Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges
The use of artificial intelligence (AI) is becoming more prevalent across industries such as
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
healthcare, finance, and transportation. Artificial intelligence is based on the analysis of …
Data-centric artificial intelligence: A survey
Artificial Intelligence (AI) is making a profound impact in almost every domain. A vital enabler
of its great success is the availability of abundant and high-quality data for building machine …
of its great success is the availability of abundant and high-quality data for building machine …
Multimodal foundation models: From specialists to general-purpose assistants
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …
methods to data compression. Recent advances in statistical machine learning have opened …
Fingpt: Democratizing internet-scale data for financial large language models
Large language models (LLMs) have demonstrated remarkable proficiency in
understanding and generating human-like texts, which may potentially revolutionize the …
understanding and generating human-like texts, which may potentially revolutionize the …
[PDF][PDF] Machine psychology: Investigating emergent capabilities and behavior in large language models using psychological methods
T Hagendorff - arxiv preprint arxiv:2303.13988, 2023 - cybershafarat.com
Large language models (LLMs) are currently at the forefront of intertwining AI systems with
human communication and everyday life. Due to rapid technological advances and their …
human communication and everyday life. Due to rapid technological advances and their …
Data-centric ai: Perspectives and challenges
The role of data in building AI systems has recently been significantly magnified by the
emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model …
emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model …
Data‐Driven Design for Metamaterials and Multiscale Systems: A Review
Metamaterials are artificial materials designed to exhibit effective material parameters that
go beyond those found in nature. Composed of unit cells with rich designability that are …
go beyond those found in nature. Composed of unit cells with rich designability that are …
The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review
D Schwabe, K Becker, M Seyferth, A Klaß… - NPJ Digital …, 2024 - nature.com
The adoption of machine learning (ML) and, more specifically, deep learning (DL)
applications into all major areas of our lives is underway. The development of trustworthy AI …
applications into all major areas of our lives is underway. The development of trustworthy AI …
[PDF][PDF] Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora
Children can acquire language from less than 100 million words of input. Large language
models are far less data-efficient: they typically require 3 or 4 orders of magnitude more data …
models are far less data-efficient: they typically require 3 or 4 orders of magnitude more data …
Opendataval: a unified benchmark for data valuation
Assessing the quality and impact of individual data points is critical for improving model
performance and mitigating undesirable biases within the training dataset. Several data …
performance and mitigating undesirable biases within the training dataset. Several data …