Anthropic’s new Claude research reveals a hidden internal “global workspace” that resembles human conscious processing, ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

Sophisticated AI models tend to require a lot of memory and take up a lot of storage space. One of the ways to reduce that ...

Right off the bat, let’s give a shout out to the mathematician propeller-heads who create the transformations that make it possible to do all kinds of high performance computing to simulate, model, ...

Abstract: There are a wide variety of different vector formalisms currently utilized in engineering and physics. For example, Gibbs' three-vectors, Minkowski four-vectors, complex spinors in quantum ...

I will explain examples of linear transformations of Lie groups. Regarding left-invariant vectors, I will show the equivalence between the expression viewed from the mapping of tangent vectors and the ...

Abstract: We propose a new class of nested vector-sensor arrays which is capable of significantly increasing the degrees of freedom (DOF). This is not a simple extension of the nested scalar-sensor ...

Researchers used algebra and geometry together to solve an old random walk problem. Random walk ideas have informed everything from biology to video games. This team identified a key geometry idea ...

Vector embeddings are the backbone of modern enterprise AI, powering everything from retrieval-augmented generation (RAG) to semantic search. But a new study from Google DeepMind reveals a fundamental ...

KokkosKernels implements local computational kernels for linear algebra and graph operations, using the Kokkos shared-memory parallel programming model. "Local" means not using MPI, or running within ...