We propose the design of an AI platform that provides services in the cloud to accelerate ML adoption.
Services are exposed via HTTP(S) endpoints and offer the following functionalities:
- train/fine-tune machine learning models;
- host/share datasets and trained models in the cloud;
- use models to make predictions about new data;
- manage models and versions through a public catalog.
We provide service implementations for some common NLP tasks (text-classification, masked language modeling, semantic search) using Transformer-based Language Models. These NLP tasks are being integrated into a Web Application devoted to manage INFN research products (publications, thesis, talks).