Monitoring LLM behavior: Drift, retries, and refusal patterns

The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production.
VentureBeat

DeepMind discovers that AI large language models can optimize their own prompts

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the ...
TechCrunch

Instead of fine-tuning an LLM as a first approach, try prompt architecting instead

Amid the generative AI eruption, innovation directors are bolstering their business’ IT department in pursuit of customized chatbots or LLMs. They want ChatGPT but with domain-specific information ...
BizTech Magazine

Prompt Injection Attacks: The LLM Security Risk IT Leaders Must Address

Security leaders must adapt large language model controls such as input validation, output filtering and least-privilege ...