Effectively monitoring and optimizing your hashtag#LLMs is extremely crucial without which you are signing up for sub-optimal outputs at best & hashtag#legal, hashtag#compliance issue at worst.
Here are latest takeaways from some very interesting researches:
✅ Review LLM inputs and outputs DAILY. Don’t let those sneaky hashtag#failure modes catch you off guard.
✅ Multiple agents can be used to improve the performance of LLM’s. Embrace the power of ensemble learning. More agents = better performance. Scale up and watch your accuracy soar!
✅ AI can label data multiple times faster than humans. Considering messy, hashtag#unlabelled data is a massive problem. Unlock the hidden potential in your hashtag#enterprise data with purpose-built models like Refuel’s LLM-2. Label data 100x faster than humans.
✅ Continuously monitor, evaluate, and fine-tune your LLMs. It’s the secret sauce to building your AI moat.
Remember, your perception of “good” and “bad” outputs will evolve as you interact with more data. Embrace the journey and keep refining your LLMs.
hashtag#ai hashtag#llm hashtag#data