Coffee Sessions #162

From Arduinos to LLMs: Exploring the Spectrum of ML

Explore the spectrum of MLOps from large language models (LLMs) to TinyML. Soham highlights the difficulties of scaling machine learning models and cautions against relying exclusively on open AI's API due to its limitations. Soham is particularly interested in the effective deployment of models and the integration of IoT with deep learning. He offers insights into the challenges and strategies involved in deploying models in constrained environments, such as remote areas with limited power and utilizing small devices like Arduino Nano.

Take-aways

- Comparison of MLOps for Large Scale ML vs TinyML - Some learnings we can take from TinyMLOps/TinyML to Large Scale ML - It’s easy to build an LLM application but really difficult to get it to production: latency, cost, reliability and trust are huge challenges that still need to be solved. We talk about some of this stuff in our newsletter (tinyml.substack.com)

In this episode

Soham Chatterjee

Soham Chatterjee

Machine Learning Lead, Sleek

Soham leads the machine learning team at Sleek, where he builds tools for automated accounting and back-office management. As an electrical engineer, Soham has a passion for the intersection of machine learning and electronics, specifically TinyML/Edge Computing. He has several courses on MLOps and TinyMLOps available on Udacity and LinkedIn, with more courses in the works.

Twitter

LinkedIn

Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.

Abi Aryan

Abi Aryan

Host

Abi is a machine learning engineer and a live streamer. Over the past six years, her focus has been building machine learning models for various industries including short-form video hosting, OTT, e-commerce, insurance tech, etc., for startups across the US, UK, Canada, and India. Prior to that, she was a Data Science Fellow with Insight Toronto and a Visiting Research Scholar at UCLA working in AutoML, MultiAgent Systems, and Emotion Recognition. In her free time, she helps produce the MLOps Community Podcast.