Latest Posts and Insights

A technical dive into a sneaky numerical instability issue with a custom loss function and how math tricks helped to solve it.

fore ai surveyed over 30 RAG developers on use cases and pain points. We present the results, which outline LLM trends and shed light on why adoption of LLM for RAGs has been slower than expected.

Explore the complex relationship between Language Models and their internal truths in fact extraction tasks. Understand how models prioritize faithfulness over correctness and the implications for AI applications.

Building RAGs is fun, but even with AI, there is no free lunch: To get your system to high quality, work is required. We have outlined here some of the common problems that may occur, and how to detect and fix them.

Air Canada was recently ordered to pay compensation because of inaccurate information from their AI Chatbot. Here's how an LLM evaluation suite like foresight could have helped prevent this turbulence.

Explore the importance of evaluating Language Model applications through metrics like Groundedness and Ground Truth Similarity. Learn how these metrics enhance LLM performance assessment.

Discover the potential and challenges of AI in 2024 as companies strive to improve accuracy and quality. Learn about the tools and strategies needed to climb the hill of AI advancement.