Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, etc). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!
Generative models: exploration to deployment
What is the model lifecycle like for experimenting with and then deploying generative AI models? Although there are some similarities, this lifecycle differs somewhat from previous data science practices in that models are typically not trained from scratch (or even fine-tuned). Chris and Daniel give a high level overview in this effort and discuss model optimization and serving.
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Featuring:
Show Notes:
- BigDL
- Article: Making LLMs even more accessible with bitsandbytes, 4-bit quantization and QLoRA
- Previous episode: Running large models on CPUs
- Baseten’s Truss
- Seldon
- Hugging Face’s TGI
- Intel Gaudi 2
- Intel TDX
Something missing or broken? PRs welcome!
Timestamps:
(00:07) - Welcome to Practical AI
(00:43) - Daniel at GopherCon & IIC
(03:31) - Local inference & TDX
(08:23) - Cloudflare Workers AI
(09:43) - Implementing new models
(16:14) - Sponsor: Neo4j
(17:11) - Navigating HuggingFace
(20:21) - Model Sizes
(24:34) - Running the model
(30:20) - Model optimization
(34:17) - Cloud vs local
(39:26) - Cloud standardization
(43:00) - Open source go-to tools
(46:21) - Keep trying!
(48:18) - Outro