2018The top 10 emerging technologies of the year: AI, quantum computing, augmented reality, etc.
9On January 19, the World Economic Forum and Scientific Americans jointly released a list of the top 10 emerging technologies for the year 2018. Artificial intelligence, biomedicine, and new materials are among the top 10 emerging technologies that are expected to bring new solutions to cancer treatment. These technologies are considered to be social in the next 3~5 years.Has an important impact on the economy.
《Scientific American and the world economic forum jointly released the ten new technologies of the world in 2018. The list, which covers biomedicine, chemistry and computing, was jointly selected by Scientific American, the Scientific American Global Advisory Committee, the World Economic Forum Global Expert Network, and the World Future Committee.The latest technology in machine, artificial intelligence and so on. Although these technologies are still in their early stages of development, they have attracted the attention of many research teams and are widely favored by investors. In the next 3~5 years, they may have an important impact on society and economy.
How will technological innovation change our lives in the near future? Artificial intelligence will greatly speed up the development of new drugs and materials; new diagnostic tools will create more advanced personalized medicine; augmented reality will become ubiquitous, and the real world will be flooded with information and animation from everyday tasks to industrial productionCovered; once you get sick, doctors can transplant living cells into your body and use these “drug factories” to treat you; the beef, chicken, and fish you eat may be grown in the laboratory with stem cells, which will greatly reduce the environmental damage caused by animal husbandry.
Together with other emerging technologies, these ideas are enough to change the world to make up the top 10 emerging technologies of the world in 2018. This list includes:
Ubiquitous augmented reality technology
Augmented reality is everywhere — the world is about to be covered by data.
Augmented Reality (AR) is a technology that covers the real world with computer generated information in real time. A large number of consumer oriented applications use the AR function. In the future, the technology will also support museums in making holographic guides, allowing three-dimensional visualization of patients’tissues to surgeons, and helping.Help beginners learn all kinds of technologies from medicine to factory maintenance.
Over the next few years, software that is simple to use to design applications will meet more consumer needs. For the moment, AR has a huge impact on industry, and it is an integral part of “Industry 4.0”: promoting systemic transformation of manufacturing by integrating real and digital systemsIn order to improve product quality, reduce costs and improve efficiency.
Some market analysts believe that AR is moving towards the mainstream market. They estimate that they are now valued at $1 billion 500 million, and the AR market will reach US $100 billion in 2020. And apple, Google, Microsoft and other large technology companies are related to AR and VR products and should.Invest a lot of money and talents with programs.
With the advent of cheaper, faster mobile chips that support AR technology, the introduction of more versatile smart glasses into the market and the increase in bandwidth, the field will develop rapidly. Subsequently, augmented reality will join the Internet, and real-time video will become an integral part of our daily lives.
Advanced diagnostic technology for personalized medicine
Private custom diagnostic tool — the traditional treatment plan to end the thousand person drug
In twentieth Century, most women with breast cancer used the same treatment regimen. But now treatments are becoming more personalized: breast cancer is divided into different subtypes, each with its own unique treatment.
Thanks to the progress of diagnostic tools, the development of personalized and precise treatment has been speeded up. These techniques help physicians identify and quantify biomarkers (molecules in the body that indicate homeostasis disorders) that differentiate patients into subgroups based on their susceptibility to disease, prognosis, and the most likely response to drugs.Type.
Early molecular diagnostic tools only observe single molecules, for example, for diabetics only monitor blood sugar. But in the past decade, biomimetic techniques have made breakthroughs: the ability to quickly and accurately sequence an individual’s entire genome in body fluid or tissue samples, or to measure all protein levels.Metabolic by-products or microorganisms.
New diagnostic tools have begun to transform the standard of disease diagnosis and treatment. Providing patients with the most effective treatment for them can even reduce medical expenses. Maybe one day, many of us will have our own unique cloud of biomarker data that will accumulate and be able toProvide information for doctors at any place that treats us.
Artificial intelligence technology in molecular design
Artificial Intelligence Aided Chemical molecular design — machine learning algorithm to accelerate the development of new drugs and materials
Whether designing new solar materials, anticancer drugs, or antiviral compounds for crops, there are two problems to be solved: finding the right chemical structure and determining which chemical reactions will connect the right atoms to the desired molecules.
If traditional methods are used, the answers to these questions often come from complex guesses and unexpected discoveries. This process is time-consuming and requires many failed attempts. Now, artificial intelligence is improving the efficiency of designing and synthesizing chemical molecules, helping businesses solve synthetic problems faster and more economically.
Machine learning algorithms can analyze all known synthetic experiments, both successful and unsuccessful. Based on the identified patterns, these algorithms can predict potential, useful new molecular structures and possible generation methods.
Generative machine learning, a new technology based on artificial intelligence, is equally exciting in the pharmaceutical field. Most pharmaceutical companies need millions of compounds to screen for the production of new drugs. This screening process is very slow, and the effective results are relatively small. Using descriptions of known drugs (andCandidate Drugs) Datasets of chemical structures and properties, and machine learning tools can find new compounds with similar but potentially more useful properties.
