The Future of Enterprise #AI: #IBM #Granite 4.1 Technical Analysis

In this video, we explore IBM Granite 4.1 — one of the most advanced open-source large language model families released under Apache 2.0. We break down the complete architecture, training pipeline, reinforcement learning stages, long-context scaling, tool calling support, benchmark performance, and enterprise deployment strategy.
https://huggingface.co/blog/ibm-granite/granite-4-1?utm_source=newsletter&utm_medium=email&utm_term=2026-05-05&utm_campaign=Global+AI+Weekly+-+Issue+148
You’ll learn:

Granite 4.1 model architecture
Decoder-only transformer design
Grouped Query Attention (GQA)
RoPE positional embeddings
SwiGLU activations
15 trillion token pretraining pipeline
Multi-stage reinforcement learning
RLHF + GRPO + DAPO training
Long context extension to 512K
Tool calling workflows
IBM Granite benchmarks
Granite 4.1 vs Granite 4.0 comparison
FP8 quantization for inference
Enterprise AI deployment strategies
Open-source LLM engineering insights

This video is perfect for:
AI Engineers, ML Engineers, LLM Researchers, GenAI Developers, Data Scientists, AI Architects, Cloud Engineers, and anyone building enterprise-grade AI systems.

Topics Covered:
Granite 4.1, IBM AI, Open Source LLMs, LLM Training, RLHF, GRPO, DAPO, Tool Calling, Agentic AI, Transformer Architecture, Long Context Models, vLLM, FP8 Quantization, AI Infrastructure, Hugging Face Models, Enterprise AI

Видео The Future of Enterprise #AI: #IBM #Granite 4.1 Technical Analysis канала BazAI