Supercharge Python & Rust with Generative AI - Best of Both Worlds

Channel:
United States Pragmatic AI Labs
Subscribers:
17,700
Published on ● Video Link: https://www.youtube.com/watch?v=o2votElo26c


Rust
Game:
Rust (2013)
Duration: 5:01
345 views
15

Learn how generative AI is bringing together the best aspects of Python and Rust. We compare the inherent strengths of both languages - Python's productivity and rapid iteration for humans vs Rust's performance, safety and modern design.
See how code generation taps into Python's readability while taking advantage of Rust's robust compiler and error checking. Generative models can safely produce up to 80% of routine code.
Key topics covered include:
Python's popularity and legacy strengths
Rust solving modern issues like threading and packaging
Using Rust for performance-intensive tasks
Leveraging Python's interactivity
Compiler protecting against AI hallucinations
Tilting towards more Rust usage with AI assistance
Maximizing strengths of both languages
This video explains the synergistic potential of combining Python, Rust and generative AI to build robust and scalable applications. Both languages have unique strengths that complement one another in the era of AI assistance.

Hey readers πŸ‘‹, if you enjoyed this content, I wanted to share some of my favorite resources to continue your learning journey in technology!
Hands-On Courses for Rust, Data, Cloud, AI and LLMs πŸš€

Rust Programming Specialization: https://www.coursera.org/specializations/rust-programming
Rust for DevOps: https://www.coursera.org/learn/rust-for-devops?specialization=rust-programming
Rust LLMOps: https://www.coursera.org/learn/rust-llmops?specialization=rust-programming
Rust Fundamentals: https://www.coursera.org/learn/rust-fundamentals
Data Engineering with Rust: https://www.coursera.org/programs/duke-university-on-coursera-obsio/learn/data-engineering-rust
Python and Rust with Linux Command Line Tools: https://www.coursera.org/learn/python-rust-linux
Virtualization, Docker, and Kubernetes for Data Engineering: https://www.coursera.org/learn/virtualization-docker-kubernetes-data-engineering
Cloud Machine Learning Engineering and MLOps: https://www.coursera.org/learn/cloud-machine-learning-engineering-mlops-duke
MLOps Tools: MLflow and Hugging Face: https://www.coursera.org/learn/mlops-mlflow-huggingface-duke
Data Visualization with Python: https://www.coursera.org/learn/data-visualization-python
Linux and Bash for Data Engineering: https://www.coursera.org/learn/linux-and-bash-for-data-engineering-duke
Spark, Hadoop, and Snowflake for Data Engineering: https://www.coursera.org/learn/spark-hadoop-snowflake-data-engineering
Cloud Virtualization, Containers and APIs: https://www.coursera.org/learn/cloud-virtualization-containers-api-duke
Cloud Data Engineering: https://www.coursera.org/learn/cloud-data-engineering-duke
Python Essentials for MLOps: https://www.coursera.org/learn/python-mlops-duke
DevOps, DataOps, MLOps: https://www.coursera.org/learn/devops-dataops-mlops-duke
Web Applications and Command-Line Tools for Data Engineering: https://www.coursera.org/learn/web-app-command-line-tools-for-data-engineering-duke
MLOps Platforms: Amazon SageMaker and Azure ML: https://www.coursera.org/learn/mlops-aws-azure-duke
Scripting with Python and SQL for Data Engineering: https://www.coursera.org/learn/scripting-with-python-sql-for-data-engineering-duke
Python and Pandas for Data Engineering: https://www.coursera.org/learn/python-and-pandas-for-data-engineering-duke
Cloud Computing Foundations: https://www.coursera.org/learn/cloud-computing-foundations-duke

πŸ“š Must-Read Books:

Practical MLOps: https://www.amazon.com/Practical-MLOps-Operationalizing-Machine-Learning/dp/1098103017
Python for DevOps: https://www.amazon.com/gp/product/B082P97LDW/
Developing on AWS with C#: https://www.amazon.com/Developing-AWS-Comprehensive-Solutions-Platform/dp/1492095877
Pragmatic AI Labs Books: https://www.amazon.com/gp/product/B0992BN7W8

πŸŽ₯ Follow & Subscribe:

Pragmatic AI Labs YouTube Channel: https://www.youtube.com/channel/UCNDfiL0D1LUeKWAkRE1xO5Q
52 Weeks of AWS Podcast: https://52-weeks-of-cloud.simplecast.com
noahgift.com: https://noahgift.com/
Pragmatic AI Labs Website: https://paiml.com/



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Tags:
python
rust
generative ai
machine learning
integration
performance
safety
python vs rust
code generation


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Rust Statistics For Pragmatic AI Labs

Pragmatic AI Labs currently has 9,346 views spread across 17 videos for Rust. There's close to 6 hours worth of content for Rust published on his channel, roughly 1.44% of the content that Pragmatic AI Labs has uploaded to YouTube.