How Data Platforms Affect ML & AI // Jake Watson // MLOps Podcast #207

Large Language Models have taken the world by storm. But what are the real use cases? What are the challenges in productionizing them? In this event, you will hear from practitioners about how they are dealing with things such as cost optimization, latency requirements, trust of output, and debugging. You will also get the opportunity to join workshops that will teach you how to set up your use cases and skip over all the headaches. Join the AI in Production Conference on February 15 and 22 here: https://home.mlops.community/home/events/ai-in-production-2024-02-15 ________________________________________________________________________________________ MLOps podcast #207 with Jake Watson, Principal Data Engineer at The Oakland Group, How Data Platforms Affect ML & AI. // Abstract I’ve always told my clients and colleagues that traditional rule-based software is difficult, but software containing Artificial Intelligence (AI) and/or Machine Learning (ML)* is even more difficult, sometimes impossible. Why is this the case? Well, software is difficult because it’s like flying a plane while building it at the same time, but because AI and ML make rules on the fly based on various factors like training data, it’s like trying to build a plane in flight, but some parts of the plane will be designed by a machine, and you have little idea what that is going to look like till the machine finishes. This double goes for more cutting-edge AI models like GPT, where only the creators of the software have a vague idea of what it will output. This makes software with AI / ML more of a scientific experiment than engineering, which is going to make your project manager lose their mind when you have little idea how long a task is going to take. But what will make everyone’s lives easier is having solid data foundations to work from. Learn to walk before running. // Bio Jake has been working in data as an Analyst, Engineer, and/or Architect for over 10 years. Started as an analys