OpenAI's Model Spec tells us a lot about how the company thinks about prompt engineering. Let's explore it and see how to use it in your daily prompting. The Three-Layer Approach The Model Spec uses three layers: objectives, rules, and defaults. This structure makes prompts more
As AI models become increasingly sophisticated, there's a growing narrative that prompt engineering – the art and science of instructing large language models – will soon become obsolete. As models get better at understanding natural language, will the need for carefully crafted prompts will disappear? The death of prompt engineering
“More compute!” is a common refrain these days in discussions about enhanced LLM performance and capability. Just scan a few recent headlines to see the resources major companies are willing to pour into getting it. In a broad sense, this refers to more and better hardware used in model training.
One of the key factors driving the growth of Large Language Models (LLMs) is in-context learning (ICL), a unique learning paradigm that allows LLMs to adapt to new tasks by processing examples provided directly within the input prompt. This article breaks down the intricacies of ICL, exploring its mechanisms, benefits,
Large language models (LLMs) are revolutionizing how we interact with technology, but their complexity introduces unique challenges for developers. Ensuring LLMs perform reliably and efficiently requires robust observability—the ability to understand and diagnose their behavior. This article compares the best tools for measuring LLM observability, examining their key features
Software development is being fundamentally reshaped by AI, but the biggest challenge isn't technical expertise – it's domain knowledge. The next generation of AI products will be built by doctors, lawyers, and educators, not just machine learning engineers. We're excited to announce that PromptLayer has
As AI systems become more sophisticated and integrated into our daily lives, the need for robust, reliable, and comprehensive evaluation tools becomes increasingly critical. AI evaluation tools enable developers, researchers, and organizations to assess the performance, identify weaknesses, and ensure the ethical and responsible deployment of AI models. This article
While both DeepSeek V2 and Coder V2 leverage DeepSeek's innovative Mixture-of-Experts (MoE) architecture, DeepSeek V2 is a versatile, general-purpose language model excelling in both natural language processing and code generation, whereas Coder V2 is specifically designed and optimized for a wide array of coding tasks Table of Contents
OpenAI's upcoming o3 and DeepSeek's r1 represent significant advancements in the domain of reasoning models. Both models have garnered attention for their impressive performance on various benchmarks, sparking discussions about the future of AI and its potential impact on various industries. From what we know, OpenAI&
DeepSeek, a new Chinese AI company that released r1, is turning heads and this is a comprehensive blog to learn about its implications. Founded in late 2023 by Liang Wenfeng—a serial entrepreneur who also runs the hedge fund High-Flyer—DeepSeek is now a major AI player. Its models are
Here's my take on where AI is headed and why subject matter experts, not ML engineers, will be the ones building the next generation of AI applications. Most of this comes from the podcast above. The Big Picture One of the main predictions I base a lot of
My technically curious dad just asked if Deepseek is a game changer. It's a fair question that gets at the heart of what's happening in AI right now. What's Really Going On Deepseek is good. They've built the best open-source model out