We discuss and comment on the role agriculture will play in the containment of the CO2 problem and address protocols for terraforming the planet Earth.
A model farm template is imagined as the central methodology. A broad range of timely science news and other topics of interest are commented on.
Monday, March 18, 2013
High Tech Brain
This is all early days but we can all see where this is headed. We
are certainly mastering our brain in the process.
An interesting question. We think that we forget but do we? We
certainly set stuff aside and move on. Yet how well do we return to
the knowledge area? Are the channels open and reinforced during a
revisit? We have examples of long term photographic memory that
gives us a very robust picture instead.
Thus an unused pathway will open up to respond eventually to a
freshly asked question. So just how does our brain order its search?
That is really important. Perhaps by smell. This is biology after
You see my point. We really have to break out of our natural way of
thinking and perhaps pick up a paint brush instead.
Let us imagine you create a question. The cells involved send out a biochemical messengers that induce related cells to produce synapses and connect together to establish a response. These responses are slowly connected together until the mind becomes satisfied with the result.
If this is how it works, then the organic system is surely the optimal solution.
German scientists said
they're making headway toward creating a computer that would work
like a human brain, learning by itself without programming.
Bielefeld University say they are experimenting with memristors --
electronic microcomponents that imitate natural nerves.
After constructing a
memristor that is capable of learning, Andy Thomas from the
university's Faculty of Physics said he is using them as key
components in a blueprint for an artificial brain.
Memristors are the
electronic equivalent of the brain's synapses, the bridges across
which nerve cells (neurons) communicate with each other and which
increase in strength the more often they are used.
memristors can learn from earlier impulses, Thomas said in a
university release Tuesday.
Because of their
similarity to synapses, memristors are particularly suitable for
building an artificial brain, he said.
"They allow us to
construct extremely energy-efficient and robust processors that are
able to learn by themselves," Thomas said, suggesting principles
taken from nature can be recreated in technological systems to
develop a neuromorphic or nerve-like computer
"This is all
possible because a memristor can store information more precisely
than the bits on which previous computer processors have been based,"
Thomas said. "This is how memristors deliver a basis for the
gradual learning and forgetting of an artificial brain."