We Can All Be AI Engineers and We Can Do It with Open Source Models // Luke Marsden // #273

Luke Marsden, is a passionate technology leader. Experienced in consultant, CEO, CTO, tech lead, product, sales, and engineering roles. Proven ability to conceive and execute a product vision from strategy to implementation, while iterating on product-market fit.

We Can All Be AI Engineers and We Can Do It with Open Source Models // MLOps Podcast #273 with Luke Marsden, CEO of HelixML.

// Abstract

In this podcast episode, Luke Marsden explores practical approaches to building Generative AI applications using open-source models and modern tools. Through real-world examples, Luke breaks down the key components of GenAI development, from model selection to knowledge and API integrations, while highlighting the data privacy advantages of open-source solutions.

// Bio

Hacker & entrepreneur. Founder at helix.ml. Career spanning DevOps, MLOps, and now LLMOps. Working on bringing business value to local, open-source LLMs.

// MLOps Swag/Merch

https://mlops-community.myshopify.com/

// Related LinksWebsite: https://helix.ml

About open source AI: https://blog.helix.ml/p/the-open-source-ai-revolution

Ratatat Cream on Chrome: https://open.spotify.com/track/3s25iX3minD5jORW4KpANZ?si=719b715154f64a5f

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Timestamps:

[00:00] Michael's preferred coffee

[00:21] Takeaways

[01:59] Please like, share, leave a review, and subscribe to our MLOps channels!

[02:10] Gaming to AI Accelerators

[11:34] Torch Chat goals

[18:53] Pytorch benchmarking and competitiveness

[21:28] Optimizing MLOps models

[24:52] GPU optimization tips

[29:36] Cloud vs On-device AI

[38:22] Abstraction across devices

[42:29] PyTorch developer experience

[45:33] AI and MLOps-related antipatterns

[48:33] When to optimize

[53:26] Efficient edge AI models

[56:57] Wrap up