Nearly 100 start-ups are exploring artificial intelligence methods for developing new drugs. Recently, Benevolent AI raised $115 million to apply its artificial intelligence technology to drug development for motor neuron disease, Parkinson’s disease and other refractory diseases.
Artificial intelligence system that will debate
Artificial intelligence that will debate: the ability of new algorithms to give personal devices to topics for discussion and debate.
Today’s intelligent assistants can at some point mislead you into thinking that they are human beings, but the future of intelligent assistants will go one step further.
The smart assistant system behind the screen must be pre-trained to learn as much as possible about human requests, and its responses are written and organized into highly structured data formats. Therefore, the intelligent assistant will be constrained by preset data when responding to requests.
Now, efforts are being made to develop new technologies that will enable the next generation of systems to absorb and organize unstructured data from various sources (such as raw text, video, pictures, audio, e-mail, etc.) and then write compelling recommendations on their own, or on a question and response that they have never been trained in.Hand debate.
In June, IBM demonstrated an advanced technology: a system that does not have prior training on a subject, but can engage in real-time debates with human experts. The system must use unstructured data to determine the relevance and authenticity of the information and organize it into a reusable form.Consistent discourse to support its assigned position. It must also respond to human opponent’s discourse. The system demonstrates two debates, one in which many audiences believe the system’s debates are more convincing.
The technology, which has been developed for more than five years, includes new software that not only understands natural language, but also detects whether the emotions contained in the language are positive or negative. This work is still in progress, but it has opened the door to countless new applications that may be in the next three to five years or more.In less time.
Implantable pharmaceutical cells
Implantable pharmaceutical cells – the release of drugs directly from patients is about to become feasible.
Many diabetics need to puncture their fingers several times a day, measure blood sugar levels, and determine how much insulin they need to inject. If normal insulin-producing islet cells can be implanted into a patient’s body, this cumbersome process can be replaced. However, the transplanted cells are always interfered by the autoimmune system.Epidemic inhibitors have huge side effects.
Over the past few decades, scientists have developed ways to seal cells in semipermeable protective membranes to prevent the immune system from attacking transplanted cells. These capsules allow nutrients and small molecules to penetrate, and hormones and other therapeutic molecules to seep out. But the problem is that the immune system may also protect the membrane.It’s also a foreign substance, so scar tissue will grow around the capsule. This “fibrosis” hinders the entry of nutrients into cells, thereby killing the cells themselves.
2016 In nineteen ninety-five, a research team at the Massachusetts Institute of Technology unveiled a way to make transplanted cells invisible to the immune system. After developing and screening hundreds of materials, the researchers chose a chemically modified alginate gel. When they seal the islet cells in this adhesive tape, they are implanted in small diabetic patients.In mice, the cells immediately responded to changes in blood sugar to produce insulin, which continued to control blood sugar levels for six months. Fibrosis was not observed during this period.
Today, the cells in these capsules are either derived from animal or human cadavers or cultured from human stem cells. Future implantable cells may include more types of cells, even those made by biosynthetic techniques: rewriting cell genes to give them new functions, such as controllable bars.Release specific drug molecules into the tissue according to needs.
Laboratory artificial meat
Artificial meat, no artificial killing meat, is heading for your table.
Imagine you took a bite of a juicy beef burger, which happened without killing the animals. The artificial meat cultivated in the laboratory is turning this idea into reality.
Artificial meat is made from muscle samples extracted from animals. Technicians collect stem cells from animal tissues, allow them to proliferate and differentiate into myofibrils, which then grow into muscle tissue. Mosa Meat claims that a tissue sample collected from cattle is enough to produce 80 thousand cows.Meat burger.
Some start-ups say they expect to formally introduce artificial meat products in the coming years. But before going public, artificial meat has to overcome many obstacles.
The two obstacles are cost and taste. Take the lab-made meat burger, which was shown to major media in 2013, for example. It costs more than $300,000 to make, and the meat is too dry (because of too little fat). Since then, the cost of artificial meat has been decreasing year by year. This year,Memphis Meats claims that the price of 1/4 pounds of artificial beef is about $600. According to this trend, artificial meat may become a competitor of traditional meat in a few years. If they can succeed in producing products that are affordable and pure in taste, artificial meat will make it possible.Our daily eating habits are more ethical and friendly to the environment.
Electrical stimulation medicine — nerve stimulation therapy will replace many drugs to treat chronic diseases.
Neuroelectric stimulator (NES) is a device for the treatment of diseases by electric current pulse. It has a long history in pharmacy, such as cardiac pacemaker, cochlear implant and deep brain electrode stimulation for the treatment of Parkinson’s disease. This electrical stimulator is becoming more and more functional and will significantly improve the efficacy of a large number of diseases.
With the efforts of Kevin Tracey and others at the Fanstein Institute of Medicine, vagus nerve stimulation (VNS) has become feasible on some occasions. They found that the vagus nerve releases chemicals to help regulate the immune system. This is for patients with immune diseases.It’s good news because the existing drugs often do not work or cause serious side effects. Since VNS only stimulates specific nervous systems, it may be a more acceptable treatment than drugs that pass through the body and harm tissues outside the target.
