article thumbnail

Design Patterns in Python for AI and LLM Engineers: A Practical Guide

Unite.AI

As AI engineers, crafting clean, efficient, and maintainable code is critical, especially when building complex systems. For AI and large language model (LLM) engineers , design patterns help build robust, scalable, and maintainable systems that handle complex workflows efficiently.

Python 144
article thumbnail

AI Engineer Summit - Building Blocks for LLM Systems & Products

Eugene Yan

I give one talk a year and in 2023 this is that talk.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

LLM Benchmarks in 2024.

Towards AI

Author(s): Tim Cvetko Originally published on Towards AI. An Overview of Why LLM Benchmarks Exist, How They Work, and What’s Next LLMs are complex. As these LLMs adopt ever-greater size, their performance starts to ensue into “what it means to be human”, i.e. their reasoning capabilities. AI Engineers, Founders, VCs, etc.

LLM 119
article thumbnail

TensorRT-LLM: A Comprehensive Guide to Optimizing Large Language Model Inference for Maximum Performance

Unite.AI

As the demand for large language models (LLMs) continues to rise, ensuring fast, efficient, and scalable inference has become more crucial than ever. NVIDIA's TensorRT-LLM steps in to address this challenge by providing a set of powerful tools and optimizations specifically designed for LLM inference.

article thumbnail

Merlinn: An Open-Source LLM-Powered-On-Call Copilot AI Engineer that Automatically Listens to Production Incidents and Resolves It for You

Marktechpost

The post Merlinn: An Open-Source LLM-Powered-On-Call Copilot AI Engineer that Automatically Listens to Production Incidents and Resolves It for You appeared first on MarkTechPost.

article thumbnail

TAI #104; LLM progress beyond transformers with Samba?

Towards AI

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week we saw a wave of exciting papers with new LLM techniques and model architectures, some of which can quickly become integrated into production LLMs. Why should you care?

LLM 116
article thumbnail

AI’s Trillion-Dollar Problem

Unite.AI

LLMs Differentiation Problem Adding to this structural challenge is a concerning trend: the rapid convergence of large language model (LLM) capabilities. In other words, while every new LLM boasts impressive performance based on standard benchmarks, a truly significant shift in the underlying model architecture is not taking place.