AI
How to Evaluate Fine-Tuned Language Models: Key Metrics and Techniques
Evaluating Fine-Tuned Large Language Models: Key Metrics and Their Importance
As Artificial Intelligence (AI) becomes more usefu...
Evaluating Large Language Models (LLMs) – A Deep Dive
Evaluating Large Language Models: Key Metrics and Their Importance
As part of our ongoing blog series on AI in the insurance ind...
How to Build a Private LLM for Enterprise Data
Enterprise data is one of the most valuable assets an organization owns. Contracts, customer records, financial documents, internal pol...
What Is an AI Agent? How AI Agents Work in Enterprise Applications
AI is moving beyond systems that simply answer questions. The next generation of enterprise AI can understand objectives, reason throug...
Operational Risks in AI: How Specialized AI Solutions Can Mitigate These Issues
Addressing Operational Risks in AI: How InsurancGPT Mitigates Challenges in the Insurance Industry
Artificial intelligence (AI) ...
Mitigating Bias in LLM Models
Mitigating Bias in AI: Strategies to Reduce Biases in LLM Models and Ensure Fair Decision-Making in Insurance
Artificial intelli...
Data Privacy Concerns in Generic LLM Models
Data Leak in ChatGPT: A notable incident highlighting the risks associated with generic AI models occurred with ChatGPT by OpenAI. In M...
Evaluating Large Language Models – Evaluation Metrics
In the field of AI, evaluation metrics serve as an essential tool to navigate through the quality and performance of language models. T...
Evaluating Large Language Models – LLM Benchmarks
Benchmarks of Large Language Models
Building on the first article, this post looks at key LLM benchmarks in more depth. MMLU, LLMEval...
Evaluating Large Language Models
Welcome to the first article in our three-part series titled "Evaluating Large Language Models".
In this inaugural article, we e...