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How Artificial Intelligence Can Power Climate Change Strategy

Forbes -- Slowing down climate change is an urgent matter. If we fail, our world will face a more extensive crisis than we experienced because of the global COVID-19 pandemic.

When artificial intelligence (AI) technology helps solve a problem, problem-solving can be done quicker, and the solution is often one that would have taken longer for humans to discover. Could artificial intelligence power climate change strategy? Yes, and it’s already doing so.

AI Can Accelerate Our Response to Climate Change

There’s no time to waste: atmospheric CO2 levels are the highest ever (even with significant drops from the stay-at-home orders for COVID-19), average sea levels are rising (3 inches in the last 25 years alone), and 2019 was the hottest year on record for the world's oceans. Artificial intelligence isn't a silver bullet, but it can certainly help us reduce greenhouse gas (GHG) emissions in various ways.

According to Capgemini Research Institute modeling, AI is estimated to assist organizations in industries from consumer products to retail to automotive and more fulfill up to 45% of the Paris Agreement targets by 2030. AI will likely reduce GHG emissions by 16%. Here are a few of the most promising ways that artificial intelligence already is or can impact climate change strategy:

 

Improve Energy Efficiency

According to the Capgemini Research Institute, artificial intelligence should improve power efficiency by 15% in the next three to five years. Machine learning supports efficiencies in power generation and distribution, from autonomous maintenance and leak monitoring to route optimization and fleet management. Google’s Deepmind AI can predict wind patterns up to 36 hours in advance to optimize wind farms.

Electricity systems create vast amounts of data. So far, energy companies aren’t leveraging this data for learning to the extent that’s possible. Machine learning can comb through this data to understand and forecast energy generation and demand to help suppliers better use resources and fill in gaps with renewable resources while reducing waste. The uses of AI for energy efficiency might start at the industry level, but use cases go down to the household and individual levels.

Optimize Clean Energy Development

In the Amazon basin, developers of hydropower dams have typically developed one at a time with no long-term strategy. A group led by Cornell University that included computer scientists, researchers, and ecologists developed an AI computational model to find sites for dams (hundreds of hydropower dams are currently proposed for the basin) that can produce the lowest amounts of GHG emissions. The AI model revealed a more complicated and surprising set of considerations to lower GHG emissions than had ever been considered before.

Avoid Waste

Companies, governments, and leaders frequently deploy AI solutions to avoid waste. Whether AI is used to reduce energy waste from buildings (accounts for one-quarter of COemissions) or understand supply and demand, a huge way AI can power climate change strategy is to reduce waste in all forms (time, money, material, etc.)

Make Transportation More Efficient

Another quarter of global COemissions is from the transportation sector. AI is already the technology that powers autonomous vehicles, including shared cars and smart transportation systems in some cities. Further adoption will help curtail emissions in the future. Artificial intelligence optimizes routes for fleets, traffic signals, and more. All of these incremental changes add up to make a significant impact on climate change.

Tools to Help Understand Carbon Footprint

They say, “knowledge is power,” and when it comes to climate change mitigation, AI can help build tools to help individuals and companies understand their carbon footprint and what actions they can take to reduce it.

Monitor Environment

This year, there were severe weather events that caused massive destruction and loss. AI is used and will continue to be used to enhance weather prediction and response. Changes to complex systems such as cloud cover and ice sheet dynamics caused some recent weather changes. Grasses, trees, and other plant life store carbon, but deforestation and unsustainable agriculture release carbon into the air. As a result, this is a major contributor to climate change. Satellite imagery and AI help conservationists monitor where this is happening to create change.

Create New Low-Carbon Materials

The production of steel and cement accounts for 9% of global GHG emissions. If AI could develop new materials with similar properties but with a smaller carbon footprint, it could help slow climate change. Artificial intelligence supports scientists by making the process of mixing various chemical compounds into combinations never tested before much faster and easier.

Doesn’t AI Have a Carbon Footprint? 

The appeal of AI to mitigate climate change was questioned after a report released by the University of Massachusetts at Amherst estimated the power required to train a neural network was approximately five times the average U.S. car's lifetime emissions (including its manufacturing). Yes, artificial intelligence does have a carbon footprint, and it's quite severe when the model is developed.

Researchers are making progress in reducing the power required to train AI models. The adoption of AI server farms powered by renewable resources, development of AI once-for-all neural networks, and more are ways researchers reduce AI's carbon footprint. In the meantime, when considering AI's carbon footprint, the tremendous value of AI, and the real-world outcomes it can have on reducing carbon emissions need to be considered as well. Some of those downstream offsets can counterbalance the emissions created when the model is trained.

The U.S. Postal Service today filed a request with the Postal Regulatory Commission (PRC) for a 1.966% rate adjustment based on the Consumer Price Index. This increase applies only to market-dominant products, such as Standard Mail, that is the primary postage class of direct mailers.

USPS has asked that the increase take effect on April 26 and estimates that it will generate an additional $900 million in contribution—or net income—on an annualized basis. Should the PRC agree to meet the Postal Service's timeline, contribution for USPS's fiscal year 2015, which concludes at the end of September, will be around $400 million. The CPI case includes a separate pricing structure for Standard Mail run through the Flats Sequencing System. Under the proposal, FSS pricing will no longer exist for carrier route, high density, or high density plus categories.

In their place a five-digit carrier route pallet price will be created. Rates for Standard Flats will increase by 2.465% Prices of Forever stamps will remain at 49 cents in the new rate base. International letters will increase by a nickel to $1.20 and postcards will go up a penny to 35 cents.

The Shanghai Composite dropped nearly 8% as investors reacted to the ruling, which will prevent the brokers from opening new margin trading accounts for three months.

Shares of two affected brokerages -- Citic Securities and Haitong Securities -- quickly lost 10%, the daily limit for stocks trading in Shanghai. Guotai Junan Securities, the third broker, was trading down more than 10% in Hong Kong. The fallout was limited to stocks trading in China. Japan's Nikkei gained nearly 1%, and most regional indices finished higher.

Deng Ge, a spokesman for the China Securities Regulatory Commission, said the brokers were caught rolling over margin trading accounts for a large number of clients "and had been warned," according to Reuters.

After absolutely dominating the market last year, the technology sector has taken a mighty hit this week, down 3.3%, the same hit the S&P 500 has taken. There is no question that some of the tech leaders may have been the victim of start-of-the-year profit taking to roll 2014 gains in to 2015. In some cases, tax-loss selling may be the culprit to print against those gains. The real question for many investors is simple: Is the tech party starting to wind down?

A new research report from the Information Technology and Hardware analysts at UBS tracks the stocks that are the most overbought and oversold on a relative strength basis. Needless to say, this week’s volatility has skewed numbers for the stocks that were oversold even more. Here are five high-profile technology stocks that showed up on the UBS oversold screen.

IBM’s software unit missed earnings badly last year, and Citrix is poised to grab business in this arena. By reason, some investors could consider that Big Blue may be keeping an eye on the company, looking to strengthen existing business while eliminating a very formidable contender in the space.

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