The world is watching innovations and the latest technological innovations because they determine our future. In this article, we will talk about the innovations of recent years, which are talked about by the world media. And you can find out about the latest in the world of casinos and sports betting on the Hellspin portal.
Lithium metal batteries
Lithium-metal batteries have every chance to change the balance of power in the car market. Their energy density is 1 kWh per liter of volume, almost double that of lithium-ion batteries. Thanks to this, electric cars charge much faster, and most importantly, the charge lasts 80% longer than lithium-ion batteries, according to MIT Technology Review. Such indicators remain after 800 cycles.
The American startup QuantumScape (among its investors is Bill Gates), which develops lithium-metal batteries, conducted the first tests in December 2020. After successful trials, he has already closed a deal with Volkswagen, which will start producing electric vehicles with these batteries in 2025.
Skeptics argue that the test results are too early to consider successful: they were carried out on single-layer cells, while in actual batteries, they should be multi-layered. In mass production, this can lead to unforeseen risks.
Messenger RNA vaccines
The RNA vaccine has been one of the most advanced developments in medicine over the past 20 years. Now there are two vaccines created using this technology: Pfizer and Moderna. Both are anti-coronavirus.
Conventional – vector – vaccines contain a weakened or inactive causative agent of the virus. mRNA-based vaccines induce the body to produce a fragment of the protein contained in the COVID-19 pathogen, which immediately attacks the immune system. As a result, there is a strong immunity to the virus; the body becomes resistant to infection.
Matrix (informational) RNAs are good because they are easy to modify for any new virus strain. They can also fight infections (such as malaria), cancer, sickle cell anemia, HIV, and other serious illnesses.
The most advanced neural network based on NLP (text recognition algorithms) is GPT-3. This is a transformer neural network that can generate coherent answers in dialogue with a person. Its data and parameters are 100 times greater than the previous generation – GPT-2.
However, even the most advanced transformers, trained on huge amounts of data, do not understand the meaning of the words and phrases they generate. Their training requires vast amounts of data and computing resources, which, in turn, leave a large carbon footprint. Another problem is the imperfection of datasets for training neural networks: texts on the Internet often contain distortions, manipulations, and outright fakes.
One of the most promising areas in developing AI and neural networks is expanding the range of perception. Now algorithms can recognize images, faces, fingerprints, sounds, and voice, and they can also speak and generate images and videos that mimic our perception of different senses. MIT scientists note that AI lacks emotional intelligence and feelings to get closer to a person. Unlike AI, a person can not only process information and issue ready-made solutions but also take into account the context, many external and internal factors, and, most importantly, act in conditions of uncertainty and a changing environment. For example, DeepMind’s AlphaGo algorithm can beat the world champion in go and chess but cannot extend its strategy beyond the board.
So far, even the most advanced algorithms, including GPT-3, are only on the way to this. Now developers are faced with the challenge of creating multimodal systems that combine text recognition and sensory perception for information processing and decision-making.