As embedded on-chip systems grow more and more complex and are about to be deployed in automotive and other demanding application areas (beyond the main-stream of consumer electronics), run-time adaptation is a prime design consideration for many reasons: i) reliability is a major concern when migrating to technology nodes of 32nm and beyond, ii) efficiency i.e. computational power per Watt etc. is a challenge as computing models do not keep up with hardware-provided computing capabilities, iii) power densities increase rapidly as Dennard Scaling fails resulting in what is dubbed "Dark Silicon", iv) highly complex embedded applications are hard to predict etc. All these scenarios (and further not listed here) make proactive and sophisticated run-time adaption techniques a prime design consideration for generations of multi-core architectures to come. The intend of this paper is to present problems and solutions of top research initiatives from diverse angels with the common denominator of the dire need for run-time adaption: The first part tackles the thermal problem i.e. high power densities and the related short and long-term effects it has on the reliability and it presents scalable techniques to cope the related problems. The second section demonstrates the potential of steep slope devices on thread scheduling of multi-cores. The third approach presents embedded pipelined architectures running complex multi-media applications whereas the fourth section introduces the paradigm of invasive computing i.e. a novel computing approach promising high efficiency through a highly-adaptive hardware/software architecture. In summary, the paper presents snapshots on four highlyadaptive solutions and platforms from different angles for challenges of complex future multi-core systems.