Large language models like ChatGPT are revolutionizing how we develop software. But they are also prone to inaccurate results, factual errors, or inappropriate content. Our tools help development teams prototype, evaluate, understand, and improve the output of text generation applications such as question answering, summarization, code generation, and chat, so that these applications can be deployed to real users with confidence.
Today, there is so much information about AI online, and even if you are interested in building an AI-driven app or product it is often difficult to know where to start. To solve this problem we have created the Inspired AI Guide, which provides a birds-eye view of the whole process of developing a user-facing AI system, from conceptualization to deployment. The content is curated by Inspired Cognition’s team of AI experts to ensure that it is comprehensive, up-to-date, and reliable.
At Inspired Cognition, we’re on a mission to make it easy to build reliable AI-driven systems. To do so, are building the next generation of tools that allow AI developers to deploy their systems with confidence. Today, we are happy to announce Critique, a new tool in the arsenal for reliable AI. Critique is a quality control tool that allows AI developers using generative AI systems (systems that generate outputs like text and images) to assess whether the outputs produced by these systems are high-quality and trustworthy.
Artificial Intelligence (AI) is becoming as much of a force for world progress as software. However, unlike traditional software engineering, AI engineering introduces a variety of new challenges. Specifically, developing AI systems involves a large amount of design choices with uncertain implications.