Optimizing Generative AI on Arm Processors: from Edge to Cloud

Colleagues, the “Optimizing Generative AI on Arm Processors: from Edge to Cloud” training shows you how to optimize GenAI workloads on real-world systems using techniques such as SIMD (SVE, Neon), low-bit quantization, and the optimized KleidiAI library. You will develop essential strategies and skills to build scalable, high-performance AI on edge and cloud-based platforms based on the most widespread processor architecture. You will learn how to optimize AI inference using Arm-specific techniques such as SIMD (SVE, Neon) and low-bit quantization. The course covers practical strategies for running generative AI efficiently on edge and cloud-based Arm platforms. You will also explore the trade-offs between cloud and edge deployment, gaining both theoretical knowledge and hands-on skills.

By the end of this course, you will have a strong foundation in deploying high-performance AI models on Arm hardware. Skill-based training modules include: 1) Challenges Facing Cloud and Edge GenAI Inference - Understanding the limitations and constraints of AI inference in different environments, 2) Generative AI Models - Exploring model architectures, training methodologies, and deployment considerations, 3) ML Frameworks and Optimized Libraries - A deep dive into AI software stacks, including PyTorch, llama.cpp, and Arm-specific optimizations, and 4) Optimization for CPU Inference - Techniques such as quantization, pruning, and leveraging SIMD instructions for faster AI performance.

Enroll today (teams and execs are welcome): https://edx.sjv.io/m4aaE1 

Recommended Reading:

1 - “AI Software Engineer: ChatGPT, Bard & Beyond” (Audible) or (Kindle)  

2 - “ChatGPT, Gemini and Llama - The Journey from AI to AGI, ASI and Singularity” (Audible) (Kindle)

3 - “The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age” (Audible) (Kindle)

Much success in your AI career, AI Academy (please subscribe and share with you colleagues)