Technology

12 ways AI can solve global warming

With the rapid development of technologyArtificial Intelligence (AI) in recent years, many have begun to wonder how these very technologies can help in addressing one of the most serious threats that has already hung over humanity - global climate change? A new article prepared by some of the leading experts in the field of developing artificial intelligence and published in the online repository arXiv.org is trying to answer this question by offering several examples of how machine learning will be able to prevent the decline of our civilization.

The proposed methods range from usingAI and satellite technologies for more efficient monitoring of deforestation, prior to the development of new materials that can replace steel and cement (their production accounts for up to 9 percent of greenhouse gas emissions). Despite this diversity, in their article, experts again and again return to the wider possibilities of using such technologies. Especially against this background stand out the possibility of using computer vision technology for environmental monitoring; conducting large data analyzes to determine the inefficiency of industries with high emissions of harmful substances into the atmosphere; and the use of AI to develop new, more efficient models of systems, such as our climate models, thanks to which we can better predict and prepare for future changes.

The authors of the article, includingDeepMind, a British artificial intelligence researcher, Demis Hassabi, founder and executive director of the DeepMind company, Joshua Bengio, winner of the Turing Award and one of the “deep learning fathers,” and Andrew Eun, co-founder of Google Brain, a research project on artificial intelligence from Google. that AI can provide “invaluable help” in minimizing the worst effects of global climate change, but they add that this technology is not a “silver bullet” - the only media Twomey from all problems. In their opinion, political forces should take an active part in this issue.

“Technology alone is not enough. Technologies that have been able to mitigate the effects of climate change have been available for many years, but, to a large extent and on the right scale, they unfortunately have not been adapted by society. And although we hope that machine intelligence can be useful in reducing the costs associated with the use of methods aimed at reducing the effects of climate change, humanity should also take an active part in this, ”the authors of the new study write.

In total, the article is considered immediatelyseveral areas in which machine learning technologies could find their application, categorized by the time frame of their potential use potential, explained by whether this technology is sufficiently developed. Below you can find this list.

Artificial intelligence will improve the efficiency of power supply systems.

If in the future mankind plans to relyfor more renewable energy sources, utilities will need ways to more effectively predict and calculate the amounts of energy we really need to use. Moreover, these calculations will have to occur in real time and during the entire period of operation of these enterprises.

Already developed algorithms capable ofpredict energy demand, however, the efficiency of these algorithms can be further improved by including in the calculations factors such as the climate features of particular regions, as well as the specifics of business activities. Attempts to make the specifics of the work of these algorithms more understandable will also allow utility operators to more accurately interpret the results of their analysis and use them when planning, choosing the most optimal time to run these sources of renewable energy.

Artificial intelligence will help in the discovery of new materials.

Scientists need to develop new materials formore efficient production, storage and use of energy, however, as a rule, the process of discovery and development of new materials is very slow and not always successful. Machine learning technologies will speed up the process of finding, developing and improving new formulas with desired properties.

Perhaps this will lead to the development, for example,A new type of fuel, let's call it “solar”, which will be able to retain the energy of sunlight; will create a new and very effective carbon dioxide absorbent or building materials, the production of which will produce less carbon. Such materials will one day be able to replace steel and concrete, the production of which releases almost 10 percent of the total global emissions of greenhouse gases to the atmosphere.

Artificial intelligence will help reorganize the transport system effectively.

Shipping worldwide is verycomplex and very often inefficient logistic process, in which there is an interaction of goods of different volume, weight and size, as well as using different types of transport. At the same time, transport accounts for a quarter of all CO2 emissions into the atmosphere. Machine learning technologies used in this area will allow for more efficient merging of goods requiring delivery to the same destination, which will reduce the number of shipments required. In addition, such a system will be more resistant to unforeseen disruptions in transportation systems and will be able to manage huge fleets of unmanned trucks. However, the authors note that at the moment the latest technology is not yet ready.

Artificial will lead to quick adaptation of electric vehicles.

Electric cars are a key elementdecarbonization of motor vehicles, face a number of problems that do not allow them to become truly widespread. Machine learning can help in this matter, say the report’s authors. For example, with the help of algorithms, it will be possible to improve the management of battery energy consumption in order to increase the mileage of each charge and reduce the level of concern for potential buyers of such vehicles about limiting the distance of the trip. In addition, these technologies will optimize charging time.

