With all the excitement over neural networks and deep-learning techniques, it's easy to imagine that the world of computer science consists of little else. Neural networks, after all, have begun to outperform humans in tasks such as object and face recognition and in games such as chess, Go, and various arcade video games. These networks are based on the way the human brain works. Nothing could have more potential than that, right? An entirely different type of computing has the potential to be significantly more powerful than neural networks and deep learning.

The Rubik's Cube is a three-dimensional puzzle developed in 1974 by the Hungarian inventor Erno Rubik, the object being to align all squares of the same color on the same face of the cube. It became an international best-selling toy and sold over 350 million units. The puzzle has also attracted considerable interest from computer scientists and mathematicians. One question that has intrigued them is the smallest number of moves needed to solve it from any position. The answer, proved in 2014, turns out to be 26.

The Rubik's Cube is a three-dimensional puzzle developed in 1974 by the Hungarian inventor Erno Rubik, the object being to align all squares of the same color on the same face of the cube. It became an international best-selling toy and sold over 350 million units. The puzzle has also attracted considerable interest from computer scientists and mathematicians. One question that has intrigued them is the smallest number of moves needed to solve it from any position. The answer, proved in 2014, turns out to be 26.

Deep learning uses layers of neural networks to look for patterns in data. When a single layer spots a pattern it recognizes, it sends this information to the next layer, which looks for patterns in this signal, and so on. So in face recognition, one layer might look for edges in an image, the next layer for circular patterns of edges (the kind that eyes and mouths make), and the next for triangular patterns such as those made by two eyes and a mouth. When all this happens, the final output is an indication that a face has been spotted. Of course, the devil is in the details.

The way we age is deeply fascinating. Indeed, knowing how our faces will look in 20, 30, or 40 years' time is a trick that many would find captivating. A number of techniques exist that can do this. But they are time-consuming and hence expensive. So a cheap and quick way to age faces in photographs would be a handy trick.

Johann Sebastian Bach is widely considered one of the great composers of baroque music. Bach lived and worked in Germany during the 18th century and is revered for the beauty of his compositions and his technical mastery of harmony and counterpoint. One form of music that Bach excelled in was a type of polyphonic hymn known as a chorale cantata. These are based on Lutheran texts and sung by four voices. The composer starts with a well-known tune which is sung by the soprano and then composes three harmonies sung by the alto, tenor, and bass voices.

Johann Sebastian Bach is widely considered one of the great composers of baroque music. Bach lived and worked in Germany during the 18th century and is revered for the beauty of his compositions and his technical mastery of harmony and counterpoint. One form of music that Bach excelled in was a type of polyphonic hymn known as a chorale cantata. These are based on Lutheran texts and sung by four voices. The composer starts with a well-known tune which is sung by the soprano and then composes three harmonies sung by the alto, tenor, and bass voices.

Human cognitive abilities decline with age. And neuroscientists have long known that this decline correlates with anatomical changes in the brain as well. So it's no surprise to learn that it is possible to spot the signs of aging in MRI images of the brain and even to determine a "brain age." The difference between brain age and chronological age can reveal the onset of conditions such as dementia. But the analysis is lengthy because the MRI data has to be heavily processed before it is suitable for automated aging.

Soon after the invention of photography, a few criminologists began to notice patterns in mugshots they took of criminals. Offenders, they said, had particular facial features that allowed them to be identified as law breakers. One of the most influential voices in this debate was Cesare Lombroso, an Italian criminologist, who believed that criminals were "throwbacks" more closely related to apes than law-abiding citizens. He was convinced he could identify them by ape-like features such as a sloping forehead, unusually sized ears and various asymmetries of the face and long arms. Indeed, he measured many subjects in an effort to prove his view although he did not analyze his data statistically.

Soon after the invention of photography, a few criminologists began to notice patterns in mugshots they took of criminals. Offenders, they said, had particular facial features that allowed them to be identified as law breakers. One of the most influential voices in this debate was Cesare Lombroso, an Italian criminologist, who believed that criminals were "throwbacks" more closely related to apes than law-abiding citizens. He was convinced he could identify them by ape-like features such as a sloping forehead, unusually sized ears and various asymmetries of the face and long arms. Indeed, he measured many subjects in an effort to prove his view although he did not analyze his data statistically.