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Ovi Hentea
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Simple formula to what to seek out in your 20s

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"New Babylon envisages a society of total automation in which the need to work is replaced with a nomadic life of creative play"

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“...Vehicle autonomy [has] some profound consequences beyond the car industry itself...

If parking goes away, road capacity increases by, perhaps, several times, and an on-demand ride is the cost of a coffee, then one needs to start thinking much more generally, not just about cars, trucks and roads but cities, land use and real-estate.

In fact, one needs to think about cities. Cars have remade cities over the past century, and if cars are now going to change entirely, cities will change too."

- Benedict Evans, Investor. Learn More on Benedict Evan's Blog

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A very digestible explanation of the usefulness of basic economic concepts

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"The National School Lunch Program was pushed through Congress after World War II with the support of military leaders who wanted to ensure that there would be enough healthy young men to fight the next war, and of farmers who were looking for a place to unload their surplus corn, milk and meat.

The result was that schools became the dumping ground for the cheap calories our modern agricultural system was designed to overproduce."

#education #food #school #nutrition

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Insightful article into how Google Translate got stealth-upgraded to machine translation - and just how much better it is than before.
The Story of Google's Revolution in Machine Translation

This is a piece of history that just unfolded this year, and this NYT piece captures it beautifully. It's the bigger story of artificial intelligence. It's that story, zoomed in on a big bet to run Google Translate on machine learning.

There are so many interesting parts to this piece. I'll highlight this one about the training process though:

“We did hundreds of experiments,” Schuster told me, “until we knew that we could stop the training after one week. You’re always saying: When do we stop? How do I know I’m done? You never know you’re done. The machine-learning mechanism is never perfect. You need to train, and at some point you have to stop. That’s the very painful nature of this whole system. It’s hard for some people. It’s a little bit an art — where you put your brush to make it nice. It comes from just doing it. Some people are better, some worse.”

And this, on some of the employment implications to machine learning inching into Natural Language Processing:

Once you’ve built a robust pattern-matching apparatus for one purpose, it can be tweaked in the service of others. One Translate engineer took a network he put together to judge artwork and used it to drive an autonomous radio-controlled car. A network built to recognize a cat can be turned around and trained on CT scans — and on infinitely more examples than even the best doctor could ever review. A neural network built to translate could work through millions of pages of documents of legal discovery in the tiniest fraction of the time it would take the most expensively credentialed lawyer. The kinds of jobs taken by automatons will no longer be just repetitive tasks that were once — unfairly, it ought to be emphasized — associated with the supposed lower intelligence of the uneducated classes. We’re not only talking about three and a half million truck drivers who may soon lack careers. We’re talking about inventory managers, economists, financial advisers, real estate agents. What Brain did over nine months is just one example of how quickly a small group at a large company can automate a task nobody ever would have associated with machines.

Thanks to +Alex Herrero for bringing this to my attention.

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How meditation can help you see beyond the stresses of the self-composed story we call our life.

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Go vote, America!

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Incredible use of 3D printing to make food that grows over time! How much fresher can you get than 5 day old mushrooms and herbs?
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