The Gene Ontology (GO) Consortium has made significant advancements in the past two years, enhancing the GO resource for computable gene function knowledge. Key developments include the improved GO-CAM annotation framework, which allows for more detailed modeling of gene functions and causal relationships. The consortium has also increased the number of GO annotations by 10%, annotated gene products by 25%, and added over 9,400 new scientific articles. They have reviewed 20,000 annotations from experimental data, ensuring consistency with other ontologies. The GO website was redesigned for easier access to documentation, tools, and data. A historical archive of GO data from the past 15 years is now available, maintaining consistency in format and structure. Collaborations have enhanced GO, such as SynGO, which expanded the GO ontology for synapse biology, and Rhea, which improved the representation of catalytic activities. The GREEKC consortium improved the annotation of DNA-binding transcription factors. Annotation efforts have increased the number of GO annotations, with PAINT annotations contributing significantly. Annotation reviews have focused on improving consistency and reflecting current biological knowledge. The GO Term Matrix was used to identify and correct annotation errors. The GO ontology has been refined, including taxon constraints and inter-ontology inferences. The GO ontology is continuously updated to reflect new biological knowledge and user feedback. The Noctua curation platform supports the creation and review of GO annotations and GO-CAMs. GO-CAMs allow for more detailed modeling of gene functions and are now accessible via the GO website. The GO ribbon has been redesigned to provide a quick, interactive summary of gene functions. The GO website now offers improved access to documentation, tools, and data. The GO historical archive includes 173 monthly releases from 2005 to 2018, providing long-term archival data. The GO resource is supported by various funding sources and is used by researchers worldwide. The GO consortium continues to improve the resource through collaboration, curation, and updates to ensure its relevance and utility in bioinformatics.The Gene Ontology (GO) Consortium has made significant advancements in the past two years, enhancing the GO resource for computable gene function knowledge. Key developments include the improved GO-CAM annotation framework, which allows for more detailed modeling of gene functions and causal relationships. The consortium has also increased the number of GO annotations by 10%, annotated gene products by 25%, and added over 9,400 new scientific articles. They have reviewed 20,000 annotations from experimental data, ensuring consistency with other ontologies. The GO website was redesigned for easier access to documentation, tools, and data. A historical archive of GO data from the past 15 years is now available, maintaining consistency in format and structure. Collaborations have enhanced GO, such as SynGO, which expanded the GO ontology for synapse biology, and Rhea, which improved the representation of catalytic activities. The GREEKC consortium improved the annotation of DNA-binding transcription factors. Annotation efforts have increased the number of GO annotations, with PAINT annotations contributing significantly. Annotation reviews have focused on improving consistency and reflecting current biological knowledge. The GO Term Matrix was used to identify and correct annotation errors. The GO ontology has been refined, including taxon constraints and inter-ontology inferences. The GO ontology is continuously updated to reflect new biological knowledge and user feedback. The Noctua curation platform supports the creation and review of GO annotations and GO-CAMs. GO-CAMs allow for more detailed modeling of gene functions and are now accessible via the GO website. The GO ribbon has been redesigned to provide a quick, interactive summary of gene functions. The GO website now offers improved access to documentation, tools, and data. The GO historical archive includes 173 monthly releases from 2005 to 2018, providing long-term archival data. The GO resource is supported by various funding sources and is used by researchers worldwide. The GO consortium continues to improve the resource through collaboration, curation, and updates to ensure its relevance and utility in bioinformatics.