"And he had power to give life unto the image of the beast, that the image of the beast should both speak, and cause that as many as would not worship the image of the beast should be killed.”
An artificial neural network that's
made entirely from DNA and mimics the way the brain
works has been created by scientists in the lab.
The test tube artificial intelligence can solve a
classic machine learning problem by correctly
identifying handwritten numbers.
The work is a significant step in demonstrating the
ability to program AI into man-made organic circuits,
This could one day lead to human-like robots made from
entirely organic materials, rather than the shiny metal
cybermen seen in popular culture.
Researchers hope the device will soon start forming its
own 'memories', from examples added to the test tube.
Their ultimate goal is to program intelligent behaviours
– such as the ability to compute, make choices, and more
– with artificial neural networks made from DNA.
Experts at Caltech chose a task that is a classic
challenge for electronic artificial neural networks,
This was one of the first tasks tackled by machine
vision researchers and an ideal method to illustrate the
capabilities of DNA-based neural networks
Human handwriting can vary widely, and so when a person
scrutinises a scribbled sequence of numbers, the brain
performs complex computational tasks in order to
Because it can be difficult even for humans to recognise
one another's sloppy handwriting, identifying
handwritten numbers is a common test for programming
intelligence into AI neural networks.
These networks must be 'taught' how to recognise
numbers, account for variations in handwriting, then
compare an unknown number to their so-called memories
and decide the number's identity.
The team demonstrated that a neural network made out of
carefully designed DNA sequences could carry out
chemical reactions to indicate it had correctly
identified 'molecular handwriting.'
When given an unknown number, this so-called 'smart
soup' would undergo a series of reactions and output two
fluorescent signals, for example, green and yellow to
represent a five, or green and red to represent a nine.
Lead researcher Lulu Qian, assistant professor of
bioengineering, said: 'Though scientists have only just
begun to explore creating artificial intelligence in
molecular machines, its potential is already undeniable.
'Similar to how electronic computers and smart phones
have made humans more capable than a hundred years ago,
artificial molecular machines could make all things made
of molecules – perhaps including even paint and bandages
– more capable and more responsive to the environment in
the hundred years to come.'
Unlike visual handwriting that varies in geometrical
shape, each example of molecular handwriting does not
actually take the shape of a number.
Instead, each molecular number is made up of 20 unique
DNA strands chosen from 100 molecules, each assigned to
represent an individual pixel in any 10 by 10 pattern.
These DNA strands are mixed together in a test tube.
Given a particular example of molecular handwriting, the
DNA neural network can classify it into up to nine
categories, each representing one of the nine possible
handwritten digits from 1 to 9.
First, the team built a DNA neural network to
distinguish between handwritten sixes and sevens.
They then tested 36 handwritten numbers and the test
tube neural network correctly identified all of them.
The system theoretically has the capability of
classifying over 12,000 handwritten sixes and sevens –
90 per cent of those numbers taken from a database of
handwritten numbers used widely for machine learning –
into the two possibilities.
Crucial to this process was encoding a 'winner take all'
competitive strategy using DNA molecules.
In this strategy, a particular type of DNA molecule
dubbed the annihilator was used to select a winner when
determining the identity of an unknown number.
The annihilator forms a complex with one molecule from
one competitor and one molecule from a different
competitor and reacts to form inert, unreactive species.
The annihilator quickly eats up all of the competitor
molecules until only a single competitor species
The winning competitor is then restored to a high
concentration and produces a fluorescent signal
indicating the networks' decision.
Next, the team built upon the principles of they first
DNA neural network to develop one even more complex, one
that could classify single digit numbers one through
The team now plan to develop artificial neural networks
that can learn, forming 'memories' from examples added
to the test tube.
In this way, they say, the same smart soup can be
trained to perform different tasks
The full findings were published in the journal Nature.
Recent events in Iceland have
highlighted the fact that there has been
a resurgence of paganism across Europe.
About 1000 years ago, paganism was
practically stamped out in Iceland,
while Christianity was ushered in. But
Nordic neopaganism, under the name of
Ásatrúarfélagið (sometimes called Asatru),
has now become the fastest growing
belief system in the country.
violence in two nations may threaten to
plunge the already restive Middle East
into a deeper conflict involving
regional and international powers,
according to the latest report by a