Cursos sobre informática e innovaciones. De los expertos. Gratis. A tu ritmo.

Digital systems offer a great opportunity to significantly reduce carbon emissions and can contribute to the efficient use of energy. However, all systems also need energy. This area of tension is addressed in the course: Sustainability in the digital age - Energy-Efficient Software Development. To effectively reduce the carbon footprint of digitalization, it is necessary to apply algorithmic efficiency and sustainability by design as guiding principles in digital engineering. We will introduce strategies to develop software that prioritizes minimized energy consumption through optimal coding and green testing practices. We will look at how the CO2 emissions of operating software applications can be measured and calculated. How to measure the performance and energy consumption of Large Language Models will be covered as well. Further we share approaches how to use advances in hardware technology and operate digital systems efficiently in data centers based on eco-friendly and cost-effective capacity management strategies.

This course is part of the Sustainability in the Digital Age series, a collaborative project between colleagues from Stanford University, SAP and the Hasso Plattner Institute.

In an era where digital technologies are reshaping industries and daily life, the environmental impact of AI systems has become a growing concern. This course explores efficient AI methodologies to address these challenges. From deep learning model compression to low-bit quantization and collaborative inference, we delve into techniques that enhance computational efficiency and reduce energy consumption. In Week 2, we focus on low-bit quantization specifically for large language models (LLMs), showcasing cutting-edge open-source tools and models. Join us to learn how to build sustainable AI systems while pushing the boundaries of innovation.

This course is part of the Sustainability in the Digital Age series, a collaborative project between colleagues from Stanford University, SAP and the Hasso Plattner Institute.