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willow.ai use case

Helping Consultants Apply Modern Methods To Industrial Problems

The Company

Willows.ai is a Montreal-based team composed of machine learning, AI, and software experts that develop and deliver full-stack AI solutions for the manufacturing industry. Manufacturing has become a proving ground to leverage the benefits of machine learning, where companies leverage technology to optimize visual systems to monitor and increase safety, track progress to deliver real-time status, and reduce common process-driven waste. With expertise in computer vision and building robust, explainable machine learning solutions, Willows.ai helps manufacturers apply the latest research to their business problems. 

 

The Problem

Prior to discovering the Grid platform, the Willows.ai team managed a complex system to compare and analyze the results of their machine learning operations. This complexity often led to duplication of work and ballooning computational costs. 

Willows knew that if they wanted to scale, they needed to not waste precious time worrying about cloud infrastructure. They wanted a platform that freed up resource time and delivered results faster for them and their clients. 

 

Solution 

The Willows team discovered Grid.ai through the open source PyTorch Lightning community. The Grid platform, developed by the same team behind PyTorch Lightning, provides Willows with the capabilities they need to manage scalable ML workflows. “We were able to solve our need to deliver more value by providing massive scale training to our clients,” explained Dr. Andrew Marble. It is extremely valuable for us to manage and see all the experiments that we create within a single dashboard view.” The Grid platform provides this unified view for managing run metrics, logs, and artifacts.

 

grid platform

 

What Willows loves most about Grid is its Hyperparameter Optimization functionality that enables them to scale variations of their models in parallel without needing to change their code or take on external dependencies. 

 

“Being able to parameterize and add parameters to your model is where the real value [for Willows] is at. Grid’s Hyperparameter Sweeps are the most interesting feature to me”, Dr. Andrew Marble, Principal, Willows.ai.

 

Grid’s ability to manage interruptible compute such as spot instances through a click of a button reduced training costs for Willow.ai. Receiving real-time estimates before, during, and after, running experiments with Grid provides Willows with the transparency it needs to manage costs.

willows runs

Getting Started With Grid.ai

Just as Grid has helped Willows.ai scale and manage their deep learning model development, you can as well. To take advantage of Grid, get started with a free community tier account today here. Also, explore our documentation and join our Slack community to learn more about what the Grid platform can do for you.

 

Get to know more about Willows.ai, and connect with Dr. Andrew Marble via email at andrew@willows.ai