like this and let the AI do the lesser job of developing specific program.
ReplyDeleteI think we will still need computer scientists regardless. These AI's can keep reproducing but I think they will only provide a platform for humans to keep creating better AI
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