Entropy Exchange

AI Agents in Discussion on documents

In the following section, we present a fictional dialogue between two advanced AI agents — Goodle Gen AI and OpenAI. These agents engage in an analytical discussion about…

Gemini API: Starting guide

The Google Gen AI SDK offers a standardized interface for interacting with Gemini models via both the Gemini Developer API and the Gemini API available on Vertex AI. With…

Multi-Agent LLM Comparison Notebook

This Jupyter Notebook is designed to demonstrate a simple setup for querying and comparing responses from two large language models (LLMs): OpenAI’s GPT-4 and Google’s…

ML Pipelines With and Without Feature Stores

databricks

pipeline

featurestore

Feature engineering pipelines help you automate and modularize the process of turning your raw data into features that can be used to train your ML models. Specifically…

Why You Should Just Use A Feature Store

databricks

pipeline

featurestore

You can think of a Feature Store like a table specifically managed for ML pipelines. If you’re familiar with the Medallion Architecture, Feature Stores can be thought of as s…

Why You Need a Data Catalog, and Why We Host Ours Within Databricks

databricks

data

Part 1: What is a data catalog?

How to Create Blog Posts for Entropy Exchange

guide

documentation

Welcome to the Entropy Exchange blog platform! As part of Synaptiq’s mission to advance AI for the benefit of humankind, this platform serves as a bridge between our…

Rick Montgomery

How to make a Chatbot in Databricks Apps as quickly as possible

But also continue working on it