Refuel

The team at Refuel just released their latest #LLM for data labeling, enrichment and cleaning, trained on our Databricks Mosaic AI Training infrastructure! Get the details here: https://lnkd.in/gVcarizZ

Better data = Better AI. In this episode of Software Engineering Daily I dive into why this is true, what makes it hard and how we're solving this at scale at Refuel. Thank you Sean Falconer for hosting and having me on! 🚀

🚀 TeachFX + Refuel: Leveraging Custom LLMs to Enhance Classroom Interactions 🎓 92% Agreement with human experts, in a complex domain ⏱ Reduced AI feature development time from 2 months to 2 weeks 📚 TeachFX, an ed-tech company focused on elevating classroom dialogue, teamed up with Refuel to revolutionize their product with new AI capabilities, enabling the detection of pivotal educational moments in classroom sessions. ✅ Leveraging Refuel's platform, TeachFX achieved a 92% agreement with expert annotators to create training datasets, on a complex, domain-specific task. ⚡ This streamlined the feature development process from two months to just two weeks, enabling a dramatic acceleration of TeachFX’s product roadmap. 💡 This partnership not only exemplifies the power of custom LLMs in enhancing data labeling efficiency and output quality, but also marks a significant stride towards improving educational outcomes. 👉 If you're interested to learn about how custom LLMs are changing the game with respect to data quality, check out the full case study in the comments below. For more insights into leveraging AI for educational excellence, follow TeachFX and Refuel on LinkedIn or sign up for a Refuel demo here: https://lnkd.in/gtKqbXix.

🚀 Retail AI success story for Beni + Refuel: Data normalization with LLMs for product catalog data 🎯 2x Accuracy Improvement 💨 < 1 day of Engineering Effort 📈 245% Increase In GMV for a major partner 👕👖 With a massive catalog of over 200 million items, Beni faced a daunting task: improving the accuracy of their product size attribute from 46% to over 80%. The solution? A partnership with Refuel and our custom LLMs. 🚀 In just one day of effort (compared to the weeks or months such a task would typically require), Beni improved the accuracy to an astounding 87%. This led to a 99% reduction in data quality issues for reseller partners and a 245% increase in Gross Merchandise Value for a major partner. 💡 If you're intrigued by how AI can improve product catalog data and drive significant business impact for marketplaces, check out this case study (click on the comments for the full story) 👉 For more stories like this, follow Refuel on LinkedIn or sign up for Refuel here: https://lnkd.in/gtKqbXix. #datascience #machinelearning #aiinnovation #retailtech #customervalue  #speed  #revenueboost #ai  #ml  #llms

Labeling with Confidence: Confidence estimation is an effective tool to mitigate hallucinations when leveraging LLMs for data labeling and enrichment: If we are able to estimate the model’s inherent confidence in its response, we can automatically reject low confidence labels, chain and ensemble LLMs. Excited to share a bit more about what we've been exploring and building at Refuel in this direction: https://lnkd.in/gyg54vfZ. You can access all of these features in Autolabel (https://lnkd.in/g7dX8Awi) with a one line config change to your labeling task!