Class-incremental learning
Class-incremental learning is a subfield of machine learning that focuses on the ability of models to learn new classes of data incrementally without forgetting previously learned information.
Artificial Intelligence
TransFusion (LiDAR-camera fusion)
TransFusion (LiDAR-camera fusion) is a technology that integrates LiDAR and camera data to enhance perception systems, primarily for autonomous vehicles and robotics. It leverages the strengths of both sensors to improve object detection, depth estimation, and environmental understanding.
MMLU (Measuring Massive Multitask Language Understanding)
MMLU (Measuring Massive Multitask Language Understanding) is a benchmark designed to evaluate the multitask language understanding abilities of large language models across a wide range of subjects. It measures performance on multiple choice questions derived from professional and academic topics to provide a standardized assessment of general language comprehension and reasoning.
Self-organizing map
A self-organizing map (SOM) is an unsupervised learning technique used in machine learning to visualize and analyze high-dimensional data.
Code as policies (robot control)
Code as policies in robot control refers to the practice of embedding rules and regulations into the programming of robots to ensure compliance with ethical and operational standards.
Google embedding (Gecko)
Google embedding (Gecko) is a concept related to integrating Google services or technologies within Gecko-based web browsers. It involves embedding Google features or content into the Gecko rendering engine, which is used by browsers like Mozilla Firefox.
DSPy (Declarative Self-improving Language Programs)
DSPy (Declarative Self-improving Language Programs) is a conceptual framework or programming paradigm aimed at creating software systems that can autonomously enhance their own code or behavior through declarative specifications. It combines principles from declarative programming with self-improvement capabilities to enable adaptive, evolving programs.
Gemini (language model)
Gemini is a language model developed to advance natural language processing tasks. It aims to improve understanding, generation, and interaction in AI systems through innovative architecture and training techniques.
Sentence-BERT (SBERT)
Sentence-BERT (SBERT) is a modification of the BERT network designed to generate semantically meaningful sentence embeddings. It allows efficient and accurate sentence similarity comparisons and clustering in natural language processing tasks.
Principal component analysis (PCA)
Principal component analysis (PCA) is a statistical technique used to reduce the dimensionality of data by transforming it into a new set of variables called principal components. These components capture the maximum variance within the data, enabling easier visualization, interpretation, and noise reduction.