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Studio LLM is Galileo’s smarter solution for building and evaluating LLM apps

LLM Studio is Galileo’s latest offering for LLM training, evaluation, and monitoring. Consisting of three modules responding to the most common problems faced by developers, Galileo aims to make LLM Studio the all-in-one solution for model evaluation.

Dmitry Spodarets profile image
by Dmitry Spodarets
Studio LLM is Galileo’s smarter solution for building and evaluating LLM apps

Galileo, the company with the mission “to create the world’s best AI developer platform for unstructured data”, has launched Studio LLM to simplify the process of managing and evaluating the colossal amounts of data needed to train and maintain large language models. Studio LLM responds to the biggest challenges faced by LLM developers which were identified by Galileo:

  1. Replacing manual human analysis as standard procedure when evaluating LLMs.
  2. Streamlining and simplifying the experimentation process: manually coming up with every variation and permutation of a particular prompt is untenable and non-efficient.
  3. Solving or at least continuously monitoring LLMs for problematic hallucinations.

Each of these challenges is tackled by one of the three modules comprising LLM Studio: Prompt, Fine-Tune, and Monitor.

Prompt simplifies the prompt engineering process of finding optimal combinations of templates, models, and parameters. It allows collaboration with automatic version controls and evaluation with Galileo’s suite of metrics. Fine-Tune automatically detects problematic gaps in the data set. Finally, Monitor offers a suite of observability tools and evaluation metrics meant for real-time performance monitoring. The three modules are meant to be used as a single ecosystem, paired with industry-standard and Galileo’s suite of metrics, to mitigate the risk of MLL hallucinations, one of the most common and urgent obstacles to overcome for generative AI to gain the trust of end users.

Read more about LLM Studio here, and learn all about Galileo’s introductory webinar, taking place on October 4, here.

Dmitry Spodarets profile image
by Dmitry Spodarets

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