Skip to content
A4 civilengineering
  • Home
  • About Us
  • Education
  • Community
  • Thought
  • Ongoing Happenings
  • Contact Us
Menu Close

Blog

Home » Ongoing Happenings » Continuum Industries Chooses Iterative to Optimize Civil Infrastructure Design with Evolutionary Computing
Continuum Industries Chooses Iterative to Optimize Civil Infrastructure Design with Evolutionary Computing
Iterative reduced Continuum’s setup and runtime from 48 hours to just three using DVC and CML

SAN FRANCISCO, Jan. 18, 2022 (GLOBE NEWSWIRE) — Iterative, the MLOps company dedicated to streamlining the workflow of data scientists and machine learning (ML) engineers, today announced Continuum Industries, which provides AI tools for engineering professionals to rapidly design linear infrastructure projects, has chosen Iterative-backed open source projects DVC and CML to optimize evolutionary computing optimization workflows and reduce time to market.

Continuum Industries works with large amounts of geospatial data with evolutionary computing algorithms to optimize the design of infrastructure like railways and roads. While Continuum Industries do not use machine learning algorithms, they face a number of the same problems that MLOps aims to resolve. They were looking for a way to have that data sync with the code and be versioned together. After considering a custom build using basic ML tools offered by Amazon Web Services (AWS), Continuum chose Iterative tools for their Optioneer product because they allowed it the freedom to freely integrate various ML tools from other vendors into their workflows (like GitHub Actions for CI/CD in training their models), and begin working on test cases immediately.

“With Iterative, we were able to get started right away without having to maintain it ourselves,” said Ivan Chan, AI engineer at Continuum Industries. “Given the incredible time savings it has already provided, we are planning on expanding our use of DVC to also set up our development and testing environment also to experiment versioning and more.”

With Iterative, Continuum Industries is now able to version everything beyond code, including data, and ML pipelines, and experiments, with DVC, run frequent algorithm tests with reproducible results through Continuous Machine Learning (CML), as well as slash support time. The developer time spent on maintaining Continuum’s suite of algorithm tests has been reduced from five hours every three weeks down to virtually no time at all. Due to the time savings, the team can invest more resources on model development and optimization.

Read More
www.yahoo.com

Read more articles

Previous PostPartnership Taps AIoT for Intelligent Wi-Fi Sensing
Next PostSouth Africa funds research chair in ‘smart mobility’

You Might Also Like

Read more about the article Panasonic Toughbook Supports Swiss Engineering Company In Move To Paperless Construction Site

Panasonic Toughbook Supports Swiss Engineering Company In Move To Paperless Construction Site

November 1, 2021
Read more about the article UL and the Telecommunications Industry Association Announce SPIRE™ Smart Building Verifications Now Available

UL and the Telecommunications Industry Association Announce SPIRE™ Smart Building Verifications Now Available

November 12, 2021
Read more about the article Cooper Carry-Designed SMART Building Fosters Exploration in Unmanned Machinery in St. Mary’s

Cooper Carry-Designed SMART Building Fosters Exploration in Unmanned Machinery in St. Mary’s

March 11, 2022

Archives

  • March 2022
  • February 2022
  • January 2022
  • December 2021
  • November 2021
  • October 2021
  • September 2021
  • August 2021
  • July 2021

Categories

  • 3D Printing
  • Air Quality
  • Architecture
  • Automation
  • BIM
  • Civil Software
  • Computer Vision
  • Constrcution Site
  • Digital Twin
  • Disaster
  • Earthquake
  • Edu Resource
  • Environmental
  • FreeCourse
  • Geotechnical Engineering
  • GIS
  • Industry News
  • Intelligent Transportation System
  • IOT
  • Market Analysis
  • Project Management
  • Remote Sensing
  • Sensors
  • Smart City
  • Smart Home
  • Smart Home/Building
  • Smart Materials
  • Structural Engineering
  • Structural Health Monitoring
  • Transportation
  • Uncategorized
  • Urban Planning

Recent Posts

  • Kontrol Technologies is in the thick of the commercial building upgrade supercycle
  • I-Bhd, China Mobile team up to build Malaysia’s first green smart building
  • FedEx launches AI-powered sorting robot to drive smart logistics
  • 8 trends shaping cities in 2022
  • DC joins growing list of cities requiring new buildings to include EV parking
A4 civilengineering
©2021 Privacy policy
  • Home
  • About Us
  • Education
  • Community
  • Thought
  • Ongoing Happenings
  • Contact Us

Enjoying the contents?

Subscribe to our weekly newsletter