Join us for an enlightening conversation with Julien Simon, VP and Chief Evangelist at ARCEE.AI , as he shares deep insights on building practical and cost-efficient AI solutions. From his extensive experience at AWS, Hugging Face, and now ARCEE.AI, Julien discusses why "small is beautiful" when it comes to language models, revealing how 10B parameter models can now match the performance of much larger 72B models from just months ago. Learn about innovative techniques like model merging, the importance of proper infrastructure choices, and practical advice for organizations starting their AI journey.
This episode covers critical topics including:
● Why small language models are the future of enterprise AI
● How to optimize costs while maintaining performance
● The role of CPU vs GPU inference
● Essential architecture considerations for AI workloads
● Best practices for building production-ready AI systems
Whether you’re a startup, enterprise, or public sector organization, this episode offers invaluable guidance on building scalable, efficient, and practical AI solutions in today’s rapidly evolving landscape.
Learn more:
Build and scale the next wave of AI innovation on AWS: https://go.aws/ai
ARCEE.AI: https://www.arcee.ai/
Julien Simon Youtube channel : https://www.youtube.com/@juliensimonfr
00:00:00 : Introduction
00:02:18 : Journey into AI
00:06:40 : Arcee.ai small language models champion
00:09:02 : Arcee.ai global presence
00:10:19 : Use cases for SLMs and AI agents
00:15:00 : Post training with model merging, model distillation
00:17:20 : Model routing
00:19:15 : Orchestra drag and drop agentic platform
00:20:42 : How to build the best SLM ?
00:23:29 : Synthetic data and data quality
00:25:26 : Open source in AI
00:28:04 : Reflecting cultural nuances
00:31:02 : Biases in synthetic data
00:34:55 : What is an SLM
00:36:33 : Obsessing on cost efficiency
00:39:37 : CPU Inference
00:41:49 : Infrastructure and model choice
00:45:38 : GPU-less and microservices architecture
00:48:02 : Training on AWS: Hyperpod & Trainium
00:55:48 : Key advice for organizations starting with AI
01:02:14 : Closing remarks and resources
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