Khajetoorians: ‘That way, distinct and complex patterns can be created using the cooperative firing of these interacting atoms.’Īll this neuronal-like atomic behaviour gave Khajetoorians the idea of the Vici project: such patterns might serve as the basis for a kind of machine learning algorithm that AI-systems and the brain use. This firing rate can be modified, and this is influenced by the interactions with nearby other cobalt atoms – just like neurons influence each other’s firing rate in a neural network. When given more electricity, the atoms start fluctuating between the two states, just like neurons that are firing. They turn out to be able to assume two different shapes: either goldfish-like or resembling a mushroom.’ Using electricity, the researchers can artificially switch between the two shapes, creating a kind of binary memory like computer bits.Īnd similar to real neurons, these atomic ‘neurons’ also show plasticity. ‘If we put cobalt atoms on phosphorus, we see something special. Using an extremely strong microscope, with the highest resolution available in the Netherlands, he can image these atoms individually, one tenth of a nanometer in size, or 100,000 times smaller than a hair’s thickness. Khajetoorians sees a similar plasticity in his research on cobalt atoms sitting above phosphorus atoms. This process of changing, usually referred to as plasticity, underlies how the noisy brain learns and may be linked to the energy efficiency of the brain, neuroscientists suspect. Synapses slowly evolve based on experience, and change how the neurons fire.’ The ‘hardware’ itself – read: the brain – adapts as a result of the learning process. Khajetoorians: ‘The brain has two fundamental units: the neurons which rapidly fire, and the synapses – the connection points between neurons. Whereas a computer chip is robust and meant to precisely store or process, the brain, in contrast, is very noisy and adaptive. ![]() Yet very different things happen under the hood, when we compare our standard computers with the brain. These basic principles, often called machine learning, are also the basis of artificial intelligence that runs on our computers.’ Alex Khajetoorians. ‘The way the brain computes, in its simplest form, is based on pattern recognition. is biology unique – or is there another way?’, he explains in his office in the Huygens building. ‘How can we learn from the brain, how to make brain-like materials that learn? And does this always require organic material – i.e. ![]() NWO recently awarded the Scanning probe microscopy professor (Institute for Molecules and Materials) this prestigious grant, worth one and a half million euros. So can’t we try to make computers more like brains? That question is the basis of Khajetoorians’ new Vici project. Our own brains, on the other hand, can do the same thing running on just 15 Watts – and then we can simultaneously also listen to the radio or make a phone call. Take the self-driving function of a Tesla, for example, which is estimated to easily consume a few hundred Watts to drive the car. ![]() ![]() Last month, the professor received a Vici grant for his plans.Īs powerful as modern computers and artificial intelligence may be, they are huge energy consumers. This makes it possible to perform energy-efficient calculations. Inanimate material such as cobalt sometimes behaves a bit like brain cells, quantum physicist Alex Khajetoorians discovered.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |