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Learn how to fine-tune OpenAI GPT-4 using your own data – with steps for data preparation, training, evaluation, and deployment to create customized LLM deployments for your specific applications.
Read moreDiscover the streamlined process of fine-tuning OpenAI GPT-3.5 Turbo with Klu.ai. Learn how to easily prepare your data, train, evaluate, and deploy your custom LLM with our comprehensive guide.
Read moreThis comprehensive guide provides developers, product managers, and AI Teams with a structured framework for optimizing large language model (LLM) applications to achieve reliable performance. It explores techniques like prompt engineering, retrieval-augmented generation, and fine-tuning to establish strong baselines, fill knowledge gaps, and boost consistency. The goal is to systematically evaluate and improve LLM apps to deliver delightful generative experiences.
Read moreIn this article, we provide a comparative analysis between Google's Gemini Pro and OpenAI's GPT-3.5, evaluating their performance, scalability, and cost-effectiveness.
Read moreLessons learned from the rise of AI Teams in 2023.
Read moreMaster the art and science of crafting prompts that precisely convey context and intent to transform how LLM systems interpret and respond to queries.
Read moreIn this post, we dive into Retool's State of AI 2023 report, analyzing key findings from a survey of over 1,500 tech professionals. We explore current AI usage, tooling preferences, and future outlooks, providing insights into how generative AI tools are being leveraged today and the evolving expectations.
Read moreThe Klu team evaluates the new functionality rolled out by OpenAI this week.
Read moreAs Azure OpenAI continues gaining traction for its speed and startup credits, understanding the key differences from the public OpenAI API is key.
Read moreIn 2023, Generative AI models like ChatGPT dominated headlines and sparked calls for regulation, while risks from physical AI systems like autonomous vehicles and deepfakes went largely overlooked.
Read moreStartups need to work smart and efficient. This blog post explores the top AI tools we use daily that help streamline operations, create content, and automate tasks.
Read moreBreak down common AI misconceptions around understanding, controlling, and aligning large language models, highlighting techniques like RLHF that shape model outputs to human preferences.
Read moreBuild your first Klu Action with the Python SDK in 5 Steps
Read moreBuild your first Klu Action with the Typescript SDK in 5 Steps
Read moreExpanding our global deployment of OpenAI GPT-4 across 12 regions, emphasizing redundancy, load scaling, and regional privacy compliance.
Read moreOpenAI GPT-4 Model Card
Read moreLearn how to fine-tune OpenAI GPT-3.5 Turbo using your own data with steps for data preparation, training, evaluation, and deployment to create customized LLM deployments for your specific applications.
Read morePrompt Evaluation and Collaboration
Read moreDiscover the top 5 open-source large language models in 2023 that developers can leverage, including LLaMA, Vicuna, Falcon, MPT, and StableLM. Compare model details like architecture, data, metrics, customization, community support and more to determine the best fit for your NLP projects.
Read moreAn analysis of the best AI products released in 2022-2023, their impact on the ecosystem, and what this means for the future.
Read moreOpen source LLMs like Gemma 2, Llama 3.1, and Command R+ are bringing advanced AI capabilities into the public domain. This guide explores the best open source LLMs and variants for capabilities like chat, reasoning, and coding while outlining options to test models online or run them locally and in production.
Read moreIn this article, we'll dive into the current state of frontier models, exploring their capabilities, limitations, and the gap between benchmarks and real-world performance. We'll introduce QUAKE, a new benchmark designed to evaluate LLMs on practical knowledge worker tasks, and share our findings on model performance across various domains.
Read moreMultimodal AI Models are transforming the landscape of artificial intelligence by enabling systems to process and understand multiple data types simultaneously, much like human cognition. This blog post dives into the power and potential of these models, exploring notable examples like GPT-4-V, LLava 1.5, and Fuyu-8B. We will discuss the challenges and solutions in multimodal AI integration, and explore their real-life applications and future implications. Join us as we unravel the future of artificial intelligence through the lens of multimodal AI models.
Read moreLearn how to develop an AI vision, foster a supportive culture, build robust data pipelines, upgrade infrastructure, embed ethical AI safeguards, and track AI success through actionable strategies.
Read moreStartups need to work smart and efficient. This blog post explores the top AI tools we use daily that help streamline operations, create content, and automate tasks.
Read moreCollaborate with your team on reliable Generative AI features.
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