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Breaking Down 21 Apple Product Flops from 1980 – 2014

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Breaking Down 21 Apple Product Flops from 1980 - 2014

Breaking Down 21 Apple Product Flops from 1980 – 2014

“Fail fast, fail often” is a common mantra that has circulated around Silicon Valley for years. However, there has been an outrage about its validity lately, especially as full-fledged funeral services mourn the remnants of startups past.

Despite this ongoing debate, Apple serves as an example of a company that has taken big product risks with their fair share of failure. At the same time, the company has had many runaway successes that have changed the world as we know it, helping the company’s market capitalization soar towards the coveted $1 trillion mark.

This culture of innovation comes with many quirks. Many of these product fails are ahead of their time such as Newton PDAs (1987), Macintosh TV (1993), and eWorld (1994). That said, many of these were also downright ridiculous. The “Hockey Puck” mouse (1998) serves as the best example of this: a perfectly circular, short, and clumsy mouse that would often do the opposite movement that a user wanted from the cursor.

Original graphics from: 7 Day Shop

Space Wars: The Private Sector Strikes Back

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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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