Please welcome our new member, Emma Mckellar.
Emma is a student studying Computing and IT at ‘The Open University’. She originally trained and worked as a nurse, however decided to take on a new challenge this year to make the jump into technology. The Open University is an online university, so it can be quite lonely. However, it is such a fast-paced course that it doesn’t give her much time to notice!
Emma’s modules, currently, include robotics, computer networking, maths (so much maths) and technologies in practice (which includes studying linux and java). She loves reading about artificial intelligence and finds it fascinating, so tries to keep up with this in whatever spare time she has. Reading blogs, books, magazines etc.
Other than university work, Emma tries to update her blog weekly. This month she started featuring women in STEM, to try and introduce people to some cool women doing incredible things. She also loves to read and hang about in coffee shops with her husband: putting the world to rights.
Neural Networks by a Newbie - Emma’s contribution
We’ve long been fascinated with creating humanoids that can do our bidding. Science fiction is littered with examples of dystopian futures, where we can no longer tell who is organic and who is machine. One problem roboticists and engineers alike face, time and time again is … we just don’t know how our own brains truly work. Therefore, how can we construct one for ourselves?
In this race to achieve artificial intelligence, people were fooled by machines that could (it would appear) beat human chess masters. However, a look under the bonnet would reveal a human behind the controls. We had to break out of the structure of programming, the if/then statements that ruled a robot’s every move. If/then statements are great, in a controlled environment where there are no surprises and every eventuality are accounted for. To advance robotics, experts looked within us. What makes a human brain capable of learning a vast array of skills, without having to re-program ourselves every time we shift to a new focus?
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