Challenges and Solutions in Managing Code Security for ML Developers - ML 175

Challenges and Solutions in Managing Code Security for ML Developers - ML 175

Today, join Michael and Ben as they delve into crucial topics surrounding code security and the safe execution of machine learning models. This episode focuses on preventing accidental key leaks in notebooks, creating secure environments for code execution, and the pros and cons of various isolation methods like VMs, containers, and micro VMs.
They explore the challenges of evaluating and executing generated code, highlighting the risks of running arbitrary Python code and the importance of secure evaluation processes. Ben shares his experiences and best practices, emphasizing human evaluation and secure virtual environments to mitigate risks.
The episode also includes an in-depth discussion on developing new projects with a focus on proper engineering procedures, and the sophisticated efforts behind Databricks' Genie service and MLflow's RunLLM. Finally, Ben and Michael explore the potential of fine-tuning machine learning models, creating high-quality datasets, and the complexities of managing code execution with AI.
Tune in for all this and more as we navigate the secure pathways to responsible and effective machine learning development.


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How to Create Team Utils - ML 122

How to Create Team Utils - ML 122

Have you ever written code and thought, "hmm, I wonder if my teammates would use this." Well in today's episode, we show you how to go from concept to production-level code. Spoiler alert: you're goin...

21 Juli 20231h 4min

How to Get Sh*t Done - ML 121

How to Get Sh*t Done - ML 121

In today's episode, Michael and Ben break down some surefire methods to be successful. If you follow these tips, you are guaranteed to co-found the next Google. Some topics include time boxing excitin...

13 Juli 202358min

ML at Netflix and How to Learn Deeply - ML 120

ML at Netflix and How to Learn Deeply - ML 120

In today's episode, we speak with Netflix ML engineer Amir Ziai. Expect to learn about building ML tools for stakeholders, the pros and cons of a Netflix-like culture, and Amir's strategy for learning...

30 Juni 20231h 3min

How to get Promoted - ML 119

How to get Promoted - ML 119

In today's episode, we dive into Ben's experience in navigating the career ladder. Expect to learn why your leveling matrix is probably wrong and how you should actually spend your time to maximize ca...

23 Juni 202348min

How does Search Work? - ML 118

How does Search Work? - ML 118

In today's episode, we speak with Roman Grebennikov, an expert in ranking algorithms. Expect to learn about his open source project, the difference between retrieval and ranking, and much more!Sponsor...

15 Juni 202352min

How to Learn a New Tool - ML 117

How to Learn a New Tool - ML 117

In today's episode, we walk through Ben's experience creating the Hugging Face transformer flavor for ML flow. During this case study we highlight the structure he uses to learn new technologies and c...

8 Juni 202358min

The Innovation Cycle of AI - ML 116

The Innovation Cycle of AI - ML 116

Today we speak with ex-Googler, Praveen Paritosh. He has over 20 years of experience as a research scientist and has worked on some of AI's most impactful projects. Expect to learn about scientific in...

25 Maj 20231h 9min

All Things Machine Learning - ML 115

All Things Machine Learning - ML 115

Host from the Ruby Rogues podcast, Dave Kimura joins Ben and Michael for this week's crossover episode. They discuss applying machine learning, deep learning, and algorithm. They also dive into how ar...

11 Maj 20231h 7min

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