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This year marks 20 years since we began compiling our annual flagship technology compilations. Some of them – such as mRNA vaccines – are already changing our lives, while others will have to wait a few more years. Below you will find a brief description of each technology. We hope you appreciate this opportunity to look into the future.
Messenger RNA Vaccines
We are incredibly lucky. The two most effective coronavirus vaccines are based on messenger RNA, a technology that has been in development for 20 years. When the Covid-19 pandemic hit last January, scientists from several biotech companies rushed to work on mRNA-based vaccines. At the end of December 2020, with 1.5 million deaths from coronavirus worldwide, vaccines were approved in the United States and the pandemic began to decline.
The new coronavirus vaccines are based on groundbreaking technology and could change medicine, paving the way for a new generation of drugs for a variety of infectious diseases, including malaria. And if the coronavirus continues to mutate, mRNA vaccines can be easily and easily modified. In addition, messenger RNA holds great promise as a basis for cheap drugs for sickle cell disease and HIV. Finally, a cure for cancer is being developed, also based on mRNA.
Large computer models in natural language that learn to write and speak on their own are an important step towards an artificial intelligence that can better understand and interact with the world. GPT-3 is by far the largest and most literate. With thousands of books and a large chunk of the Internet, GPT-3 can mimic the human way of composing texts with incredible, sometimes even bizarre, realism. This makes it the most impressive machine learning language model today.
But GPT-3 does not understand what it is writing, so sometimes confusion or even nonsense comes out. Training requires a tremendous amount of computing power, data, and money. This multiplies the carbon footprint and inhibits the development of similar models, requiring exceptional resources from laboratories. And since she learned from texts from the Internet, and it is crammed with misinformation and prejudice, the model produces equally biased opuses.
TikTok recommendation algorithm
Since its launch in 2016, TikTok has become one of the fastest growing social media platforms in the world. The application has collected billions of downloads and has united hundreds of millions of users. Why? Because TikTok’s custom feed algorithms have revolutionized the world and how people achieve fame online.
If other platforms are more likely to push content aimed at mass audiences, then TikTok’s algorithms are just as likely to wrest a new creator out of obscurity and ignite a new star. And they are particularly adept at delivering relevant content to niche communities with specific interests or distinctive tastes and preferences.
The ability for new contributors to quickly collect a lot of views and the ease with which users discover new content have provided the app with staggering growth. Other social media companies are struggling to replicate these features in their own apps.
Lithium metal batteries
Selling electric vehicles is not an easy task: not only are they more expensive, but they are only enough for a few hundred kilometers without recharging – moreover, it takes much longer than refueling. All of these disadvantages stem from lithium-ion batteries and their limitations. One well-funded Silicon Valley start-up says it has developed a battery that will make electric vehicles much more attractive to the mainstream.
This type of battery is called lithium metal and is being developed by QuantumScape. Preliminary tests have shown that a battery can increase the mileage of an electric vehicle by 80% while still being charged quickly. The startup has already entered into a deal with Volkswagen, which intends to sell electric vehicles with a new type of battery by 2025.
So far, this is only a prototype, much less than what is needed for a real car. But if QuantumScape and others in the same direction succeed, electric vehicles can finally reach millions of drivers.
It turns out that tech companies don’t store our personal data well. We have already lost count of how many times they have been leaked, hacked and resold. Maybe the problem is not with us, but with the privacy model we are used to holding onto – where everyone is personally responsible for maintaining privacy?
Data trust offers an alternative approach that some governments have already begun to look at. A data trust is a legal entity that collects and manages personal data of people on their behalf. While the structure and function of these trusts is still being determined and many questions remain, data trust is notable for offering a potential solution to longstanding privacy and security concerns.
Hydrogen has always been a curious replacement for fossil fuels. Burns clean, does not emit carbon dioxide, and is also energy intensive – so it’s a good way to store energy from non-permanent renewable sources. In addition, liquid synthetic fuels can be produced, which will become an irreplaceable replacement for gasoline or diesel fuel. So far, most of the hydrogen is produced from natural gas – but the process is dirty and energy intensive.
However, solar and wind energy is rapidly falling in price, which means that green hydrogen is now also available enough to become profitable. Just plug the water into the electricity and you’re done – here’s the hydrogen for you. Europe is leading the way and is already starting to build the necessary infrastructure. These projects are just the first step towards a future global network of electrolysis plants that will produce pure hydrogen from solar and wind energy.
Digital contact tracing
When the coronavirus first started spreading around the world, at first it seemed that digital contact tracing would save us. Smartphone apps create GPS or Bluetooth based meeting logs. If someone then receives a positive test for coronavirus, he will be able to enter this information into the application, and it will warn others who could be infected from it.
Alas, digital contact tracing has not really been able to contain the spread of the virus. Apple and Google quickly rolled out notification functionality to many smartphones, but health officials have failed to convince citizens to use them. The lessons from this pandemic will not only help us prepare for the next one, but also affect other areas of health.
We all use GPS every day – it has changed our lives and our work. But if modern GPS has an accuracy of 5 to 10 meters, then new technologies for ultra-precise positioning – within a few centimeters or even millimeters. This opens up new possibilities – from landslide warnings to delivery robots and self-driving cars that can safely navigate the streets.
China’s BeiDou Global Navigation System (Ursa Major) was completed in June 2020 and opens up new opportunities in this direction. It provides positioning accuracy of 1.5 to two meters to any user. And thanks to the ground-based differential correction system, it can improve accuracy to the millimeter. Meanwhile, the GPS system, which has been around since the early 1990s, is also being updated: four new satellites for GPS III will be launched in November, and more will be in orbit by 2023.
Due to the coronavirus pandemic, the world has switched to remote mode. It is especially important not to go wrong with this transition in healthcare and education. In some countries, efforts have been made to maximize the benefits of these two areas.
To date, distance learning company Snapask has 3.5 million users in nine Asian countries, and Indian learning app Byju’s has grown to 70 million. Unfortunately, students in many other countries will not switch to remote classes.
Meanwhile, thanks to advances in telemedicine in Uganda and several other African countries, millions of patients received the necessary medical care during the pandemic. In a chronically underserved part of the world, telemedicine services are saving lives.
Despite tremendous advances in artificial intelligence in recent years, AI and robots in general are still dumb – especially when it comes to solving new problems and navigating in unfamiliar environments. They lack the human abilities that even young children have – they do not know how the world works, and they do not know how to apply this general knowledge in a new situation.
One promising approach to improving AI is to expand its sensitivity. Today, AI with computer vision or sound recognition can sense things, but cannot “talk” about what it sees and hears using natural language algorithms. But what if you combine these abilities in a single AI system? Will they then acquire human-like intelligence? By learning to see, feel, hear, and communicate, will a robot become a more skillful helper – thanks to more flexible intelligence?