Artificial Intelligence optimizes building infrastructure

Smart control systems operating on the basemachine learning, will be able to significantly reduce the level of energy consumption by buildings, taking into account weather conditions, current occupancy of the building and other environmental factors, after which the heating, cooling, ventilation, and indoor lighting will be adjusted accordingly Smart buildings will be able to transmit information about the current state of the environment directly to the grid, so that energy consumption can be reduced if there is a shortage of low-carbon power supply.

AI will be able to more accurately calculate the amount of energy used

In many regions of the world are practically absentdata on the level of local energy consumption and greenhouse gas emissions into the atmosphere, which can be a big problem for the development and implementation of effective compensation measures. Machine vision methods will allow satellite technology to be used to estimate the spot (area) of buildings, so that machine learning algorithms can calculate energy consumption and emissions based on these data. Similar methods can be used to identify buildings that require retrofitting to increase their efficiency.

Artificial intelligence optimizes supply channels

Using similar capabilities, technologymachine learning will be able to optimize channels and supply chains, minimizing carbon emissions when transporting various goods. The ability to more effectively predict the law of supply and demand will reduce industrial and transport waste.

Artificial intelligence will scale precision farming

Most modern agricultural farmsuse the principle of growing monocultures. In other words, only one crop is grown over a large area. This approach makes it easier for farmers to tillage fields with agricultural equipment and other basic autonomous tools, but at the same time it depletes the soil, depriving it of nutrients and thus making it less productive. As a result, various fertilizers are often used to increase the yield, in particular on the basis of nitrogen, which can turn into nitrogen oxides - greenhouse gases are 300 times more dangerous than carbon dioxide. Machine learning robots can help agriculture assess the current state of the soil and suggest which crops to plant in order to restore soil health, reducing the need for fertilizer use.

AI will help to more effectively monitor deforestation

Deforestation contributes to emissions of about 10percent of total greenhouse gases. Tracking and preventing this often illegal activity is usually a very laborious and routine process that requires personal observation on the spot. In turn, satellite images, coupled with machine vision technologies, will allow automatic analysis of forest cover loss on a large scale, and special sensors installed at sites, combined with algorithms that can, for example, detect the sound of chainsaws, can help law enforcement agencies more effectively deal with illegal activity.

AI will help change our consumer attitude.

According to the authors of the report, in the worldthere is a common misconception that ordinary people cannot have a major impact on climate change. ” Therefore, in this matter it is necessary to clarify exactly how people can help. Machine learning technologies will make it possible to calculate the carbon footprint of a person (the totality of all greenhouse gas emissions that he creates in the course of his daily activities) and make small changes that will reduce it. For example, the system may offer more frequent use of public rather than personal transport; buy meat less often in the store; or reduce power consumption at home. Each of us individually creates a small carbon footprint, but if we take all at once, the numbers will be much more significant. Changes in our attitude towards consumption and the addition of all the individual actions aimed at this can have a great cumulative effect.

AI will improve the efficiency of meteorology and climatology

Many of the most significant effectsClimate change over the coming decades will be associated with very complex natural systems, such as changes in the dynamics of cloud or ice cover. These are precisely the questions in the solution of which great hopes are placed on AI. Accurate modeling of these processes will help scientists more effectively predict extreme weather conditions (for example, hurricanes and droughts), which in turn will help states develop methods to protect against the worst effects of these phenomena.

Artificial Intelligence will help with geo-engineering

At this stage, this use of AIamong all the above, it is the most speculative, but it also places great hopes on it, at least on the part of some scientists. If we can develop ways to make the cloud cover of our planet more reflective or even create artificial clouds based on special aerosols, then we can reflect more sunlight from the Earth. But this issue requires a serious investigation. AI can help with this, but the authors of the report note that this method of using artificial intelligence is a matter of a very distant prospect, which will require the cooperation of all the governments of the world. Experts of Canadian University of Waterloo, for example, agree with this position, who believe that this unreasonable approach to the issue of geoengineering can start a third world war.

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