by Rahul Jayaram '21 Do you struggle to find your keys? Don’t worry. More important information took their location in your memory. Most people have trouble recalling this simple piece of information at some point, and wish to have the ability to remember everything. While such a super power seems amazing, forgetting is actually an important part of how our brains learn and function. In fact, the mechanism of eliminating unneeded information from our memory is so critical to the human mind that scientists have developed a synthetic material that imitates the way we forget. The implications of such a feat show great promise in the present-day artificial intelligence renaissance. Researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory over the past months have created quantum perovskite, a compound that shows habituation, or decreased response to a repeated stimulus, at the atomic level. According to Dr. Subramanian Sankaranarayanan, a nanoscientist at the Argonne National Laboratory, “The brain has limited capacity, and it can only function efficiently because it is able to forget. It's hard to create a nonliving material that shows a pattern resembling a kind of forgetfulness, but the specific material we were working with can actually mimic that kind of behavior [1].” When a proton is added to the perovskite, the material’s atomic lattice structure expands. Likewise, if a proton is removed, the structure contracts dramatically and shrinks in size. Such expansion or contraction of the perovskite is what scientists call “lattice breathing.” One would expect that perovskite retains lattice breathing properties as long as the material is not altered in any way. However, as this process is repeated, the perovskite material becomes less and less responsive to a change in proton count, and reduces the amount it changes in size each time. In other words, the perovskite eventually forgets how to react to an extra proton. Imagine your first day of high school and all of the strong emotions that were going through your mind. This was such a drastic change from your previous life where you didn't know much about this new place. Now imagine yourself in the middle of the year, where you are adapted to the day-to-day, monotonous life of high school, finding it to be commonplace. Even though you are experiencing the same stimuli as your first day, you are much less affected. This essentially describes the habituating behavior of the perovskite, and shows the importance of “forgetting” unnecessary, repetitive stimuli. Processing unchanging information this way is fundamental to the way we learn new things. The next step of the perovskite study involves developing novel algorithms that parallel the physical properties of quantum perovskite. These algorithms, based off the adaptability of perovskite, can lead to smoother machine learning, enabling technology to achieve tasks by ignoring input information after it becomes obsolete, raising the bar for processing ability. With the information pruning ability of perovskite-based algorithms, high computational power tasks such as human decision making become a more viable capability for machines. As a result, over time we can train such devices to accomplish goals that are beyond the scope of our current technology, making the world more automatic. Whether mankind can keep up with what follows this advancement is left to be found out. References:
[1] Fan Zuo, Priyadarshini Panda, Michele Kotiuga, Jiarui Li, Mingu Kang, Claudio Mazzoli, Hua Zhou, Andi Barbour, Stuart Wilkins, Badri Narayanan, Mathew Cherukara, Zhen Zhang, Subramanian K. R. S. Sankaranarayanan, Riccardo Comin, Karin M. Rabe, Kaushik Roy, Shriram Ramanathan. Habituation based synaptic plasticity and organismic learning in a quantum perovskite. [online]. 2017 [cited 2017 Nov 6]. Available from: https://www.nature.com/articles/s41467-017-00248-6 [2] Forget about it: A material that mimics the brain. Science Daily. [online]. 2017 [cited 2017 Nov 6]. Avaialble from: https://www.sciencedaily.com/releases/2017/10/171010124057.htm
0 Comments
Leave a Reply. |