Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.

In some ways, data and its quality can seem strange to people used to assessing the quality of software. There’s often no observable behaviour to check and little in the way of structure to help you ...

Here's how the JavaScript Registry evolves makes building, sharing, and using JavaScript packages simpler and more secure ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

In 2026, artificial intelligence skills sit on the short list for promotions in analytics, product, and operations. Teams want people who can frame the right problem, choose workable models, and ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...

AI Engineering focuses on building intelligent systems, while Data Science focuses on insights and predictionsBoth careers offer high salaries and ...

Python libraries handle real business tasks like APIs, data analysis, and machine learning at scaleUsing ready-made libraries ...

Something extraordinary has happened, even if we haven’t fully realized it yet: algorithms are now capable of solving ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.