Breakthroughs in artificial intelligence (AI) now make it possible to engage in greener bitcoin mining. Because mining for bitcoin requires large amounts of energy consumption, it’s important to optimise the procedure so that the practice is more sustainable.
Technology is essential to modern living. One of the solutions that large tech companies have come up with is to offset any carbon they produce by planting trees. PEGA Pool does this as well.
Optimising the machines performing the energy-intensive work is another way to positively impact the environment. In this respect, AI offers several excellent opportunities for “Green Bitcoin Mining”.
What are AI and Machine Learning?
AI refers to the field of computing that attempts to get computers to perform tasks typically associated with humans. Machine Learning (ML) is the ability of computers to improve based on data they receive, either as raw data or as feedback from humans interacting with the computer.
AI and ML can operate on huge amounts of data and make predictions and deductions based on analyses of this data. These predictions can be used to:
- Predict energy usage and take action to reduce it
- Optimise the energy efficiency in real-time
- Increase efficiency
- Help humans make smarter decisions based on analysed data
- Reduce costs
Predicting energy usage reduces waste and increases sustainability. AI can analyse historical data and real-time weather patterns to accurately forecast energy generation from solar and wind sources.
With this information, engineers can optimise their hardware to ensure that it operates only on renewable energy sources, and also to maximise performance.
Real Time Optimisation
AI can take action based on the real-time data it receives and analyses, thereby reducing energy consumption. It can continuously monitor energy production and adjust its usage in real-time to ensure the hardware only operates on sustainable sources.
Increased Efficiency and Better Decision Making
AI-enabled tools constantly receive data from sensors and other monitoring devices. These tools can then make decisions to improve overall efficiency and so reduce overall costs. The tools can also determine where energy is being wasted and take action.
Better data leads also leads to better decisions, and AI can present data in a way that leaders can make better-informed decisions.
Finally, improved energy usage results in reduced costs. By gathering data on the most energy-heavy processes, AI can furnish actionable data about which processes need to be improved. Predictive AI also assists in preventing breakdowns which can come with their own set of crippling costs over time.