Abstract: We present Scallop, a language which combines the benefits of deep learning and logical reasoning. Scallop enables users to write a wide range of neurosymbolic applications and train them in a data- and compute-efficient manner. It achieves these goals through three key features: 1) a flexible symbolic representation that is based on the relational data model; 2) a declarative logic programming language that is based on Datalog and supports recursion, aggregation, and negation; and 3) a framework for automatic and efficient differentiable reasoning that is based on the theory of provenance semirings. We evaluate Scallop on a suite of eight neurosymbolic applications from the literature. Our evaluation demonstrates that Scallop is capable of expressing algorithmic reasoning in diverse and challenging AI tasks, provides a succinct interface for machine learning programmers to integrate logical domain knowledge, and yields solutions that are comparable or superior to state-of-the-art models in terms of accuracy. Furthermore, Scallop’s solutions outperform these models in aspects such as runtime and data efficiency, interpretability, and generalizability.
greysemanticist@lemmy.onetoProgramming@programming.dev•Why Facebook does not use Git – and why most other devs do • DEVCLASS
2 years
jujutsu is a fresh take on git-- you describe the work you’re about to do with jj new -m 'message'. Do the work. Anything not previously ignored in .gitignore is ready to commit with jj ci. You don’t have to git add anything. No futzing with stashes to switch or refocus work. Need that file back? jj restore FILENAME.
This is true. But at
jj ciyou’re plonked into an editor and can change the description.