enabling organizations to utilize it for RAG (retrieval-augmented generation, which uses supplemental data to improve results) and fine-tuning large language models.

Traditional data collection models are reaching their limits ... This fragmentation stifles innovation and prevents AI systems from reaching their full potential. At the same time, AI systems ...

Additionally we have been collecting 1st party data online through brand activations, data collection promo campaigns, partnerships. However our data collection process to... We’re long-term ...

For companies willing to embrace privacy-first innovation ... from machine learning models that minimize data collection to tools that enhance interoperability. The industry is evolving to ...

Unlike traditional data collection models, these marketplaces prioritize privacy-enhancing technologies, giving users more control over sensitive data. Decentralized compute platforms can build ...

is introducing a new process chain for data collection with the accompanying IT landscape. Data is of crucial importance in making high quality statistics. CBS needs large-scale innovation to ensure ...

AI-driven applications in customer analytics, computer vision and predictive maintenance require large labeled datasets. Synthetic data can deliver datasets large enough to be useful. Note that ...