keep-up-with-ai.hashnode.devAI and Deep Learning Accelerators: A Comprehensive Review of Non-GPU ArchitecturesIntroduction The AI hardware market is undergoing a profound transformation, moving beyond the long-standing dominance of general-purpose Graphics Processing Units (GPUs) to embrace a diverse ecosystem of specialized accelerators. This report provide...Sep 17, 2025·28 min read
keep-up-with-ai.hashnode.devAffordable AI Powerhouse: Discover AMD's Best GPUs for Deep Learning NowIn the domain of artificial intelligence and deep learning, Advanced Micro Devices (AMD) has established itself as a significant contender to NVIDIA by 2025, emphasizing an open and accessible approach. AMD's strategy centers on its Radeon Open Compu...Sep 7, 2025·4 min read
keep-up-with-ai.hashnode.devBuilding My First Budget AI WorkstationIn late 2024, I decided to build a dedicated AI and deep learning workstation. My goal was to explore GPUs more closely and deepen my understanding of how hardware supports deep learning. I wasn’t aiming for a top-tier rig but rather something afford...Aug 27, 2025·3 min read
keep-up-with-ai.hashnode.devA History of NVIDIA Datacenter GPUs, from P100 to B200The development of NVIDIA’s datacenter GPUs can be seen as a steady progression of increasingly capable hardware rather than a series of dramatic leaps. It began with the Tesla P100 from the Pascal generation. This GPU offered thousands of CUDA cores...Aug 26, 2025·2 min read
keep-up-with-ai.hashnode.devAre older GPUs still valuable for learning AI and experimentation?If you’ve ever wondered what you can still do with older NVIDIA GPUs, think of it as your own learning journey. Each generation opens a new door, and even cards released years ago can still handle meaningful experiments in language models, image gene...Aug 26, 2025·3 min read