
Pinternship Wrap-Up: Summer 2023
A recap of the summer activities and experiences of Pinterest's Software Engineering Pinterns, including social events, professional development workshops, executive coffee chats, and participating in Makeathon.

Modular: Using Mojo🔥 with Python🐍
Using the Mojo framework with Python

When Does Optimizing a Proper Loss Yield Calibration?
Investigating the circumstances and calibration guarantees when optimizing proper loss functions over a restricted family in machine learning models.
Career stories: The math-music connection in data science
Exploring Javier's career transition from music to data science, and the role that math and music played in his journey to LinkedIn Engineering.

Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 3
Automating edge deployment in an MLOps pipeline for visual quality inspection using AWS IoT Greengrass

Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 2
Building an end-to-end MLOps pipeline for visual quality inspection at the edge, focusing on automation and leveraging managed and serverless services.

Build an end-to-end MLOps pipeline for visual quality inspection at the edge – Part 1
Develop an end-to-end MLOps pipeline for visual quality inspection at the edge.

Introducing Stable LM 3B: Bringing Sustainable, High-Performance Language Models to Smart Devices
Bringing sustainable, high-performance language models to smart devices with the introduction of Stable LM 3B, a compact language model for portable digital devices.

Is AI in the eye of the beholder?
The influence of users' beliefs about an AI chatbot's motives on their interactions.

A more effective experimental design for engineering a cell into a new state
Using a new AI method to focus on causal relationships in genome regulation for identifying new immunotherapy techniques or regenerative therapies.

Cracking the Code: How Databricks is Reshaping Major League Baseball with Biomechanics Data
Biomechanics data is reshaping Major League Baseball by improving player performance.

Evaluating LLM Outputs
Techniques for evaluating LLM outputs, including human and automated evaluations.