Fine-tuning gpt-oss 20b model to efficiently detect users intents to eliminate latency bottleneck. We need intent detection that preserves the accuracy of a bigger model while delivering responses fast enough to keep multi-threaded conversations fluid. Our goal is to maintain high-quality intent classification with minimal response times so the main thread remains free most of the time.
Team
+1Placement
Advertisers struggle to optimize campaigns across budgets, targeting, creatives, and engagement. Traditional tools fail to unify campaign data, product info…
+1Supply Chains are always at risk. From strikes, tariffs, shortages and natural disasters. The effects of this ripple through the eco system with millions at…
Submit video for ADA compliance analysis and present recommendations on how to resolve them.
Problem Statement: Generate multimodal data to complement or be in distribution with a users existing corpus of data. LabRat is an extension to that helps…
We solve the problem of shallow, forgettable networking by creating a Human CRM that makes every interaction authentic, contextual & actionable. It learns…
citizen opens app → sees hospital availability → sees estimate of how many other citizens are heading towards a hospital with availability → citizen chooses…
