NLP Logix has joined the NVIDIA Metropolis Partner Program, which provides the hardware and software to prototype computer vision models in less than half the time of traditional environments.
NLP Logix, a leading machine learning and automation solution provider, announced it has joined the NVIDIA Metropolis Partner Program, a program designed to nurture and bring to market a new generation of vision AI solutions to make processes more efficient.
One of the challenging barriers facing any artificial intelligence/machine learning company is the ability to quickly gather large and accurate enough data sets to train a computer to do a task normally accomplished by a human. For example, if you wanted to train a computer to review hours upon hours of video, and accurately identify specific items such as a stop sign, light post, item in a crowd etc., you would have to gather the data, review it and note (annotate) enough positive examples and then feed the results through specialized hardware to be able to train the computer to accurately identify the items in future video.
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“The LaunchPad environment gives us the capability to quickly iterate with the client and tell them if the probability of success is high or low that the model will work, and a much more accurate estimate on the level of effort to get the model from lab to production.” – Ben Webster, NLP Logix
“This computer vision algorithm training pipeline has not changed much over the past ten plus years that we have been doing this at NLP Logix,” said Matt Berseth, Co-Founder and Chief Information Officer. “It has always been very time consuming and expensive to gather and annotate enough images so that we can confidently put the models into our customers’ production systems, which we have done hundreds of times for dozens of customers.”
This time-consuming activity has now been greatly reduced by NLP Logix utilizing NVIDIA LaunchPad that offers a free GPU-powered environment enabling teams to quickly prototype and train computer vision models in less than half the time of traditional techniques. This allows companies to test the feasibility of putting a computer vision model into production at a much lower cost point by reducing the amount of data to train a first-pass model.
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“Many of our customers want to test the feasibility of using computer vision to solve a business problem, but do not have the budget to fund a full end-to-end model,” said Ben Webster, Modeling and Analytics Lead at NLP Logix. “The LaunchPad environment gives us the capability to quickly iterate with the client and tell them if the probability of success is high or low that the model will work, and a much more accurate estimate on the level of effort to get the model from lab to production.”
Other technologies include NVIDIA pre-trained models and TAO Toolkit in the solutions that we provide to our clients. NLP Logix has been using NVIDIA GPU-accelerated technologies to automate business processes for almost ten years and is excited to be expanding its capabilities through its participation in the Metropolis program.
