When you transmit information long-distance there is always a chance that some of it gets mangled and arrives at the other end corrupted. Luckily, there are clever ways of encoding information which ensure a tiny error rate, even when your communication channel is prone to errors.
Computers represent information using bits — that's 0s and 1s. It turns out that Claude Shannon's entropy, a measure of information invented long before computers became mainstream, measures the minimal number of bits you need to encode a piece of information.
Most of us have a rough
idea that computers are
made up of complicated hardware and software. But perhaps few of us
know that the concept of a computer was envisioned long before these
machines became ubiquitous items in our homes, offices and even
Yesterday's refusal by the UK government to posthumously pardon Alan Turing makes sad news for maths, computer science and the fight against discrimination. But even if symbolic gestures are, symbolically, being rebuffed, at least Turing's most important legacy — the scientific one — is going stronger than ever. An example is this week's announcement that scientists have devised a biological computer, based on an idea first described by Turing in the 1930s.
Almost nothing tangible remains of the legendary Bletchley Park codebreaker Alan Turing. So when an extremely rare collection of papers relating to his life and work was set to go to auction last year, an ambitious campaign was launched to raise funds to purchase them for the Bletchley Park Trust and its Museum. The Trust has announced today that the collection has been saved for the nation as the National Heritage Memorial Fund (NHMF) has stepped in quickly to provide £213,437, the final piece of funding required.
The human brain faces a
difficult trade-off. On the one hand it needs to be complex to ensure high performance, and on the other it needs to minimise "wiring cost" — the sum of the length of all the connections —
because communication over distance takes a lot of energy. It's a problem well-known to computer scientists. And it seems that market driven human invention and natural selection have come up with similar solutions.
Researchers have unveiled the first prototypes of robots that can
develop emotions and express them too.
If you treat these robots
well, they'll form an attachment to you, looking for hugs when they
feel sad and responding to reassuring strokes when they are
distressed. But how do you get emotions
into machines that only understand the language of maths?
The human genome is represented by a sequence of 3 billion As, Cs, Gs, and Ts. With such large numbers, sequencing the entire genome of a complex organism isn't just a challenge in biochemistry. It's a logistical nightmare, which can only be solved with clever algorithms.