AI
The Engineer's Guide to Efficient AI Inference
A deep dive into the techniques and technologies for optimizing the performance and cost of running large AI models in production.
Efficient AI inference is the process of running trained models to generate predictions quickly and cost-effectively in a production environment. As models, particularly large language (LLM), mixture-of-experts (MoE), and multi-modal models, continue to grow in size and complexity, inference has become the central, long-term challenge in building scalable and financially viable AI products.
This research hub explores the key strategies for tackling the inference challenge. We cover the full stack of optimizations, from advanced model techniques like sub-4-bit quantization and speculative decoding to infrastructure decisions involving next-generation GPUs, TPUs, and custom AI accelerators. The focus is on understanding the trade-offs between latency, throughput, cost, and accuracy to build sustainable AI applications.
Latest briefings on The Engineer's Guide to Efficient AI Inference
AI
Security Concerns Now Slow AI Adoption
A new Linux Foundation report finds that security readiness is the biggest obstacle to AI adoption. A widening gap exists between the rush to deploy AI and the ability to secure it. The report notes 67% of teams face pressure to accelerate deployment despite security risks.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
AI
Figma's AI Agents Resolve Security Alerts 70% Faster
Figma built custom AI agents that help its security team investigate alerts and prepare code fixes. The agents learn from past incidents, reducing repetitive work and resolving complex security issues about 70% faster.
Neeraj Dhiman ·
Frequently asked questions
What is the difference between AI training and inference?
Training is the one-time or periodic process of teaching a model by feeding it vast amounts of data, which is computationally intensive and expensive. Inference is the process of using that trained model to make predictions on new, unseen data, which happens continuously in a live application and must be fast and cost-effective.
What is quantization in the context of AI models?
Quantization is a technique to reduce the numerical precision of a model's weights, for instance, from 16-bit brain floating-point (BF16) numbers down to 4-bit integers (INT4). This dramatically shrinks the model's memory footprint and accelerates computation on compatible hardware, leading to faster inference with often minimal impact on accuracy.
How do specialized hardware like GPUs help with inference?
Specialized hardware like GPUs (from NVIDIA, AMD), TPUs (from Google), and custom accelerators (e.g., AWS Inferentia, Groq LPUs) are designed for massive parallel computation. Their architecture, featuring thousands of cores and specialized units like NVIDIA's Tensor Cores, excels at the matrix operations central to AI models, delivering orders-of-magnitude lower latency than general-purpose CPUs.
What are some popular open-source frameworks for AI model serving?
Popular open-source frameworks include vLLM, known for its PagedAttention memory management, and optimized runtimes like TensorRT-LLM. Increasingly, these are packaged as containerized inference microservices (like NVIDIA NIM) or deployed via general-purpose servers like Triton, which handle complexities like dynamic batching and support for techniques like speculative decoding.