In recent years, data in large volumes has become readily accessible through new sensor technologies, satellite data and drones, making the data collection quick and inexpensive. This opens new opportunities to utilize technologies like artificial Intelligence (AI), machine learning (ML) and blockchain in combination with drones, high-speed internet and more to identify and accelerate climate solutions. Such technologies can help measure, understand, evaluate challenges and make forecasts, enabling decision makers to make informed policy choices, while also enabling the automation of responses, optimizing the use of resources and providing the smart and coupled infrastructure for responses at scale. Digital technologies can also drive behavioural change, enabling individuals to understand their carbon footprint and act to reduce it.
According to a study conducted by a group of researchers, AI is estimated to have the potential to enable the fulfilment of 93% of the environmental Sustainable Development Goals targets.
Tackling Climate Change With Machine Learning:
A recent study by researchers at leading AI institutions such as Stanford University, Google AI and Microsoft Research has identified 13 industries where ML could have a significant impact:
- Electricity systems
- Transportation
- Buildings and cities
- Industry
- Farms and forests
- CO2 removal
- Climate prediction
- Societal impacts
- Solar geo-engineering
- Individual action
- Collective decisions
- Education
- Finance
An Ecosystem in Support of Climate Tech Solutions
New innovative start-ups are demonstrating how new emerging tech can play an important role in mitigating and adapting to climate change, such as increased energy efficiency in consumer goods and industry, climate predictions or material optimization. Silicon Valley’s thriving ecosystem of academic institutions, venture capital, entrepreneurs and innovative corporations has a unique capacity to accelerate this innovation.Tech Companies Supporting Tech Solutions for Climate Change
Google hosts the Google AI Impact Challenge – an open call for projects on how to use AI to solve social and climate related challenges. The program has provided twenty organizations with a total of 25 million USD in grant funding from Google.org, coaching from Google’s AI experts, credit, consulting from Google Cloud and inclusion in a six-month Google Developers Launchpad Accelerator.
Microsoft launched the Microsoft AI for Earth program, which awards grants and support to researchers and innovators dedicated to solving environmental challenges using cutting-edge technology. The program will award 50 million USD over its five-year span, and more than 200 research grants have already been awarded. The call is ongoing and also open to Danish academic institutions, organizations and companies. You can read more about the program here.
AI can reduce the energy consumption of buildings
Automated drones and deep learning can predict maintenance needs
Blockchain technology can create food transparency
AI can make carbon markets more transparent
Fire-fighter drones can help prevent fires
Sensors help us navigate air quality
Data-driven climate decisions will be more effective
Mapping and protecting wildlife can prevent extinction
To better protect wildlife, seven organizations, led by Conservation International and Google, have mapped more than 4.5 million animals in the wild using photos taken from motion-activated cameras known as camera traps. The photos are all part of Wildlife Insights, an AI-enabled, Google Cloud-based platform that streamlines conservation monitoring by speeding up camera trap photo analysis.
Virtual reality can get people involved in climate change
The Downside of High Tech: Its High Energy Usage
While some high-tech solutions have the potential to reduce carbon emissions and help protect the environment, there is also a downside. The computational requirement for deep learning has proven to have a large carbon footprint. AI and machine learning work with enormous datasets, which can themselves have a significant climate impact. Some estimates suggest that the total electricity demand of information and communication technologies (ICTs) could require up to 20% of the global electricity demand by 2030, up from 1% today. Or, to put it into perspective, training one AI model could produce as much carbon dioxide as 150 round-trip flights between San Francisco and Copenhagen.Digital technologies are no panacea for all climate ills, and there is a need to consider climate tech solutions based on their lifetime impact, in order to create truly sustainable solutions. Understanding the impact of AI solutions and developing better implementation models will be an important part of the process.
Making AI and Machine Learning Models Energy Efficient
Example: Silicon Valley startup Cerebras claims to have built the largest computer chip ever to accelerate AI training. Linking processing parts in one large unit can, if successful, limit the power use normally associated with shifting data between tiny AI chips.explore more related content
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