We've seen so many folks struggle with prompt optimization. What to change and why? Now, w/ OSS Zenbase all you need is example data and Zenbase will create an optimized prompt for you. 🔥

Day 1 support for llama 3.1 via Fireworks AI in PareaAI's playground! 🧨🦙

New Wallpaper.

Some tactics to build LLM apps consisting of multiple components: - test every sub-step to minimize cascading failures - reference-based evaluation of sub-components using synthetic data - cache LLM calls to quickly iterate on independent components More details incl. synthetic

How do you detect unreliable behavior of your LLM app? Recently, we talked to the team at Sixfold and they shared with us a simple, yet powerful way to assess the reliability of their LLM app using PareaAI. More about how they test their risk assessment AI solution for

.PareaAI also looks like a good LLM monitoring tool and is open source

Literally why we built PareaAI

So what happens when we crack both quantum computing and AGI?

It’s crazy that a cars power is still defined by horse power. Like I have no mental model for the strength of a horse. In 18th century this probably made great sense,

So good.

See so many open source AI repos written in typescript, for example all the CLIs are. Very interesting, is full stack typescript going to become the default GenAI stack ? Or all the good stuff still built with Python and just not open sourced?