A.I. uses a great deal of energy, and many companies still can’t evaluate the environmental impact it causes. Therefore, a thorough discussion and education are needed on this topic.
Before starting, let’s know what A.I. marketing is?
It refers to a type that uses artificial intelligence concepts and models such as machine learning and Bayesian Networks to achieve marketing goals. It differs from humans, as reasoning is done through computers and algorithms.
So, do you know A.I. impact the environmental factors?
A.I. contributes to the company’s carbon footprints. But if these are managed well, they can even reduce the impact. Seeing the depreciating environmental health, many big firms have made ‘sustainable finance’ the core goal of their business. Therefore, it’s essential to know its ecological impact and how A.I. can control it.
A.I. reduces carbon footprints. How?
There are committed cloud providers who reduce their carbon footprints, along with the company they are allied with. Therefore, companies can shift their A.I.’s processing and train to a data centre cloud provider rather than focusing on the internal training process.
Here are some examples of such cloud providers:
Google Deep Mind:
It has a developed A.I., which teaches itself to use energy in a minimized way to cool down Google’s data centres. In this way, Google reduces the energy requirements by 35%. The public cloud offering platform is Google cloud.
It is Microsoft’s public cloud platform which is committed to being Carbon Negative by 2030.
Amazon Web Services:
Amazon Web Service provides on-demand cloud computing platforms and APIs to individual companies. Its parent company has a long-term goal of using 100%renewable services.
Apart from the cloud providers, there are many industries in which A.I. positively contributes to environmental sustainability.
A.I. monitors the weather forecast and crop yields. They can even help in reducing both fertilizers and water while improving crop yields.
Under this A.I., create an intelligent grid system to manage the demand and the supply of renewable energy. Besides accurately predicting weather patterns, it can optimize efficiency, cut costs, and reduce unnecessary carbon pollution.
A.I. helps in regarding traffic congestions, improve supply chain logistics and promote autonomous driving capability. It will help in last minute delivery problems and reduces the need for vehicles.
Water Resource Management:
Localized A.I. can predict the weather forecast and optimize the usage of water.
Robotics can reduce waste and energy use in production facilities by designing a more efficient system.