With Moore's Law slowing down, building distributed and heterogeneous systems becomes a new trend to support large-scale applications, such as large model training and big data analytics. In-Network Computing (INC) is an effective approach to building such distributed systems. INC leverages programmable network devices to process traversing data packets, and provides line-rate and low-latency data processing capabilities, which could compress traffic volume and accelerate the overall transmission and job efficiency. In this talk, we will share the progress and development of INC technologies, including INC protocol design for machine learning and data analytics, and RDMA-compatible INC solutions. These works are published in NSDI21 and ASPLOS23.