Faster LLMs: Accelerate Inference with Speculative Decoding

Ready to become a certified watsonx AI Assistant Engineer? Register now and use code IBMTechYT20 for 20% off of your exam → https://ibm.biz/BdnJta Learn more about AI Inference here → https://ibm.biz/BdnJtG Want faster large language models? 🚀 Isaac Ke explains speculative decoding, a technique that accelerates LLM inference speeds by 2-4x without compromising output quality. Learn how "draft and verify" pairs smaller and larger models to optimize token generation, GPU usage, and resource efficiency. AI news moves fast. Sign up for a monthly newsletter for AI updates from IBM → https://ibm.biz/BdnJtn #llm #aioptimization #machinelearning

Join Today
Why Inference is hard..
▶︎

Why Inference is hard..

RAG vs. CAG: Solving Knowledge Gaps in AI Models
▶︎

RAG vs. CAG: Solving Knowledge Gaps in AI Models

How vLLM Became the Standard for Fast AI Inference | Simon Mo, Inferact
▶︎

How vLLM Became the Standard for Fast AI Inference | Simon Mo, Inferact

Is Fine-Tuning Still Needed? LLMs, RAG, & LoRA
▶︎

Is Fine-Tuning Still Needed? LLMs, RAG, & LoRA

Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou
▶︎

Mastering LLM Inference Optimization From Theory to Cost Effective Deployment: Mark Moyou

What Is Llama.cpp? The LLM Inference Engine for Local AI
▶︎

What Is Llama.cpp? The LLM Inference Engine for Local AI

Deep Dive: Optimizing LLM inference
▶︎

Deep Dive: Optimizing LLM inference

LLM Inference Explained: Prefill vs Decode and Why Latency Matters
▶︎

LLM Inference Explained: Prefill vs Decode and Why Latency Matters

How to make LLMs fast: KV Caching, Speculative Decoding, and Multi-Query Attention | Cursor Team
▶︎

How to make LLMs fast: KV Caching, Speculative Decoding, and Multi-Query Attention | Cursor Team

Speculation is all you need: Intro to Speculative Decoding for High Performance Inference
▶︎

Speculation is all you need: Intro to Speculative Decoding for High Performance Inference

What is AI Search? The Evolution from Keywords to Vector Search & RAG
▶︎

What is AI Search? The Evolution from Keywords to Vector Search & RAG

RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models
▶︎

RAG vs Fine-Tuning vs Prompt Engineering: Optimizing AI Models

This Post Office Was Totally Out of Control | 100% Cat Mail Co.
▶︎

This Post Office Was Totally Out of Control | 100% Cat Mail Co.

Understanding the LLM Inference Workload - Mark Moyou, NVIDIA
▶︎

Understanding the LLM Inference Workload - Mark Moyou, NVIDIA

CHOSEN ONE!! YOUR IDENTITY REVEAL JUST SHOOK THE INTERNET... AND THEIR MINDS
▶︎

CHOSEN ONE!! YOUR IDENTITY REVEAL JUST SHOOK THE INTERNET... AND THEIR MINDS

„Bei der Hochzeit meines Bruders behandelte mich die Familie wie Personal – bis ich zahlte.“
▶︎

„Bei der Hochzeit meines Bruders behandelte mich die Familie wie Personal – bis ich zahlte.“

Your Local LLM Is 3x Slower Than It Should Be
▶︎

Your Local LLM Is 3x Slower Than It Should Be

Understanding LLM Inference | NVIDIA Experts Deconstruct How AI Works
▶︎

Understanding LLM Inference | NVIDIA Experts Deconstruct How AI Works

What Are Large Reasoning Models (LRMs)? Smarter AI Beyond LLMs
▶︎

What Are Large Reasoning Models (LRMs)? Smarter AI Beyond LLMs

Transformers, the tech behind LLMs | Deep Learning Chapter 5
▶︎

Transformers, the tech behind LLMs | Deep Learning Chapter 5