Towards AI

OCTOBER 31, 2024

Data analytics has become a key driver of commercial success in recent years. The ability to turn large data sets into actionable insights can mean the difference between a successful campaign and missed opportunities. Flipping the paradigm: Using AI to enhance data quality What if we could change the way we think about data quality?

Data Quality 102

Data Quality Data Scarcity Automation Natural Language Processing 102

Unite.AI

SEPTEMBER 12, 2024

Much like a solid foundation is essential for a structure's stability, an AI model's effectiveness is fundamentally linked to the quality of the data it is built upon. In recent years, it has become increasingly evident that even the most advanced AI models are only as good as the data they are trained on.

Data Quality 162

Data Quality Data Scarcity AI AI 162

Marktechpost

FEBRUARY 29, 2024

Data scarcity in low-resource languages can be mitigated using word-to-word translations from high-resource languages. However, bilingual lexicons typically need more overlap with task data, leading to inadequate translation coverage. This approach faces challenges with domain specificity and performance compared to native data.

Artificial Intelligence 96

Artificial Intelligence Artificial Intelligence Data Scarcity NLP 96

Marktechpost

OCTOBER 11, 2024

The competitive dynamic between the two networks allows for continuous refinement of the synthetic data. As a result, the framework can generate high-quality, diverse datasets that can be applied to various domains, such as medical imaging or text generation, where data quality is critical.

Data Scarcity 109

Data Scarcity Neural Network Natural Language Processing Machine Learning 109

Marktechpost

MAY 8, 2024

Availability of training data: Deep learning’s efficacy relies heavily on data quality, with simulation environments bridging the gap between real-world data scarcity and training requirements.

Deep Learning 122

Deep Learning Neural Network Data Scarcity Natural Language Processing 122

Marktechpost

DECEMBER 15, 2024

The navigator then evaluates the fidelity of these instructions, filtering out low-quality data to train a better generator in subsequent iterations. This iterative refinement ensures continuous improvement in both the data quality and the models’ performance.

Data Scarcity 79

Data Scarcity Data Quality Automation AI 79

Viso.ai

DECEMBER 18, 2023

Instead of relying on organic events, we generate this data through computer simulations or generative models. Synthetic data can augment existing datasets, create new datasets, or simulate unique scenarios. Specifically, it solves two key problems: data scarcity and privacy concerns.

Computer Vision 52

Computer Vision Neural Network Auto-complete Data Scarcity 52