Group 1 - The construction of data centers is booming, but there is a significant power shortage that is not receiving enough attention, which poses a major obstacle for AI development in the U.S. according to Goldman Sachs [1] - The power consumption of data centers is substantial, with NVIDIA's H100 GPU consuming 700 watts, leading to an annual consumption of 3,740 kWh per unit, which could exceed the total electricity usage of all households in Phoenix, Arizona when millions are deployed [2][3] - AI computational power is expected to grow exponentially, with predictions indicating a 10,000-fold increase over the next 20 years, leading to an estimated energy requirement of 130 trillion kWh by 2050 for AI alone [3] Group 2 - PowerLattice, a startup focused on data center power solutions, has appointed former Intel CEO Pat Gelsinger to its board and raised $25 million in funding, indicating strong market recognition of its technology [4] - PowerLattice is developing a "chiplet" technology designed to improve power efficiency by reducing energy loss in computer systems, claiming a potential power reduction of over 50% while maintaining computational capability [4][5] - Empower, another startup, has integrated multiple components into a single IC using its patented IVR technology, aiming to revolutionize power management in AI and data centers, and has recently secured $140 million in funding [6][7] Group 3 - The demand for AI power chips is rapidly increasing due to the extreme power requirements of AI workloads, necessitating high-performance power management integrated circuits (PMICs) that can handle significant power fluctuations [9][10] - Traditional power supplies are inadequate for AI applications, which require rapid response to power changes and higher power density, leading to a shift towards advanced power management solutions from companies like Infineon and Texas Instruments [9][10] - Domestic AI power chip companies such as Jingfeng Mingyuan and Jiewater are experiencing significant growth, with Jingfeng Mingyuan's high-performance computing power chip revenue increasing by 419.81% year-on-year [11][12] Group 4 - The market for data center power supply units (PSUs) is projected to reach $14.1 billion by 2030, with high-power PSUs expected to dominate the market due to the increasing power demands of AI servers [15] - The adoption of third-generation semiconductor materials like GaN and SiC is becoming essential for meeting the high power density requirements of AI servers, with SiC MOSFETs being preferred for their high voltage and frequency characteristics [14][15] - The 800V high-voltage direct current (HVDC) architecture is being promoted as a more efficient power distribution solution for AI, with significant improvements in system efficiency and reduced material usage [16]