Beginning of introduction

src/chapters/introduction.tex

@@ -1,2 +1,23 @@
 \section{Introduction}
 \label{sec:introduction}
+
+Emerging applications such as \acp{llm} revolutionize modern computing and fundamentally change how we interact with computing systems.
+An important compound of these models make use of \acp{dnn}, which are a type of machine learning model inspired by the structure of the human brain - composed of multiple layers of interconnected nodes that mimic a network of neurons, \acp{dnn} are utilized to perform various tasks such as image recognition or natural language and speech processing.
+Consequently, \acp{dnn} make it possible to tackle many new classes of problems that were previously beyond the reach of conventional algorithms.
+
+However, the ever-increasing use of these technologies poses new challenges for hardware architectures, as the energy required to train and run these models reaches unprecedented levels.
+Recently published numbers approximate that the development and training of Meta's LLaMA model over a period of about 5 months consumed around $\qty{2638}{\mega\watt\hour}$ of electrical energy and caused a total emission of $\qty{1015}{tCO_2eq}$ \cite{touvron2023}. 
+As these numbers are expected to increase in the future, it is clear that the energy footprint current deployment of artificial intelligence applications is not sustainable \cite{blott2023}.
+In a more general view, the energy demand of computing for new applications continues to grow exponentially, doubling about every two years, while the world's energy production grows only linearly, at about $\qty{2}{\percent}$ per year \cite{src2021}.
+This dramatic increase in energy consumption is due to the fact that while the energy efficiency of compute processor units has continued to improve, the ever-increasing demand for computing is outpacing this progress.
+In addition, Moore's Law is slowing down as further device scaling approaches physical limits.
+
+% TODO move in correct directory
+\input{chapters/energy_chart}
+
+The exponential grow in compute energy will eventually be constrained by market dynamics, flattening the energy curve and making it impossible to meet future computing demands.
+It is therefore required to achieve radical improvements in energy efficiency to avoid this scenario.
+
+% -> effizierntere systeme
+% diskussion bezieht sich vor allem auf prozessoren
+% -> muss vor allem memory beachten, movement cost diagram