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Home»Machine-Learning»Use of Analog Computer systems in Synthetic Intelligence (AI)
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Use of Analog Computer systems in Synthetic Intelligence (AI)

By December 26, 2022Updated:December 26, 2022No Comments7 Mins Read
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Analog Computer systems are a category of gadgets by which bodily portions like electrical voltage, mechanical motions, or fluid strain are represented in order that they’re analogous to the corresponding quantity in the issue to be solved. 

Right here is a straightforward instance of an analog laptop.

If we flip the black and white wheels by sure quantities, the grey wheel reveals the sum of the 2 rotations.

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One of many earliest analog computer systems was The Antikythera  Mechanism, constructed round 100-200 B.C. It concerned a sequence of interlocking bronze gears in such a manner that the movement of sure dials was analogous to the movement of the solar and the moon. It was additionally able to predicting eclipses many years upfront.

Benefits & Disadvantages of Analog Computer systems

So as to add two eight-bit numbers, round 50 transistors are required. With an analog laptop, nonetheless, we will add two currents by merely connecting two wires. Equally, to multiply two numbers, we want 1000s of transistors. Quite the opposite, we will cross a present (I Ampere) by way of a resistor (R-Ohm), and the potential drop throughout the 2 ends of the wire can be I*R, i.e., the product of two numbers.

Analog computer systems are highly effective, quick, and vitality environment friendly. Nevertheless, digital computer systems changed them as a result of they’re single-purposed and inaccurate, and because the inputs are steady, it’s troublesome to repeat the method precisely.

Analog Computer systems & AI.

In AI, analog computer systems had been used for numerous duties, together with sample recognition, decision-making, and management. For instance, they had been used to coach neural networks, that are machine-learning fashions impressed by the human mind’s construction and performance. Analog computer systems had been additionally used to implement rule-based AI techniques that use particular guidelines to make choices or take actions. 

Regardless of their widespread use previously, analog computer systems are now not as frequent in AI and machine studying, largely because of the introduction of digital computer systems. Digital computer systems are a lot quicker and extra dependable than analog computer systems, and so they can retailer and course of a lot bigger quantities of information. Moreover, digital computer systems are simpler to program and keep, which has made them the popular alternative for many AI and machine studying functions.

The rise in the usage of Analog Computer systems in AI

There’s a rising development towards utilizing bigger neural networks in machine studying and synthetic intelligence functions. This development is pushed by the necessity to enhance efficiency on more and more complicated duties and the supply of extra information, {hardware}, and algorithms to help the coaching of bigger networks. Nevertheless, there are particular challenges related to this elevated demand.

  • Coaching a big neural community requires an quantity of vitality equal to the typical yearly consumption of round three households.
  • Each trendy laptop shops information in reminiscence and accesses it as wanted. However when neural networks require big matrix multiplications, more often than not, the vitality goes into fetching the worth of the weights moderately than performing the calculations.
  • In line with Moore’s Legislation, the variety of transistors on a chip has historically doubled each two years. Nevertheless, we at the moment are approaching the purpose the place the scale of a transistor is approaching the scale of an atom, which presents vital bodily challenges to additional miniaturization.

As digital computer systems strategy their limits, neural networks have gained widespread recognition, with a lot of their performance centered on matrix multiplication. Moreover, neural networks don’t require the exact calculations of digital computer systems, as a 98% or 95% confidence in classifying a picture as a canine is adequate. These elements current a chief alternative for analog computer systems to imagine a way more main position in AI.

Case Research: Mythic AI

Mythic AI is an analog computing startup that creates analog chips to run neural networks. Totally different AI algorithms, like movement detection, depth estimation, classification of objects, and many others., are run within the analog area.

Mythic has modified digital flash storage cells to make this doable. These cells are usually used for reminiscence storage and might maintain both a one or a zero. A constructive voltage utilized to the management gate permits electrons to cross by way of an insulating barrier and turn out to be trapped on the floating gate. The voltage can then be eliminated, and the electrons will stay on the floating gate for a very long time, stopping present from flowing by way of the cell. 

      Supply: https://www.youtube.com/watch?v=GVsUOuSjvcg&t=1128s

The saved worth may be decided by making use of a small voltage. No present will circulate if there are electrons on the floating gate, indicating a zero. If there aren’t any electrons, present will circulate, which means a one.

             Supply: https://www.youtube.com/watch?v=GVsUOuSjvcg&t=1128s

Mythic’s concept is to make use of these cells not as on/off switches however as variable resistors. They do that by placing a particular variety of electrons on every floating gate as a substitute of all or nothing. The higher the variety of electrons, the upper the channel’s resistance. When making use of a small voltage, the flowing present equals V over R. However it’s also possible to consider this as voltage instances conductance, the place conductance is simply the reciprocal of resistance. So a single flash cell can be utilized to multiply two values collectively, voltage instances conductance.

To make use of this to run a man-made neural community, they first write all of the weights to the flash cells as every cell’s conductance. Then, they enter the activation values because the voltage on the cells. And the ensuing present is the product of voltage instances conductance, which is activation instances weight. The cells are wired collectively in order that the present from every multiplication provides collectively, finishing the matrix multiplication.

              Supply: https://www.youtube.com/watch?v=GVsUOuSjvcg&t=1128s

Their chip can carry out 25 trillion math operations per second whereas utilizing solely 3W of energy. Quite the opposite, newer digital techniques can carry out 20-100 trillion math operations per second, however they’re expensive (1000s of {dollars}) and devour 50-100W of energy.

There have been ideas to make the most of analog circuitry in sensible house audio system particularly for the aim of detecting wake phrases reminiscent of “Alexa” or “Siri.” This strategy would require much less energy and permit for the fast and dependable activation of the digital circuitry within the gadget.

To sum up, it’s unsure if analog computer systems will turn out to be as prevalent as digital computer systems. Nevertheless, they’re higher suited to a wide range of present duties we would like computer systems to carry out, and possibly we may make machines obtain true intelligence by way of the ability of analog.


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References:

  • https://www.britannica.com/expertise/analog-computer
  • https://www.youtube.com/watch?v=GVsUOuSjvcg&t=1128s
  • https://www.youtube.com/watch?v=IgF3OX8nT0w


I’m a Civil Engineering Graduate (2022) from Jamia Millia Islamia, New Delhi, and I’ve a eager curiosity in Information Science, particularly Neural Networks and their software in numerous areas.


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