The SBND Collaboration completed the construction and installation of the cryostats, which employees the membrane technology recently transferred from the industry to the High Energy Physics community. SBND cryostat installation was completed in 2023. The installation of the SBND detector in the cryostat, including the Liquid Argon Time Projection Chamber, the Photon Detection System and the Cosmic Ray Tagger, was completed in 2024. Liquid Argon filling was completed in March 2024 and the Time Projection Chamber was brought to nominal voltage and took neutrino beam data in July 2024, until Fermilab beam shutdown in August 2024. SBND data taking was resumed in the fall 2024 along with ICARUS data taking (Run 4). SBND and ICARUS are collecting data (Run 4) and progressing in data analysis, including neutrino oscillation, neutrino cross sections and searcher for physics Beyond the Standard Model. The design of DUNE is progressing and the technological specifications of the DUNE Far Detector has been completed, with the Horizontal Drift and the Vertical Drift Technologies. The design of the DUNE Near Detector is progressing as well, with the construction of the 2x2 Demonstrator, a technical demonstrator of the ArgonCube detector concept. Between 2021 and 2023, the 2x2 Demonstrator modules were sequentially constructed and operated at the University of Ber, where they operated on cosmic ray muons. Immediately following these test runs, the four modules were shipped fully-assembled to Fermilab and in transported underground to the MINOS cavern in 2023. In early 2024 the modules began collecting commissioning data in the NuMI beam for the purpose of detector calibration. Visual scanning and data reconstruction allowed to reconstruct neutrino events. NuMI beam is not available in 2025 and will be resumed in 2026. The 2x2 Demonstrator will resume collecting neutrino data in 2026. The studies of the DUNE physics reach are progressing. This includes the development of the detector simulation and the optimisation of the reconstruction algorithms.