Cornell Research Identifies 3 Strategies for AI Infrastructure to Reduce Emissions by 73%
A Cornell study reveals that while AI has substantial environmental consequences, employing smarter infrastructure strategies could slash related emissions by up to 73%. The report underscores the importance of sustainable AI development to mitigate its ecological footprint.
Collaborative Data Sharing in Supply Chains Drives Carbon Reduction
Scope 3 emissions from indirect supply chain activities account for the largest corporate carbon footprint. Technology-driven solutions like AI data management, network platforms for visibility, and forecasting tools help companies accurately track and reduce these emissions. By collaborating and sharing data, supply chain partners can optimize operations, limit waste, and achieve sustainability goals, gaining a competitive edge in the low-carbon economy.
Environmental Concerns Rise as AI Data Centers Expand Rapidly in Latin America
As AI data centers rapidly spread across Latin America, local communities in dry areas seek transparency amid large foreign investments. The scale and secrecy surrounding these projects raise environmental concerns and resistance efforts.