video1.0<iframe src="https://www.loom.com/embed/6a06c2ea00c04f319e273468e7108fbd" frameborder="0" width="1110" height="832" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>8321110Loomhttps://www.loom.com8321110https://cdn.loom.com/sessions/thumbnails/6a06c2ea00c04f319e273468e7108fbd-1342ba600626b5ad.gif79.985In this video, I discuss the challenges we face in training and fine-tuning AI models, particularly the issues with cloud compute environments that hinder our progress. I share my experience at Bacranium, where even highly skilled teams struggled with unreliable setups, which ultimately slowed down our experiments. To address this, we developed Train Lane, a platform that simplifies AI training through an easy-to-use Python SDK. I demonstrate how it works, highlighting the automatic allocation of GPU instances and the live monitoring dashboard it provides. I encourage you to explore Train Lane and see how it can enhance your AI training processes.