Here is the MIT Technology Review’s annual list of technology that will change the course of human life.
The MIT annual report, titled 10 Breakthrough Technologies 2018, it features some of the advances in technology which have been in the pipeline for years, and there are others which are more latest advancements. Some of the technologies in the list may be commercially avaibale in recent furture.
Here are MIT’s 10 breakthrough technologies for 2018
3D metal printing:
While 3-D printing been around us for decades, It was mainly used by designers for producing the prototype of some components with use of plastic. The metal printing was expensive and time taking process.
Now it is becoming affordable and easier for manufacturing parts and if it will be adopted on a wide scale it can change the fate of the mass production in manufacturing industry.
Using this technology we can manufacture intricate, complex designed and stronger parts which were not possible through conventional methods. It can control the structure of the material at a micro level.
In 2017, researchers from the Lawrence Livermore National Laboratory announced they had developed a 3-D-printing method for creating stainless-steel parts twice as strong as traditionally made ones.
The metal parts printing is also getting easier with help of software.
“Desktop Metal” offers software that generates designs ready for 3-D printing only users have to tell the program about specs of the job and software itself generates a computer model which is suitable for printing.
Breakthrough: Now 3D-printers can produce metal jobs faster and affordable price.
Why It Matters: It will be a paradigm shift for manufacturing industry if this technology employed for large and complex designs.
Key Players: Mark forged, Desktop Metal & GE
This breakthrough can lead us to know how life was created. Embryologists working At the University of Cambridge, embryologists have developed a realistic looking mouse with use of stem cell. There was no use of egg or sperms, just cells plucked from another embryo.
“We know that stem cells are magical in their powerful potential of what they can do. We did not realize they could self-organize so beautifully or perfectly,” Magdelena Zernicka-Goetz, who headed the team, told an interviewer at the time.
Synthetically developed human embryos will be a boon to scientists. Since these embryos developed with easily manipulated stem cells, there is the obvious scope of gene editing.
Breakthrough: Researchers have developed an embryo-like structure with stem cell. There was no use of egg or sperms, just cells plucked from another embryo.
Why It Matters: Artificial embryos will make it easier for researchers to study the mysterious beginnings of human life, but they’re stoking new bioethical debates.
Key Players: University of Cambridge; University of Michigan; Rockefeller University
We have seen numerous schemes for smart cities in past but, either these schemes & projects are delayed or stopped due to heavy fund requirements.
The future of building smart cities is going to change with proper use of the latest digital technology. Quayside, a project in Toronto is started by Alphabet’s Sidewalk Labs, based in New York City, with collaboration with the Canadian government, slated for Toronto’s industrial waterfront.
Major project goals are, gathering of data for everything including air quality, noise level and even people’s activity with the extensive network of sensors.
There is a plan for autonomous and shared vehicles, underground passage for robots to execute menial activities like mail delivery, monitoring etc. As per Sidewalk Labs, they will provide open access through API for their software and systems for making it easier for other companies to build services.
Breakthrough: Quayside, a project in Toronto is started by
Alphabet’s Sidewalk Labs, based in New York City, with collaboration with the Canadian government, slated for Toronto’s industrial waterfront with help of the latest digital technology.
Why It Matters: Affordable and environmentally friendly infrastructure
Key Players: Sidewalk Labs and Waterfront Toronto
Availability: The Project announced in October 2017; construction could begin in 2019
AI for Everybody
Artificial Intelligence has been used mainly by bigger companies like Amazon, Google, Microsoft, Samsung, and Apple. For most of the companies use of AI is extremely difficult to implement and also it is expensive.
The machine learning tools accessed through cloud computing making is available for bigger audiences. The bigger companies are dominating cloud services through their subsidiaries like Amazon with its AWS subsidiary, Google with TensorFlow. But an open-source AI library that can be used to build other machine-learning software. Recently Google announced Cloud AutoML, a suite of pre-trained systems that could make AI simpler to use.
It is uncertain which of these companies will become the leader in offering AI cloud services. But it is a huge business opportunity for the winners.
Breakthrough: Cloud-based AI is making the technology cheaper and easier to use.
Why It Matters: Right now the use of AI is dominated by relatively few companies, but as a cloud-based service, it could be widely available to many more, giving the economy a boost.
Key Players: Amazon; Google; Microsoft
Dueling Neural Networks
Artificial intelligence is getting better day by day at identifying objects. show it a million pictures, and it can tell you with accuracy that which ones depict a footpaths on streets. But AI doesn’t help to generate pictures 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 problem is, creating something entirely new requires imagination—and until now that has perplexed AIs.
The solution first occurred to Ian Goodfellow, then a Ph.D. student at the University of Montreal, during an academic argument in a bar in 2014. 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.
Both networks are trained on the same data set. One, known as the generator, is tasked with creating variations on images it’s already seen—perhaps a picture of a pedestrian with an extra arm. The second, known as the discriminator, is asked to identify whether the example it sees is like the images it has been trained on or a fake produced by the generator—basically, is that three-armed person likely to be real?
Over time, the generator can become so good at producing images that the discriminator can’t spot fakes. Essentially, the generator has been taught to recognize, and then create, realistic-looking images of pedestrians.
The technology has become one of the most promising advances in AI in the past decade, able to help machines produce results that fool even humans.
Breakthrough: Two AI systems can spar with each other to create ultra-realistic original images or sounds, something machines have never been able to do before.
Why It Matters: This gives machines something akin to a sense of imagination, which may help them become less reliant on humans—but also turns them into alarmingly powerful tools for digital fakery.
Key Players: Google Brain, DeepMind, Nvidia
Earbud and Mobile interface, The person wearing earbud speaks in his or her language and app translates the talking language and plays on mobile. The second person using mobile responds and this response is translated back to the language used by earbud wearer.
This feature is already used by Google Translate. but in this interface mobiles are used and background noise makes it harder to understand the language by the app.
These earbuds resolved above problem and splitting the interaction between phone and earbud gives control over the conversation.
The Pixel Buds were widely panned for subpar design. They do look silly, and they may not fit well in your ears. They can also be hard to set up with a phone.
Breakthrough: Real-time translation that works for many languages.
Why It Matters: It removes one barrier of communication which is language.
Key Players: Google and Baidu
Zero-Carbon Natural Gas
Natural gas is our primary source of electricity. It accounts for more than the 22 percent of electricity production in the world. It is cleaner than coal but it is still a massive source of carbon emission.
A pilot power plant just outside Houston, in the heart of the US petroleum and refining industry, is testing a technology that could make clean energy from natural gas a reality. The company behind the 50-megawatt project, Net Power, believes it can generate power at least as cheaply as standard natural-gas plants and capture essentially all the carbon dioxide released in the process.
If so, it would mean the world has a way to produce carbon-free energy from fossil fuel at a reasonable cost. Such natural-gas plants could be cranked up and down on demand, avoiding the high capital costs of nuclear power and sidestepping the unsteady supply that renewables generally provide.
Net Power is a collaboration between technology development firm 8 Rivers Capital, Exelon Generation, and energy construction firm CB&I. The company is in the process of commissioning the plant and has begun initial testing. It intends to release results from early evaluations in the months ahead.
The plant puts the carbon dioxide released from burning natural gas under high pressure and heat, using the resulting supercritical CO2 as the “working fluid” that drives a specially built turbine. Much of the carbon dioxide can be continuously recycled; the rest can be captured cheaply.
A key part of pushing down the costs depends on selling that carbon dioxide. Today the main use is in helping to extract oil from petroleum wells. That’s a limited market and not a particularly green one. Eventually, however, Net Power hopes to see growing demand for carbon dioxide in cement manufacturing and in making plastics and other carbon-based materials.
Breakthrough: A power plant efficiently and cheaply captures carbon released by burning natural gas, avoiding greenhouse-gas emissions.
Why It Matters: Around 32 percent of US electricity is produced with natural gas, accounting for around 30 percent of the power sector’s carbon emissions.
Key Players: 8 Rivers Capital; Exelon Generation; CB&I
Availability: 3 to 5 years
Perfect Online Privacy
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.
Much of the credit for a practical zero-knowledge proof goes to Zcash, a digital currency that launched in late 2016. Zcash’s developers used a method called a zk-SNARK (for “zero-knowledge succinct non-interactive argument of knowledge”) to give users the power to transact anonymously.
That’s not normally possible in Bitcoin and most other public blockchain systems, in which transactions are visible to everyone. Though these transactions are theoretically anonymous, they can be combined with other data to track and even identify users. Vitalik Buterin, the creator of Ethereum, the world’s second-most-popular blockchain network, has described zk-SNARKs as an “absolutely game-changing technology.”
or banks, this could be a way to use blockchains in payment systems without sacrificing their clients’ privacy. Last year, JPMorgan Chase added zk-SNARKs to its own blockchain-based payment system.
Breakthrough: Computer scientists are perfecting a cryptographic tool for proving something without revealing the information underlying the proof.
Why It Matters: If you need to disclose personal information to get something done online, it will be easier to do so without risking your privacy or exposing yourself to identity theft.
Key Players: Zcash; JPMorgan Chase; ING
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 or 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.”
Though the new DNA tests offer probabilities, not diagnoses, they could greatly benefit medicine. For example, if women at high risk for breast cancer got more mammograms and those at low risk got fewer, those exams might catch more real cancers and set off fewer false alarms.
Pharmaceutical companies can also use the scores in clinical trials of preventive drugs for such illnesses as Alzheimer’s or heart disease. By picking volunteers who are more likely to get sick, they can more accurately test how well the drugs work.
The trouble is, the predictions are far from perfect. Who wants to know they might develop Alzheimer’s? What if someone with a low risk score for cancer puts off being screened, and then develops cancer anyway?
Polygenic scores are also controversial because they can predict any trait, not only diseases. For instance, they can now forecast about 10 percent of a person’s performance on IQ tests. As the scores improve, it’s likely that DNA IQ predictions will become routinely available. But how will parents and educators use that information?
Breakthrough: Scientists can now use your genome to predict your chances of getting heart disease or breast cancer, and even your IQ.
Why It Matters: DNA-based predictions could be the next great public health advance, but they will increase the risks of genetic discrimination.
Key Players: Helix; 23andMe; Myriad Genetics; UK Biobank; Broad Institute
Materials’ Quantum Leap
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 an 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 liquid fuel, and much more efficient solar cells.
We don’t have these things because molecules are ridiculously hard to model on a classical computer. Try simulating the behavior of the electrons in even a relatively simple molecule and you run into complexities far beyond the capabilities of today’s computers.
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.
Breakthrough: IBM has simulated the electronic structure of a small molecule, using a seven-qubit quantum computer.
Why It Matters: Understanding molecules in exact detail will allow chemists to design more effective drugs and better materials for generating and distributing energy.
Key Players: IBM; Google; Harvard’s Alán Aspuru-Guzik
Availability: 5 to 10 years