DeepSeek's recent advancements challenge the prevailing belief that significant AI progress requires massive compute resources, demonstrating that innovative hardware utilization can reduce reliance on expensive GPUs. This breakthrough suggests that smaller, focused teams can rival industry giants by unlocking efficiencies that accelerate AI advancements. To sustain AI's growth, the industry must reduce the Total Cost of Ownership by enhancing access to alternative hardware, optimizing current systems, and driving software innovation. The post reflects on the author's extensive experience in computing advancements, from founding LLVM to leading AI software development for Google's TPU platform, and underscores the need for a deeper understanding of AI's foundational challenges. It highlights the importance of co-designing hardware and software and suggests that while AI progresses rapidly, significant potential remains untapped. The piece introduces a multipart series aimed at demystifying key industry issues, such as CUDA's role and the challenges faced by other hardware makers, to foster further discussions and push the industry forward.