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The Supercomputer In Your Pocket

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The Supercomputer in Your Pocket

The Supercomputer in Your Pocket

We have mentioned here many times that the exponential rise in technology creates unprecedented opportunities for investors. Smaller and faster computers have led to emerging fields such as big data, the internet of things, cybersecurity, and the mobile payments revolution.

It all stems from Moore’s Law, which is based on observations made as early as 1965 by Gordon E. Moore, the co-founder of Intel. Moore suggested that the number of transistors in a dense integrated circuit would double approximately every two years, creating an exponential rise in computing potential.

However, for many this whole “exponential” thing is hard to wrap our heads around. Most of our daily observations are on a linear level, meaning that relationships hold true at a fixed rate. For example, if one wishes to bake a chocolate cake that is twice the size as a given recipe, the ingredients are to be doubled. If one is buying three cartons of milk from the grocery store, the cost will be three times higher.

Exponential Growth

Here’s an example of an exponential situation that just doesn’t feel intuitive. For the full version, which is worth reading, go to Peak Prosperity as they explain the compounding problem. Otherwise I will paraphrase:

Imagine that you are in Fenway Park, that the stadium is watertight, and you are handcuffed to the very highest bleacher seats. Meanwhile a drop of water is dropped on the pitcher’s mound, and the amount of water dropping will double every minute. How long do you have to escape from the handcuffs before drowning? Minutes, hours, days, years?

The answer turns out to be 49 minutes. Even more interesting is that most people wouldn’t be aware of how dire the situation until about 45 minutes, when the stadium is about 7% full of water and about to double yet again.

This example illustrates exponential growth. Applied to technology, it means that even though we have seen big advances over the last few decades with the emergence of personal computers, smartphones, and even smaller connected devices, the best is still yet to come.

Quantum computing and general artificial intelligence are approaching us faster than we may know.

Original graphic by: Fonebank

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Technology

Charted: The Jobs Most Impacted by AI

We visualized the results of an analysis by the World Economic Forum, which uncovered the jobs most impacted by AI.

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Charted: The Jobs Most Impacted by AI

This was originally posted on our Voronoi app. Download the app for free on iOS or Android and discover incredible data-driven charts from a variety of trusted sources.

Large language models (LLMs) and other generative AI tools haven’t been around for very long, but they’re expected to have far-reaching impacts on the way people do their jobs. With this in mind, researchers have already begun studying the potential impacts of this transformative technology.

In this graphic, we’ve visualized the results of a World Economic Forum report, which estimated how different job departments will be exposed to AI disruption.

Data and Methodology

To identify the job departments most impacted by AI, researchers assessed over 19,000 occupational tasks (e.g. reading documents) to determine if they relied on language. If a task was deemed language-based, it was then determined how much human involvement was needed to complete that task.

With this analysis, researchers were then able to estimate how AI would impact different occupational groups.

DepartmentLarge impact (%)Small impact (%)No impact (%)
IT73261
Finance70219
Customer Sales671617
Operations651817
HR57412
Marketing56413
Legal46504
Supply Chain431839

In our graphic, large impact refers to tasks that will be fully automated or significantly altered by AI technologies. Small impact refers to tasks that have a lesser potential for disruption.

Where AI will make the biggest impact

Jobs in information technology (IT) and finance have the highest share of tasks expected to be largely impacted by AI.

Within IT, tasks that are expected to be automated include software quality assurance and customer support. On the finance side, researchers believe that AI could be significantly useful for bookkeeping, accounting, and auditing.

Still interested in AI? Check out this graphic which ranked the most commonly used AI tools in 2023.

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