A vector database is a database designed to store and managevector embeddings, which are mathematical representations of data in a high-dimensional space. In this space, each dimension corresponds to a feature of the data, and tens of thousands of dimensions might be used to represent sophistica...
In vector search, both the input question and passages in the corpus are encoded as dense vector representations. Relevant context is retrieved by finding passages with the highest semantic similarity to the question vector. However, questions often have an indirect relationship to the actual answers...
Function parameters: {{namespace.functionName $varName}} and {{namespace.functionName "value"}} syntax : The weather today in {{$city}} is {{weather.getForecast $city}}. Prompts needing double curly braces : {{ "{{" }} and {{ "}}" }} are special SK sequences. ...
Eye-tracking studies are becoming increasingly popular in mathematics education research. In a systematic review by Strohmaier et al. (2020), three benefits of the use of eye tracking are provided, all of which apply to the assessment situation here: observing solution processes (e.g., Ögren...
Visual mapless navigation (VMN), modeling a direct mapping between sensory inputs and agent actions, aims to navigate from a stochastic origin location to
for a desktop vector tool, make sure to check its size. If it consumes more disk space which your system can not supply, there'll be a performance lag, which is the last thing you would want to experience. So, either choose a tool that consumes less disk space or upgrade your PC, ...
Kernel memory provides the functionality to ingest and index data in a way that makes it possible to answer questions later. The interface IMemoryDb and the data structure MemoryRecord are how Kernel Memory connects to vector databases and storage systems capable of performing vector similarity search...
There's plenty of discussion of solutions to these problems on KLOV, UKVAC, and the FB vector forums with plenty of knowledgeable people able to answer questions. Also there are a fair few videos on Youtube going from theory to practice. Again, it's not that hard, so give it a go!
1.1Main results and organization of the paper In the first part of this paper, we consider the classical questions of optimal regularity, non-degeneracy, and density estimates for local minimizers to (1.2). Then, we derive a Weiss-type monotonicity formula, which allows us to use a blow-up...
In this paper, we classified all MNBC functions in six variables and proposed several constructions of MNBC functions outside the{\mathcal {M}}^{\#}class. In addition to the questions raised in Sects.2and3, we would like to mention the following open problems. ...