Tech Tuesday
Page 8
February 28, 2017
Neural networking used to improve artificial intelligence performance can be easily fooled if you give it well-designed inputs. This is a major limitation of the networks.”
What did the Luka team do?
Neural networks are being used to advance research in artificial intelligence. Researchers create the base of the network, but cannot say how networks might make decisions. GRAPHIC BY WAYLEN GLASS / DESIGN EDITOR
Nikhilesh De
itself to transform the inputs into an output. During the process of creating an output — for example, the From “Iron Man’s” Just a name of an image from a given Rather Very Intelligent Sysinput, the image itself — the nettem (J.A.R.V.I.S). to “Portal’s” work “learns” how to complete GLaDOS to “2001: A Space Odtasks, like identifying images. yssey’s” HAL 9000, the idea of One of the disadvantages to having a fully sentient digital asneural networks is that they are sistant is one that people hope to black boxes, Elgammal said. Ofsee jump from science fiction into ten, the people who create or work reality sooner rather than later. on these networks are not entirely Google, Apple and Windows sure how they work — they build have all begun this process with What is a neural the framework of the network and their own digital assistants, network? let it take on tasks for themselves. which allow users to control their Neural networks are a new type What scientists were unable to phones or computers with voice of computer program, which can do during neural networks’ early commands. Facebook found- respond to queries or carry out stages, was have a neural network er and CEO Mark Zuckerberg instructions more efficiently and explain its reasoning, according to spent a large part of 2016 trying creatively than existing programs. All About Circuits. While a network to push the idea of digital assis- They are programs used to identimight produce the desired output tants a step further, by creating fy faces in photos, analyze medibased on the given inputs, it would an artificial intelligence that can cal data, crunch through quantum not be able to provide a reason, control his house. mechanics, steer self-driving cars which would While these not help any of digital asthe research sistants are fields listed. examples of “...a neural network takes the image and the task you’re trying to (teach it) According smart systems, and learns.” to an article they are not published by thinking indeAhmed Elgammal the Massachupendently and Professor in the Department of Computer Science setts Institute they cannot of Technology pass the Tur(MIT), “After ing test — they cannot fool humans into thinking and improve automation, among at the data that is available and let training, a network may be very good at classifying data, but even the machine learn for itself.” they are sentient. The advance other tasks. These networks are trained its creators will have no idea why.” of neural networks may have They do this by creating arIn the October 2016 article, rechanged this by creating artificial tificial neurons — the human to identify patterns on their own intelligences that can successfully brain cells which allow people through test data provided by the searchers said that because they simulate a human being. to think and reason, said Ahmed program’s creators. Unlike tradi- cannot figure out why a neural Late last year, a team of pro- Elgammal, a professor in the De- tional programs, these networks network might reach any particgrammers came one step closer partment of Computer Science. are then expected to find similar ular conclusion, they cannot trust to simulating a full intelligence Perceptrons — artificial neurons patterns given unique data, in- the results. This inability to predict a neuwhen they built an artificial intel- — have existed as a concept since stead of simply providing an exral network’s reasoning process ligence capable of responding to the 1950s, and form the basis of a pected result with a given input. There are two ways to train makes using them a disadvanmessages as a person. neural network. Eugenia Kuyda, founder and The components of a neural data, Elgammal said. Super- tage for researchers who want CEO of Luka, an artificially intel- network are designed to cooper- vised learning occurs when a re- to understand how a network ligent messenger bot, directed ate in order to produce a unique searcher provides input data and can relate to a human brain, Elher team to develop a program output from a given input that directs the network to create the gammal said. “It’s really hard to predict its that could simulate Roman Ma- might be different from what matching output data. Unsuperzurenko — her former col- each neuron might produce on vised learning occurs when the behavior on some data that it has researcher lets the network train never seen before,” he said. “Its league, boyfriend and best friend its own. correspondent
who died in a car accident early in 2016. In late 2016, using thousands of stored text messages and pictures, the Luka team completed a neural network that could respond to people as Mazurenko through a chat interface. The network was realistic enough that Kuyda, as well as Mazurenko’s friends and family, said that speaking to it was similar, if not identical to speaking to him.
In other words, neural networks try to simulate being a human brain. “Other algorithms have a lot of tweaking and are designed,” Elgammal said. “So to recognize an image, for example, you would have to start by designing certain features or elements that you need in order to recognize it. A neural network doesn’t do that, a neural network takes the image and the task you’re trying to (teach it) and learns.” Researchers approach neural networks differently than they do traditional algorithms, he said. “You don’t design the algorithm, you design the architecture of the network,” he said. “You don’t design what exactly (it) should look for in the image — is it the colors, is it the line, is it the corners, you don’t do that anymore. You look
Roman Mazurenko was hit by a speeding vehicle while crossing the street and died shortly after the accident. Three months later, his friends and family could send him messages and receive responses by texting him. The Verge notes that the idea of resurrecting deceased loved ones through the use of technology is not new — an episode of “Black Mirror” actually features robots created with the messages left behind by the deceased. In “Black Mirror,” these robots can simulate everything about a person except for their emotions. Kuyda said in The Verge that she saw the episode and her project was inspired at least in part by it. The Mazurenko bot’s responses are identical to what he would have sent and are based on feeding the neural network some 8,000 messages he sent over his lifetime. While it originally only responded with archived versions of the actual messages the person sent, it is now able to choose its own words in each message. While it primarily responds with text, the bot can also respond with images. Though the bot can seem real, it cannot feel emotions — the same problem facing the androids in “Black Mirror.” The bot is also not the person it was modeled after, despite how effective the simulation may be. After interacting with the bot, one of Mazurenko’s friends said “What really struck me is that the phrases (the bot) speaks are really his. You can tell that’s the way he would say it.” The same friend said he asked the bot for advice, and the response also matched what Mazurenko might have said, which means the bot is not only able to respond to queries, it can determine what a person might need to know.
Can a neural network simulate a person?
Elgammal said it is unlikely for an artificial intelligence to fully simulate a human, even with the use of neural networks. The present technology is simply not sufficiently advanced to do so. But by simulating specific aspects of a reasoning process, whether that is for responding to people’s messages, analyzing traffic patterns or even just agreeing with a doctor’s diagnosis, neural networks have proven their potential for future applications, he said. Neural networks can dramatically change how researchers analyze different problems facing society, but it is clear they can also be used to advance artificial intelligence research by leaps and bounds. Though the Mazurenko bot is based on a specific person and carries the traits of that person, it is possible that in the future, unique people may be simulated without needing a source person to create it.