How It's Made
How It's Made
Building for Balance
How we developed a unified marketplace balancing engine with machine learning and optimization. Written by Trace Levinson, Senior Machine Learning Engineer. The Instacart Marketplace team is deeply focused on producing both timely, high-quality deliveries for our customers and meaningful earning opportunities for shoppers. To consistently do both of these well, it is critical for us to maintain a healthy balance between supply and demand on…
Apr 12, 2024
How It's Made
Building for Balance
How we developed a unified marketplace balancing engine with machine learning and optimization. Written by Trace Levinson, Senior Machine Learning Engineer. The Instacart Marketplace team is deeply focused on producing both timely, high-quality deliveries for…
Apr 12, 2024
How It's Made
One Model to Serve Them All: How Instacart deployed a single Deep Learning pCTR model for multiple surfaces with improved operations and performance along the way
Authors: Cheng Jia, Peng Qi, Joseph Haraldson, Adway Dhillon, Qiao Jiang, Sharath Rao Introduction Instacart Ads and Ranking Models At Instacart Ads, our focus lies in delivering the utmost relevance in advertisements to our customers, facilitating novel product discovery and enhancing…
Dec 19, 2023
How It's Made
Monte Carlo, Puppetry and Laughter: The Unexpected Joys of Prompt Engineering
Author: Ben Bader The universe of the current Large Language Models (LLMs) engineering is electrifying, to say the least. The industry has been on fire with change since the launch of ChatGPT in November of…
Dec 19, 2023
How It's Made
Introducing Griffin 2.0: Instacart’s Next-Gen ML Platform
Authors: Rajpal Paryani, Han Li, Sahil Khanna, Walter Tuholski Background Griffin is Instacart’s Machine Learning (ML) platform, designed to enhance and standardize the process of developing and deploying ML applications. It significantly accelerated ML adoption at Instacart by tripling…
Nov 22, 2023
How It's Made
Unveiling the Core of Instacart’s Griffin 2.0: A Deep Dive into the Machine Learning Training Platform
Authors: Han Li, Sahil Khanna, Jocelyn De La Rosa, Moping Dou, Sharad Gupta, Chenyang Yu and Rajpal Paryani Background About a year ago, we introduced the first version of Griffin, Instacart’s first ML Platform, detailing its development and support for end-to-end ML in…
Nov 22, 2023
How It's Made
The Economics Team at Instacart
Tilman Drerup, Levi Boxell, and Robert Fletcher Tech firms are increasingly choosing to hire graduates from PhD programs in economics [1, 2, 3]. In this blog post, we present the economics team at Instacart and our take…
Nov 22, 2023
How It's Made
Scaling Productivity with Ava — Instacart’s Internal AI Assistant
By Zain Adil, Kevin Lei and Ada Cohen Over the past few months, we’ve been building an internal AI assistant powered by OpenAI’s GPT-4 and GPT-3.5 models called Ava. Ava has seen accelerated adoption at…
Sep 7, 2023
How It's Made
Instacart’s Item Availability Architecture: Solving for scale and consistency
By Michael Prescott This blog post is the last segment in a three-part series that outlines our innovative approach to overcoming inventory challenges, delving into the application of product design, machine learning, and engineering technology…
Sep 6, 2023
How It's Made
Adopting dbt as the Data Transformation Tool at Instacart
By James Zheng At Instacart, datasets are transformed for use in analytics, experimentation, machine learning, and retailer reporting. We use these datasets to make key business decisions that provide better experiences for our customers and…
Aug 17, 2023