Because of its fragile condition and our inability to see inside it at that time, this mechanical conundrum was put on the backburner as perhaps an anachronism that was way too complex to have been created by ancient Greeks. However, beginning in the 1950s, much investigation has gone into deciphering its secrets. In fact, the latest studies show the level of miniaturisation of intricate gears within was on a par with 19th-century clocks.
It now appears this device performed many tasks. Composed of 30 gears and a number of faces and dials, it stakes a claim to being the first analog computer. Its internal construction and movements are based on astronomical and mathematical theories developed by Greek astronomers of the Hellenistic period. It’s thought to be possibly connected to Archimedes and his teachings because the inscriptions of the months on its face are those used in Corinth and its colonies, where he lived, and he was known for designing innovative machines.
With the use of modern, non-invasive methods to determine its interior structure, we came to understand it could predict the positions of the known planets, sun and moon, much like a modern planetarium. Furthermore, it could be used as a calendar with compensation for the extra quarter day of the solar year. As well as having a spherical model of the moon that could show its current phase, it could also forecast eclipses and simulate the anomaly in the moon’s angular velocity.
Brilliant - but there’s more. It indicated which years were to feature the Olympic Games, the Panhellenic Games and others. All this and more spell out an amazing genius, producing clockwork mechanisms way before we had the first clocks.
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![shychemist:
joshbyard:
“Google and Stanford have created the [digital equivalent of the] visual cortex of an infant human”
Jeff Dean and his team from Google, working with Andrew Ng and Quoc Le from Stanford University, have effectively created a rudimentary, low-resolution digital version of the brain’s visual cortex.
The system, which comprises of a cluster of 1,000 computers (totaling 16,000 processor cores), analyzes 10 million 200×200 still frames from YouTube. Over 3 days, the system’s software builds up a network of hundreds of neurons and thousands (millions?) of synapses. During this period, the system tries to identify features — edges, lines, colors — and then creates object categories based on these features.
The rather intriguing result is that, when the system looks at an image of a cat, a specific (digital) neuron fires — just like in a human brain. Watching the system in action — watching the neurons light up — is almost like performing a virtual, digital MRI scan. In the picture below, you can see the contents of the “human face” neuron, alongside some of the stimuli that successfully trigger the neuron.
(via Google and Stanford create a digital brain that, like an infant, learns to identify a human face from scratch | ExtremeTech)
This is pretty mind blowing stuff!
The robot/ AI age is happening so fast.](http://24.media.tumblr.com/tumblr_m68od0U8Wt1qgpcs1o1_500.jpg)





