With enterprises prioritizing secure AI deployments, it’s essential to ensure proprietary data is truly an asset, not a ...

(Jump to Section) Common challenges include data acquisition and quality management, data privacy and security, model explicability, infrastructure requirements, and regulatory and ethical ...

Where to start: clean data is crucial for successful AI integration It is clear that AI has many benefits, but an AI ...

Data quality KPIs and maturity model Integrating key performance indicators (KPIs) with a data quality maturity model enables organizations to assess and enhance their data management practices ...

AI’s growth is limited by poor-quality data, not model size. Human expertise in data curation, decentralized feedback and ...

And it achieved this despite air quality data being relatively limited compared to weather data. Because the model first learns from a large and diverse set of data, it can be fine-tuned with smaller ...

Microsoft has launched several new 'open' AI models, the most capable of which is competitive with OpenAI's o3-mini on at least one benchmark.

A new ultra-lightweight artificial intelligence (AI) model has been developed that assists in generating high-quality images without directly sending sensitive data to servers. This technological ...