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10 BREAKTHROUGH TECHNOLOGIES 2018 by MIT Technology Review
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By: Marc Andrei
| In: Technology
Dueling neural networks. Artificial embryos. AI in the cloud. Here are the 10 breakthrough technologies in 2018, so far, by MIT Technology Review.
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The prospect of powerful new quantum computers comes with a puzzle. They’ll be capable of feats of computation inconceivable with today’s machines, but we haven’t yet figured out what we might do with those powers.
One likely and enticing possibility: precisely designing molecules.
Chemists are already dreaming of new proteins for far more effective drugs, novel electrolytes for better batteries, compounds that could turn sunlight directly into a liquid fuel, and much more efficient solar cells.
But it’s a natural problem for quantum computers, which instead of digital bits representing 1s and 0s use “qubits” that are themselves quantum systems. Recently, IBM researchers used a quantum computer with seven qubits to model a small molecule made of three atoms.
One likely and enticing possibility: precisely designing molecules.
Chemists are already dreaming of new proteins for far more effective drugs, novel electrolytes for better batteries, compounds that could turn sunlight directly into a liquid fuel, and much more efficient solar cells.
But it’s a natural problem for quantum computers, which instead of digital bits representing 1s and 0s use “qubits” that are themselves quantum systems. Recently, IBM researchers used a quantum computer with seven qubits to model a small molecule made of three atoms.
 
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One day, babies will get DNA report cards at birth. These reports will offer predictions about their chances of suffering a heart attack or cancer, of getting hooked on tobacco, and of being smarter than average.
The science making these report cards possible has suddenly arrived, thanks to huge genetic studies—some involving more than a million people.
It turns out that most common diseases and many behaviors and traits, including intelligence, are a result of not one or a few genes but many acting in concert. Using the data from large ongoing genetic studies, scientists are creating what they call “polygenic risk scores.”
The science making these report cards possible has suddenly arrived, thanks to huge genetic studies—some involving more than a million people.
It turns out that most common diseases and many behaviors and traits, including intelligence, are a result of not one or a few genes but many acting in concert. Using the data from large ongoing genetic studies, scientists are creating what they call “polygenic risk scores.”
 
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True internet privacy could finally become possible thanks to a new tool that can—for instance—let you prove you’re over 18 without revealing your date of birth, or prove you have enough money in the bank for a financial transaction without revealing your balance or other details. That limits the risk of a privacy breach or identity theft.
The tool is an emerging cryptographic protocol called a zero-knowledge proof. Though researchers have worked on it for decades, interest has exploded in the past year, thanks in part to the growing obsession with cryptocurrencies, most of which aren’t private.
The tool is an emerging cryptographic protocol called a zero-knowledge proof. Though researchers have worked on it for decades, interest has exploded in the past year, thanks in part to the growing obsession with cryptocurrencies, most of which aren’t private.
 
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NET Power is developing a power production facility that uses oxyfuel combustion in a unique process where CO2 is recycled to reduce the fuel and oxygen requirements.
 
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In the cult sci-fi classic The Hitchhiker’s Guide to the Galaxy, you slide a yellow Babel fish into your ear to get translations in an instant. In the real world, Google has come up with an interim solution: a $159 pair of earbuds, called Pixel Buds. These work with its Pixel smartphones and Google Translate app to produce practically real-time translation.
 
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Artificial intelligence is getting very good at identifying things: show it a million pictures, and it can tell you with uncanny accuracy which ones depict a pedestrian crossing a street. But AI is hopeless at generating images of pedestrians by itself. If it could do that, it would be able to create gobs of realistic but synthetic pictures depicting pedestrians in various settings, which a self-driving car could use to train itself without ever going out on the road.
. The approach, known as a generative adversarial network, or GAN, takes two neural networks—the simplified mathematical models of the human brain that underpin most modern machine learning—and pits them against each other in a digital cat-and-mouse game.
. The approach, known as a generative adversarial network, or GAN, takes two neural networks—the simplified mathematical models of the human brain that underpin most modern machine learning—and pits them against each other in a digital cat-and-mouse game.
 
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Artificial intelligence has so far been mainly the plaything of big tech companies like Amazon, Baidu, Google, and Microsoft, as well as some startups. For many other companies and parts of the economy, AI systems are too expensive and too difficult to implement fully.
What’s the solution? Machine-learning tools based in the cloud are bringing AI to a far broader audience.
What’s the solution? Machine-learning tools based in the cloud are bringing AI to a far broader audience.
 
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Smart Cities Toronto - the newly announced joint project between Sidewalk Labs (owned by Google) and Waterfront Toronto, to develop a brand new smart city neighbourhood near downtown toronto called Quayside. Toronto was picked to be a smart city after the Smart Cities initiative sent out by Google because it has all the criteria Google and Sidewalk Labs was looking for. The idea here is to model a city of the future that other cities around the world can be built like - using smart technology, improving transportation, addressing affordable housing, and addressing environmental and clean renewable energy concerns.
 
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CAMBRIDGE, UNITED KINGDOM — UK scientists have successfully grown a mouse embryo in the lab using only stem cells, which indicates this procedure could be eventually applied to growing artificial human embryos.
Researchers at the University of Cambridge extracted the embryonic stem cells and the extra-embryonic trophoblast stem cells, which will form the placenta, from a mouse. The two types of cells were then mixed, placed on a 3D scaffold and grown in a tank of chemicals that mimics the conditions inside the womb. The cells were able to grow and formed a structure that very closely resembled a natural mouse embryo after 96 hours.
Researchers at the University of Cambridge extracted the embryonic stem cells and the extra-embryonic trophoblast stem cells, which will form the placenta, from a mouse. The two types of cells were then mixed, placed on a 3D scaffold and grown in a tank of chemicals that mimics the conditions inside the womb. The cells were able to grow and formed a structure that very closely resembled a natural mouse embryo after 96 hours.
 
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100 times faster and 20 times cheaper than laser-based 3D metal printers, this system could revolutionize manufacturing by making the cost and speed of 3D metal printing competitive with traditional processes like casting, machining and forging.
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