Offline dengan aplikasi Player FM !
110. Why should you use Lambda for Machine Learning?
Manage episode 396187208 series 2980070
In this episode, we discuss using AWS Lambda for machine learning inference. We cover the tradeoffs between GPUs and CPUs for ML, tools like ggml and llama.cpp for running models on CPUs, and share examples where we've experimented with Lambda for ML like podcast transcription, medical imaging, and natural language processing. While Lambda ML is still quite experimental, it can be a viable option for certain use cases.
💰 SPONSORS 💰 AWS Bites is brought to you by fourTheorem, an Advanced AWS Partner. If you are moving to AWS or need a partner to help you go faster, check us out at fourtheorem.com ! In this episode, we mentioned the following resources.
- Episode "46. How do you do machine learning on AWS?": https://awsbites.com/46-how-do-you-do-machine-learning-on-aws/
- Episode "108. How to Solve Lambda Python Cold Starts": https://awsbites.com/108-how-to-solve-lambda-python-cold-starts/
- ggml (the framework): https://github.com/ggerganov/ggml
- ggml (the company): https://ggml.ai
- llama.cpp: https://github.com/ggerganov/llama.cpp
- whisper.cpp: https://github.com/ggerganov/whisper.cpp
- whisper.cpp WebAssembly demo: https://whisper.ggerganov.com/
- ONNX Runtime: https://onnxruntime.ai/
- An example of using whisper.cpp with the Rust bindings: https://github.com/lmammino/whisper-rs-example
- Project running Whisper.cpp in a Lambda function: https://github.com/eoinsha/whisper_lambda_cpp
- AWS Lambda Image Container Chest X-Ray Example: https://github.com/fourTheorem/lambda-image-cxr-detection
- Episode "103. Building GenAI Features with Bedrock": https://awsbites.com/103-building-genai-features-with-bedrock/
Do you have any AWS questions you would like us to address? Leave a comment here or connect with us on X, formerly Twitter: - https://twitter.com/eoins - https://twitter.com/loige
140 episode
Manage episode 396187208 series 2980070
In this episode, we discuss using AWS Lambda for machine learning inference. We cover the tradeoffs between GPUs and CPUs for ML, tools like ggml and llama.cpp for running models on CPUs, and share examples where we've experimented with Lambda for ML like podcast transcription, medical imaging, and natural language processing. While Lambda ML is still quite experimental, it can be a viable option for certain use cases.
💰 SPONSORS 💰 AWS Bites is brought to you by fourTheorem, an Advanced AWS Partner. If you are moving to AWS or need a partner to help you go faster, check us out at fourtheorem.com ! In this episode, we mentioned the following resources.
- Episode "46. How do you do machine learning on AWS?": https://awsbites.com/46-how-do-you-do-machine-learning-on-aws/
- Episode "108. How to Solve Lambda Python Cold Starts": https://awsbites.com/108-how-to-solve-lambda-python-cold-starts/
- ggml (the framework): https://github.com/ggerganov/ggml
- ggml (the company): https://ggml.ai
- llama.cpp: https://github.com/ggerganov/llama.cpp
- whisper.cpp: https://github.com/ggerganov/whisper.cpp
- whisper.cpp WebAssembly demo: https://whisper.ggerganov.com/
- ONNX Runtime: https://onnxruntime.ai/
- An example of using whisper.cpp with the Rust bindings: https://github.com/lmammino/whisper-rs-example
- Project running Whisper.cpp in a Lambda function: https://github.com/eoinsha/whisper_lambda_cpp
- AWS Lambda Image Container Chest X-Ray Example: https://github.com/fourTheorem/lambda-image-cxr-detection
- Episode "103. Building GenAI Features with Bedrock": https://awsbites.com/103-building-genai-features-with-bedrock/
Do you have any AWS questions you would like us to address? Leave a comment here or connect with us on X, formerly Twitter: - https://twitter.com/eoins - https://twitter.com/loige
140 episode
همه قسمت ها
×Selamat datang di Player FM!
Player FM memindai web untuk mencari podcast berkualitas tinggi untuk Anda nikmati saat ini. Ini adalah aplikasi podcast terbaik dan bekerja untuk Android, iPhone, dan web. Daftar untuk menyinkronkan langganan di seluruh perangkat.