Seeking Real-World ML/AI Production Results and Experiences
Analysis
This post from r/MachineLearning highlights a common frustration in the AI community: the lack of publicly shared, real-world production results for ML/AI models. While benchmarks are readily available, practical experiences and lessons learned from deploying these models in real-world scenarios are often scarce. The author questions whether this is due to a lack of willingness to share or if there are underlying concerns preventing such disclosures. This lack of transparency hinders the ability of practitioners to make informed decisions about model selection, deployment strategies, and potential challenges they might face. More open sharing of production experiences would greatly benefit the AI community.
Key Takeaways
- •Real-world production results are valuable but often scarce.
- •There may be concerns preventing the sharing of production experiences.
- •More transparency in production deployments would benefit the AI community.
“'we tried it in production and here's what we see...' discussions”