In this webinar, Sense Street will share their top 10 tips to help you get the most from your labeling team.
While foundation models can make it easier to label large datasets, the need for human supervision in labeling domain-specific items is still critical.
Nobody is more familiar with this than Sense Street. They develop large generative language models to understand a comprehensive array of financial jargon used across the life cycle of a trade - a task demanding niche expertise and high precision.
However, it's also critical for the enterprise to keep annotation costs down, and a major part of that is figuring out how to get the best performance from your human labellers.
Sense Street stands out as a notable representation of this achievement, as they managed to double the output of their data annotators and maintain a consistently smooth operational pace throughout this process.
In this webinar, you’ll learn:
- The crucial role of human labellers in the success of AI training
- Key processes to boost labeling productivity
- How Label Studio features enhance workflow
- Approaches to streamline labeling workload distribution
- And much more
Speakers
Linguist