Training foundation AI models from scratch can play a pivotal role in enhancing privacy, as discussed in a recent ZDNet article.
Rather than relying on massive external datasets with potential privacy vulnerabilities, these models utilize localized data, providing robust protection against privacy breaches.
Depending on the use case, a common challenge companies face is whether they have enough data of their own to train the AI model, he said. He noted, however, that data quantity did not necessarily equate data quality.
However, an emerging concern is that adding domain-specific content to an existing Language Learning Model (LLM) pre-trained on general knowledge requires significantly less data.
The article highlights Jiva, an agritech vendor, who prioritizes accuracy by utilizing AI in its mobile app, Crop Doctor. The app diagnoses crop diseases using image processing and computer vision, suggesting appropriate treatments. Additionally, AI evaluates the credit worthiness of farmers seeking cash advancements pre-harvest. Jiva employs various AI tools like Pinecorn, OpenAI, scikit-learn, Google’s TensorFlow, and Vertex AI.