We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
"Vector Symbolic Architectures In Clojure" by Carin Meier
Discover the innovative Vector Symbolic Architectures (VSAs) in action, a mathematical framework for representing complex patterns in high-dimensional spaces, and learn how Clojure implementation enables AI, natural language processing, and more.
- Vector Symbolic Architectures (VSAs) are a mathematical way to represent complex patterns in high-dimensional spaces.
- VSAs can be used to merge symbolic operations with algebra to determine meaning.
- In VSAs, all data structures are hyperdimensional vectors, which can contain arbitrary amounts of information.
- VSAs can be used to represent strings, numbers, key-value pairs, collections, and sequences.
- The three operations in VSAs are addition, permutation, and clipping.
- Addition is element-wise, and clipping sets the magnitude of the result.
- Permutation is used to bind vectors together, and can be thought of as a way to associate values.
- Clipping and permutation are used to protect the associations between values in the vector.
- The VSA implementation is 100% dense, meaning that every element in the vector is used.
- The VSA map is initialized with a random hyperdimensional vector, and can be queried using the bind operation.
- The VSA can be used to represent complex patterns, and can be used to make predictions or classify data.
- VSAs have applications in AI, natural language processing, and other areas of research.
- The intersection of VSAs and deep learning is an area of active research, and has potential applications in tasks such as language translation and image recognition.
- Carin Meier is a researcher in the field of VSAs, and has worked on implementing VSAs in the programming language Clojure.