A team from MIT has developed an algorithm to identify causal links in complex systems by measuring interactions between variables over time.
The versatile algorithm identifies variables that likely influence others in complex systems. This method analyzes data collected over time to measure interactions between variables and estimate the impact of changes in one variable on another. It generates a "causality map" showing which variables are strongly linked.
The algorithm distinguishes between different types of causality:
- **Synergistic:** A variable only influences another when paired with a second variable.
- **Redundant:** A change in one variable has the same effect as another variable.
The algorithm also estimates "causal leakage," indicating that some unknown influence is missing.
The versatile algorithm identifies variables that likely influence others in complex systems. This method analyzes data collected over time to measure interactions between variables and estimate the impact of changes in one variable on another. It generates a "causality map" showing which variables are strongly linked.
The algorithm distinguishes between different types of causality:
- **Synergistic:** A variable only influences another when paired with a second variable.
- **Redundant:** A change in one variable has the same effect as another variable.
The algorithm also estimates "causal leakage," indicating that some unknown influence is missing.
A new program from MIT helps children understand AI by letting them build small-scale language models.
- Introduction by Sid Kasivajhula
- Gerald Sussman: Teaching People Thinking: Programming and Powerful Ideas (3:00)
- Hạl Abelson: From Computational Thinking to Computational Action (18:50)
- Questions (33:40)
- Gerald Sussman: Teaching People Thinking: Programming and Powerful Ideas (3:00)
- Hạl Abelson: From Computational Thinking to Computational Action (18:50)
- Questions (33:40)
Matilde Marcolli, a mathematician at Caltech, has developed a new mathematical framework for Noam Chomsky's model of language, using ideas from theoretical physics. Chomsky's latest model, the minimalist program, simplifies language into a single computational operation called "merge," which combines elements of a sentence. Marcolli used Hopf algebras, a mathematical tool used in theoretical physics, to describe this merge operation. She worked with Chomsky and Bob Berwick to create a forthcoming book explaining this mathematical approach to language. Marcolli also taught a course and hosted workshops at Caltech on this topic, bringing together experts from various fields. This research supports Chomsky's philosophy that language should be studied using the methods and tools of the physical sciences.
This article describes the special keys on the Knight TV keyboard and their functions.
A new method called Clio enables robots to quickly map a scene and identify the items they need to complete a given set of tasks.
An interdisciplinary research project exploring the history and ideas behind the influential ELIZA chatbot, created in the 1960s. The project aims to contextualize ELIZA, analyze its code, and examine its cultural impact on human-computer interaction.
This book explores the integration of computational thinking into K-12 education, covering topics such as artificial intelligence literacy and physical computing. Edited by Siu-Cheung Kong and Harold Abelson.
This video features an interview with Professor Hal Abelson, a pioneer in computer science education. He reflects on his career, starting from his early work with Logo programming language and its use in education. He emphasizes the importance of computer education for everyone, particularly for children who can use technology to make a real-world impact.
Abelson also discusses the risks associated with artificial intelligence and MIT's decision to make educational materials freely available online, which led to MIT OpenCourseWare. He believes computer scientists should not only focus on technical advancements but also consider the ethical implications of their work, asking "What, in fact, is worth making?". The video also highlights resources like Logo, Scratch, and MIT App Inventor, encouraging viewers to explore these tools.
Abelson also discusses the risks associated with artificial intelligence and MIT's decision to make educational materials freely available online, which led to MIT OpenCourseWare. He believes computer scientists should not only focus on technical advancements but also consider the ethical implications of their work, asking "What, in fact, is worth making?". The video also highlights resources like Logo, Scratch, and MIT App Inventor, encouraging viewers to explore these tools.
Dan Weinreb, a founding member of Symbolics and LMI, refutes Richard Stallman's account of the split between the two companies. He provides his personal perspective on the events, as well as quotes from other participants.
