Designing for Forward Compatibility in Gen AI // Rohit Agarwal // #189

MLOps podcast #189 with Rohit Agarwal, CEO of Portkey.ai, Designing for Forward Compatibility in Gen AI. // Abstract For two whole years of working with a large LLM deployment, I always felt uncomfortable. How is my system performing? Are my users liking the outputs? Who needs help? Probabilistic systems can make this really hard to understand. In this talk, we'll discuss practical & implementable items to secure your LLM system and gain confidence while deploying to production. // Bio Rohit is the Co-founder and CEO of portkey.ai which is an FMOps stack for monitoring, model management, compliance, and more. Previously, he headed Product & AI at Pepper Content which has served ~900M generations on LLMs in production. Having seen large LLM deployments in production, he's always happy to help companies build their infra stacks on FM APIs or Open-source models. // MLOps Jobs board https://mlops.pallet.xyz/jobs // MLOps Swag/Merch https://mlops-community.myshopify.com/ // Related Links Website: https://portkey.ai ⁠ --------------- ✌️Connect With Us ✌️ ------------- Join our slack community: https://go.mlops.community/slack Follow us on Twitter: @mlopscommunity Sign up for the next meetup: https://go.mlops.community/register Catch all episodes, blogs, newsletters, and more: https://mlops.community/ Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/ Connect with Rohit on LinkedIn: https://www.linkedin.com/in/1rohitagarwal/ Timestamps: [00:00] Rohit's preferred coffee [00:15] Takeaways [03:22] Please like, share, and subscribe to our MLOps channels! [05:16] Rohit's current work [06:37] The Portkey landscape [09:13] Compute unit is no longer a Cloud resource, it's a Foundational Model [11:09] Hang-ups at high-scale models and how to combat them [15:22] Complexity of the Apps evolving [19:54] Rohit's working relationships with the agents [22:52] Fine-tuning reliability [24:38] Small language models can outperform larger ones [26:38] Market map at Portkey [34:37] AI Gateway [37:59] Worker Bee and Queen Bee [39:27] Security and Compliance [43:11] Idea of Data Mesh [45:57] Forward compatibility [49:59] Decoupling AI Gateway from the code [56:05] Hardest design decisions to make since creating Portkey [58:52] Wrap up

Om Podcasten

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations.