Plotting The World’s Exponential Technological Progress

Exponential growth is essential. In May 2020 I wrote the #TejTalks blog about how my Kohli Ventures funding car focused on arriving at exponential growth options early. Then in an interview on I talked about how I’m pursuing a second wave of CRISPR-Cas9 because I think the technology is within early levels of exponential growth.

Exponential technological progress matters because it is well established that technological change improves the total wealth in a society and this in turn reduces poverty and extreme poverty. The biggest reasons behind my not-for-profit Tej Kohli Foundation’s unnecessary blindness won’t be cataracts or corneal infections – they are merely signs of the truth that the world could possibly be avoided or handled in the creation of more than 80% of blindness. The real underlying trigger is poverty.

As I wrote in an August 2020 #TejTalks post, the tech information switch has the potential to be one of the many biggest catalysts for poverty reduction around the world. And so it follows that as the world experiences technological progress, poverty and extreme poverty usually fall, and the consequences of poverty, analogous to untreated blindness, usually fall as well.

And because of we are now able to plot and measure technological progress and because of this fact we can understand it better.

Moore’s regulation is the remark that transistor diversity on built-in circuits doubles approximately every two years. This side of technological advancement is essential because the capabilities of many digital digital gadgets are strongly tied to Moore’s regulation. Within the chart below we can see how features have grown exponentially in digital cameras in terms of processing speed, product price, recall capability, and even the amount and measurement of pixels:

Moore’s Law was developed in early 1965 by Intel co-founder Gordon E. Moore, after whom it is named. Discover the famous small graph revealed by Moore in 1965:

As you can see, Moore made only seven observations from 1959 to 1965, although he predicts persistence with evolution, saying “there is no reason to consider that it would have been around for at least 10 years.” Won’t be stable”. Because it turned out, Moore was not only right about the next ten years, but the surprisingly regularity he found has been true for more than half a century now:

Moore’s opening remarks are necessary because it affirms that technological progress does not progress linearly, though rapidly. However, in itself, a doubling of transistors every two years doesn’t immediately make a difference in our lives.

So let’s ask as an alternative, in what ways the exponential growth of information and the way in which exponential technological development is a driver of technological and social change, which are a lot of issues in our lives now.

Perhaps more importantly for us, the convenience and speed of computer systems has grown exponentially; The doubling time of computational capacity for personal computer systems was 1.5 years between 1975 and 2009. The growing energy of a wide variety of computer systems – starting with the Primary Normal Function Laptop (ENIAC) in 1946 – is proven in black and white charts. Down:

Within the latter chart, which is up to date 12 months 2020, we can see that the expansion of supercomputer energy is measured through a variety of floating-point operations performed per second (FLOPS) by the most significant. Supercomputers in a given 12 months:

FLOPS is a measure of counts per second for floating-point operations. Floating-point operations are wanted for very large scales or very small real numbers, or computations that require a large dynamic variance. This is due to the fact that only one additional correct is measured per second than the directions.

While some technological changes follow a continuous linear development, we see that many technological improvements follow a non-linear path. This non-linearity is most clearly seen in examples that present rapid development following a necessary enabling innovation, such as the take-off of human flight and the sequencing of the human genome.

The chart above documents the worldwide distances determined by non-commercial flights since 1800. This document represents the maximum distance traveled by a non-commercial operated aircraft without refueling.

We see that prior to 1900, people had not developed the necessary information to allow powered flight. It was not until 1903 that the Wright Brothers were in a position to engineer the primary powered flight technology.

This early innovation continued, with rapid advances in modern aviation, with document distances increasing nearly 150,000-fold from 0.28 kilometers in 1903 to just under 41,500 kilometers in 2006.

It offers an example of the non-linear evolution of technological change: a singular opportunity moved us from a civilization that was unable to fly, to at least one that could, and suddenly we became an extra connected turned into a world group. Advances in aviation – and exploration of the field – have been rapid since then.

Another example that demonstrates non-linear technological progress is the field of DNA sequencing of the human genome. The Human Genome Project (HGP), which aims to trace and map the entire set of nucleotide base pairs that make up human DNA (which is more than three billion), ran for 13 years from 1990-2003. This early discovery and dedication of the human genome sequence was an important injection level into the subject of DNA sequencing.

As reported by the NHGRI Genome Sequencing Program (GSP), the cost of DNA sequencing has dropped dramatically (more than 175,000-fold) since the completion of the first sequencing venture. This rapid drop in price can also be seen in the prices for sequencing the entire human genome:

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