Integrating Machine Learning and Knowledge Representation for Trustworthy AI
As AI models scale, they have become powerful at prediction. However, they still often struggle to reason consistently and transparently with symbolic knowledge and c
Efficient Scaling of LLMs via Optimization-Aware Architecture Design
The success of large language models (LLMs) is driven in large part by their scale. However, continued scaling is increasingly constrained by compute, data, and deployment co
Over the last few years, engineers at Kingland have seen the usage of AI in software development progressing from simple chatbots to code suggestions, and now to agentic AI.
Title: Big-Data Algorithms That Are Not Machine Learning
We shall introduce four algorithms that run very fast on large amounts of data, although typically the answers they give are approximate rather than precise. (1) Locality-sensitive hashing (2) Approximate counting (3) Sampling (4) Counting triangles in graphs.