Photo by Kinga Cichewicz on Unsplash

In 2014, I felt relief when a scientific paper confirmed that precrastination is, indeed, a thing. The meta irony that I’d already coined the term myself did not escape me.

https://lalonshah540.medium.com/how-the-pandemic-is-helping-me-kick-a-bad-work-habit-7b77b3b05e4
https://lalonshah540.medium.com/how-the-pandemic-is-helping-me-kick-a-bad-work-habit-1df79b005629

Sorry, I’m getting ahead of myself (as usual): Procrastinators put off cleaning…

The causal mechanism behind disruption that Grove so quickly understood was that even if a disruptive innovation started off as inferior, by virtue of it dramatically expanding the market, it would improve at a far greater rate than the incumbent. It was what enabled Intel (and Microsoft) to win the computing market in the first place: even though personal computers were cheaper, selling something that sat in every home and on every desk ends up funding a lot more R&D spend than selling a few very expensive servers that only existed in server rooms.Similarly, Apple’s initial foray into chips didn’t produce anything that special in terms of silicon. But it didn’t need to — people were happy to just have a computer that they could keep in their pocket. Apple has gone on to sell a lot of iPhones, and all those sales have funded a lot of R&D. The silicon inside them has kept improving, and improving, and improving. And their fab partner, TSMC, has gone along with them for the ride.In the world of High-Frequency Trading, automated applications process hundreds of millions of market signals every day and send back thousands of orders on various exchanges around the globe.

Let’s start with the most general role, data scientist. Being a data scientist entails, you will deal with all aspects of the project. Starting from the business side to data collecting and analyzing, and finally visualizing and presting.

What about this chart is interesting? Well, it turns out, it bears…

The causal mechanism behind disruption that Grove so quickly understood was that even if a disruptive innovation started off as inferior, by virtue of it dramatically expanding the market, it would improve at a far greater rate than the incumbent. It was what enabled Intel (and Microsoft) to win the computing market in the first place: even though personal computers were cheaper, selling something that sat in every home and on every desk ends up funding a lot more R&D spend than selling a few very expensive servers that only existed in server rooms.Similarly, Apple’s initial foray into chips didn’t produce anything that special in terms of silicon. But it didn’t need to — people were happy to just have a computer that they could keep in their pocket. Apple has gone on to sell a lot of iPhones, and all those sales have funded a lot of R&D. The silicon inside them has kept improving, and improving, and improving. And their fab partner, TSMC, has gone along with them for the ride.In the world of High-Frequency Trading, automated applications process hundreds of millions of market signals every day and send back thousands of orders on various exchanges around the globe.

Let’s start with the most general role, data scientist. Being a data scientist entails, you will deal with all aspects of the project. Starting from the business side to data collecting and analyzing, and finally visualizing and presting.

What about this chart is interesting? Well, it turns out, it bears…

The causal mechanism behind disruption that Grove so quickly understood was that even if a disruptive innovation started off as inferior, by virtue of it dramatically expanding the market, it would improve at a far greater rate than the incumbent. It was what enabled Intel (and Microsoft) to win the computing market in the first place: even though personal computers were cheaper, selling something that sat in every home and on every desk ends up funding a lot more R&D spend than selling a few very expensive servers that only existed in server rooms.Similarly, Apple’s initial foray into chips didn’t produce anything that special in terms of silicon. But it didn’t need to — people were happy to just have a computer that they could keep in their pocket. Apple has gone on to sell a lot of iPhones, and all those sales have funded a lot of R&D. The silicon inside them has kept improving, and improving, and improving. And their fab partner, TSMC, has gone along with them for the ride.In the world of High-Frequency Trading, automated applications process hundreds of millions of market signals every day and send back thousands of orders on various exchanges around the globe.

Let’s start with the most general role, data scientist. Being a data scientist entails, you will deal with all aspects of the project. Starting from the business side to data collecting and analyzing, and finally visualizing and presting.

What about this chart is interesting? Well, it turns out, it bears…

Photo illustration, source: Cristian Newman/Unsplash

300,000 to 500,000: That’s how many fewer babies the think tank Brookings Institution projects will be born in the United States next year. Birth rates in the United States were already steadily declining before the pandemic, but the latest projection is a steep drop from the 3.7 …

Andrew R. Joseph

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