Easter couldn’t be “celebrated” more productively – on the 2nd of April the event “LLM Explainability, Mitigating Hallucinations & Ensuring Ethical Practices” has taken place at Google Berlin! 🔥
The main takeaways from the keynotes:
👾Hallucination in LLMs Can Be a Feature or a Bug: Hallucinations by LLMs can invent facts, which is problematic for factual consistency but may enhance user experience in creative tasks.
👾Systematic Approach to Hallucinations: Hallucinations should be addressed as part of the systems LLMs operate within, not just within the LLMs themselves. This is crucial for creating robust systems that can identify and correct hallucinations.
👾Understanding and Critiquing LLMs: Analysing the objectives of LLMs and comparing them with each other helps to identify and resolve problems.
👾Human-AI Collaboration: Involving humans in AI evaluation ensures balanced oversight and enhances dataset quality.
👾Context and Culture in LLM Use: The use of LLMs requires careful consideration of the cultural and contextual implications of their output. This helps in anticipating and addressing potential issues of toxicity and bias in diverse cultural contexts.
