Nano AI - Match Made in Tech Heaven

This is essentially where AI and nanotechnology would intersect in a Venn diagram

were we to draw one.

AI certainly needs no introduction, with its fingerprints smeared across just about every

industry that has technology incorporated deep into it. By definition, AI is basically a

simulation of human intelligence on machines.

In other words, it is how a computer-controlled robot or a computer does tasks only

humans do because of one defining factor: they require human intelligence. AI heavily

relies on biological inspirations to develop some of its most common paragons—like the

neural chip.

Nanotechnology, on the other hand, is derived from nanometers – the measurement. If

it goes on in the dimensions of the nanometer scale, it falls under nanotechnology.

Throw in design, characterization, production and application of materials and voila! We

have a new field of science called nanotechnology.

How They Come Together

Having already looked at them individually, let’s have a look at how nano AI is born.

As I had earlier mentioned, nanotech deals with stuff in the nanometer scale so the tech

and deep learning hardware involved is often too intricate in nature. So much so that

they aren’t always tailored for all elements of AI. Be that as it may, there are some

areas where they integrate perfectly:

Chemical Modeling

In this case, some AI algorithms are used to illustrate the frameworks of a molecule or

material with the aim of finding out what they are made of and how they interact with

different environments.

This is just the tip of the iceberg. Naturally, more advanced and complex machine

learning algorithms have been incorporated for the same.

When going about chemical modeling, there are lots of parameters that need to be in

harmony to generate a dynamic depiction of a chemical system.

AI is quite adept at information analysis and with machine learning, it is possible to learn

from the past and make improvements. This self-learning process will lead to more

precise representation of the system under study. One way of achieving this is by

minimizing the size of a particle, which is very important for the nano part of this

operation. By the way, a nanometer is a billionth of a meter so lines don’t get any finer

really.

Microscopy

Microscopy is a field that refers to the viewing of samples and objects that are

impossible to see with the naked eye – try even visualizing a billionth of a meter

Yourself.

Microscopes and technology have come a long way although getting high-quality

signals from them and other imaging devices is still a tad challenging. The reason this

happens is most of these tip-sample interactions are complex and very hard to

decipher. Here is where AI comes in to smoothen these nanotech creases:

Using an approach called functional recognition imaging, it is possible to directly identify

local actions from measured spectroscopic reactions. Neural chips again are at the

center of it all, in cahoots with principal component analysis to streamline the input data

to the neural network.

Nanocomputing

Nanocomputing is a branch of tech that deals with nano computers. As you may already

have guessed, they are computers in the nanometer scale.

The most appropriate definition of nanocomputing would perhaps be a field that covers

the representation and manipulation of data by computers smaller than a

microcomputer with transistors smaller than 100 nanometers already being used.

Being all in the nanometer scale, these devices have to rely on very complex physical

systems and deep learning hardware to allow computing all on the nanoscale. Machine

learning and AI can be used to generate new information representations for whatever

need be.