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Data Insights
Explore your unstructured data and power buisness and AI intelligence.
NLU Design
Train, evaluate and continuously optimize custom NLU models using unstructured data.
NLG Design
Guarantee prompt performance and observe LLM input/output at scale (beta).
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Google Cloud and Human First make it design, test , and launch scalable AI prompts and models you can trust using your unstructured data.
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Data Insights
Explore your unstructured data using NLU and prompts
NLU Design
Train, evaluate and continuously improve custom NLU
models using unstructured data
NLG Design
Guarantee prompt performance, and observe
LLM input/output data at scale (beta)
LLM fine-tuning (coming soon)
Prepare labeled data to fine-tune LLMs
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Add the intersection of NLU, LLMs and natural language data

RAG Evaluation

Retrieval Augmented Generation (RAG) is a very popular framework or class of LLM Application. The basic principle of RAG is to leverage external data sources to give LLMs contextual reference. In the recent past, I wrote much on different RAG approaches and pipelines. But how can we evaluate, measure and quantify the performance of a RAG pipeline?

COBUS GREYLING
5 min read
Tutorial

Importing Conversational Data from Rasa to HumanFirst

This article explains the process of importing your conversational data from Rasa to HumanFirst.

MATHIEU RENE
1 MIN READ
Tutorial

How to bootstrap and continuously improve Botpress projects with HumanFirst Studio and real data

In this article we’ll see how to use available datasets or your own in order to create a Botpress bot from scratch without having to come up with every single training phrase.

MATHIEU RENE
7 MIN READ
Tutorial

Using HumanFirst Studio to bootstrap Rasa projects from real data

HumanFirst Studio was built in order to manage and continuously improve the training data of large conversational assistants, identifying valuable training data from existing sources that are often available but

MATHIEU RENE
6 MIN READ
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