The latest in AI and NLP insights and research from the Datasaur team
Choosing the Right LLM: An Exploration into How Different Models Stack Up in Performance
With new models emerging frequently, boasting superiority over OpenAI, we dive into their strengths, weaknesses, and performance differences to uncover what sets them apart.
Enhancing Language Model Distillation with Datasaur
LLMs advance AI by revolutionizing language understanding. However, they demand heavy resources, making them expensive and hard to debug. Model distillation simplifies these models while retaining their capabilities.
Working with Machine Learning (ML) can be quite challenging. This is where MLOps (Machine Learning Operations) comes in. MLOps provides a valuable framework for ML engineers and data scientists.
Mongabay: First Indonesian Weak Supervised Dataset - Curated by Data Programming
Read more on how we utilize our own Data Programming feature to construct a weakly curated dataset sourced from Mongabay, an Indonesian conservation portal. This discovery was also featured at the South East Asian Language Processing workshop 2023.
Read about how Datasaur lets you track productivity at every level, from zooming in to check individual labeling progress to zooming out for project overviews.
We [Consensus] had a very complex and specific set of annotation needs. Datasaur was able to address those needs efficiently and effectively.
Eric Olson, Co-founder and CEO, Consensus
Information labeling tasks has been reduced by 80% which has allowed us to optimize our workflow much more, allowing us to focus on other areas that are also priorities for us.
Product Manager, LegalTech
"We looked at Prodigy, LightTag, LabelBox, Scale and more. You really can't beat Datasaur for their suite of features and price point."