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Achieving AI development at scale ft. Luis Ceze of OctoAI

In this episode, Rob is joined by Luis Ceze, CEO of OctoAI and a distinguished professor of computer science at the University of Washington. Together, they unpack the surge of interest in AI, attributing it to the convergence of factors like the unprecedented availability of data thanks to the internet boom and the accessibility of powerful computing resources.

Build and test LLM applications with AIConfig and CircleCI

The power of LLMs to solve real-world problems is undeniable, but unfortunately, in some cases, only theoretical. What’s stopping us from getting the most out of OpenAI’s text completion capabilities in production apps? One common problem is the inability to confidently guard against bad outputs in production the way we’re used to doing with non-AI test suites. Let’s go one step deeper. There is no equivalent of code coverage for an LLM.

The testing pyramid: Strategic software testing for Agile teams

The testing pyramid model untangles the complexity of software testing by fitting it into an efficient hierarchical structure. By focusing on unit tests at the base, integration tests in the middle, and end-to-end tests at the top, the testing pyramid ensures that most testing efforts are spent on tests that are fast, reliable, and easy to maintain. This allows for quicker iterations, improved code quality, and more stable releases.

Integrating AI and DevOps for Software Development Teams

For a long time, the domains of Machine Learning and AI on one side, and software development on the other side, were separate kingdoms. Sometimes, they touched, and something magical would happen. But more often, things didn’t really work out. They faced challenges stemming from a lack of mutual understanding, shared language, and compatible tools. With the meteoric rise and increased accessibility of powerful generative AI and LLMs, the need for collaboration to achieve real-world engineering and customer value has never been more vital.

LLM hallucinations: How to detect and prevent them with CI

An LLM hallucination occurs when a large language model (LLM) generates a response that is either factually incorrect, nonsensical, or disconnected from the input prompt. Hallucinations are a byproduct of the probabilistic nature of language models, which generate responses based on patterns learned from vast datasets rather than factual understanding.

What is microservices architecture?

Microservices architecture is a method of developing software systems that structures an application as a collection of loosely coupled services, each focusing on a single function or business capability. Each service operates within a discrete, confined context, communicating with other services through well-defined interfaces — typically APIs.

Test-driven development (TDD) explained

Test-driven development (TDD) is a software development process that involves writing tests for your code before you write the code. This approach has transformed the development methodology around testing. While the traditional waterfall model of software development was linear, with testing occurring near the end of one long timeline, TDD makes testing an ongoing, iterative process.