Atom
A work-in-progress relational and logic programming language inspired by Datalog and Bruce MacLennan's work on relational programming. It adopts the open-world assumption to allow missing values and heterogeneous data while enforcing data integrity, and is motivated by the idea that logic languages can provide strong correctness guarantees and a source of reinforcement learning in the LLM era. It favors relational data models over the object-oriented view.
What it addresses
Logic languages are seen as increasingly important in the LLM era to provide strong correctness guarantees and as a source of reinforcement learning; the author believes relational data models have many advantages over the object-oriented view.
Shared over time
Each entry reflects what was shared on that date. Details may have changed since then.
Atom
A work-in-progress relational and logic programming language inspired by Datalog and Bruce MacLennan's work on relational programming. It adopts the open-world assumption to allow missing values and heterogeneous data while enforcing data integrity, and is motivated by the idea that logic languages can provide strong correctness guarantees and a source of reinforcement learning in the LLM era. It favors relational data models over the object-oriented view.
Problem: Logic languages are seen as increasingly important in the LLM era to provide strong correctness guarantees and as a source of reinforcement learning; the author believes relational data models have many advantages over the object-oriented view.
Posted by @roland_nilsson · Original comment ↗
“I'm working on a new relational / logic language inspired by datalog and Bruce MacLennan's pioneering work on relational programming, but adopting the open-world assumption to allow missing values / heterogeneous data and enforce data integrity.”