Vagus nerve is not the only target of emerging electrical stimulation therapy. In late 2017, the FDA approved a non-implantable device that sends signals to cranial and occipital nerves through the back of the ear skin to relieve withdrawal responses to opioid withdrawal.
VNS The biggest obstacle to treatment is the cost of the surgery, but with advances in non-implantable technology, the price problem should be significantly alleviated. Researchers also need to learn more about how VNS works in each disease and how to determine the optimal current frequency for each patient. In any case, accompanyWith more research on mechanisms and efficacy, VNS and other electrical stimulation medicine may be able to better control many chronic diseases and reduce the demand for medicines for thousands of patients.
Gene driven technology
Gene driven technology tools for changing or even destroying entire species
A rapidly developing genetic engineering technique can permanently alter the properties of a population or even of an entire species. This technique increases the number of offspring containing certain genetic factors by gene-driven, thus speeding up the spread of the gene across species. Gene drive can happen naturally or through genetic engineering.Cheng is good for humans in many ways: stopping insects from spreading malaria and other infectious diseases, modifying pest genes to increase food production, empowering corals to withstand environmental stress, and preventing invasive species from destroying ecosystems.
Despite promising prospects, gene-driven technology has raised concerns: Will the man-made genes inadvertently spread to other wild species and interfere with their growth? What are the risks of eliminating existing species from ecosystems? Will illegal organizations drive gene driving as a weapon to destroy agricultural production??
To avoid this extreme situation, a team of researchers has invented a drive switch that must pass on a particular substance in order to turn on the gene drive. At the same time, many groups of scientists are working on provisions to guide the progress of gene-driven experiments at all stages. In 2016,The National Academy of Sciences, Academies of Engineering, and Colleges of Medicine reviewed gene-driven research and made recommendations for related research. In 2018, a large international team developed a process for research operations ranging from laboratory research to field trials. The group has proposed the use of gene driving in malaria control in Africa.This will benefit public health from an unprecedented level.
Plasmon material sensor technology, a new revolution is arising in the field of photo controlled nanomaterials.
2007 In 2005, Harry A. Atwater of the California Institute of Technology predicted in Scientific American that “plasmon photonics” would eventually lead to a range of applications, from highly sensitive biodetectors to invisible covers. Over the next ten years, all kinds ofPlasma technology has been commercialized, and some other technologies are being transformed from laboratory to market.
These techniques rely on the control of the interaction between electromagnetic fields and free electrons in metals (usually gold or silver), which determine the conductivity and optical properties of materials. When the metal is irradiated by light, the free electrons on the surface of the metal resonate and form the surface plasmon. If the metal material is large,The materials emit light when the free electrons reflect the light illuminated by them, but if the metal is just a few nanometers in diameter, its free electrons are confined to a very small space, thus limiting the vibration frequency of the electrons. The specific frequency of the electrons will depend on the size of the metal nanoparticles.
In the field of plasmon materials, one of the most thorough applications is the sensors used to detect chemical and biological reagents; other applications include sensors inside batteries that monitor cell activity, devices that distinguish viruses from bacterial infections. In addition, in the field of medicine, researchers are testing photosensitive Na in clinical trials.The application of rice granules in cancer treatment. According to market research firm Future Market Insights, the market value of plasmon sensors in North America will rise from nearly $250 million in 2017 to nearly 2027.470 million dollars.
Quantum computer algorithm
Algorithm for quantum computers — developers are constantly modifying programs to adapt to quantum computers.
The unique superposition and entanglement properties of quantum computers make them more efficient than any traditional computer in solving specific problems. However, the conditions for achieving quantum computing are notoriously picky. Quantum decoherence, for example, destroys its functions. Researchers have confirmed that by quantum error correction, it can be made thousands of times.Quantum computers are tightly controlled and maintained in quantum states. But so far, the quantum computers in the laboratory have been just noisy, medium-sized quantum (NISQ) computers with dozens of qubits and no error correction.
However, with the rise of research on algorithms specifically written for NISQ computers, the field of quantum computing may usher in a breakthrough.
In the view of researchers, NISQ algorithm has broad prospects in the field of simulation and machine learning. Many researchers have developed algorithms to simulate molecules and materials on NISQ devices (and future error-correcting quantum computers). These algorithms can improve the new field from energy to health science.Material design efficiency.
Developers are also evaluating whether quantum computers will be better at machine learning. Tests of algorithms for NISQ devices show that quantum computers can indeed speed up machine learning, such as categorizing information, classifying similar items or features, and from existing ones.Statistical samples generate new samples.
Over the next few years, researchers are likely to develop larger, more manipulative NISQ devices, followed by thousands of quantum bits of fully corrected instruments. We are optimistic that NISQ’s algorithm will be more efficient than traditional computers with the most advanced technology, although we may beWait until the fully corrected machine is available.
（This article is authorized to be reproduced from global science ScientificAmerican (ID:huanqiukexue).