Jensen and Chris

Pieter Abbeel, a professor at the University of California, Berkeley, and cofounder of Covariant.ai, an AI company, has pioneered the idea that deep learning could be the key to bridging that gap: creating robots that can learn how to move through the world more fluidly and naturally. ” Teaching robots new skills is similar to taking classes in college, Abbeel explained on the latest episode of the AI Podcast. While college courses may not immediately qualify a student for a job, the classes are still important in helping students develop fundamental skills they can apply in all kinds of situations. The research cycle is a lot about just trying things people haven’t tried before and trying them quickly and understanding how to simplify things.

It’s a job tailor-made for AI, and Lucidyne has jumped in with both feet by building a cutting-edge scanning system for lumber mills that’s powered by GPU-enabled deep learning. It then applies a deep learning model trained on a combination of NVIDIA GPUs, with a dataset of hundreds of thousands of scanned boards across 16 tree species, all of which have been classified by a team of lumber-grading experts. After scanning a 20-foot board, Lucidyne’s system might determine that the best cut will remove a 2-foot defective section near the center, leaving two 8-foot grade 1 and 2 sections on either side, and an additional 2-foot section of trim, which might be sold to a sawdust manufacturer. “Going to deep learning has allowed us to be a lot more accurate, and our customers produce packs that are 2 percent below or above grade,” said Dan Robin, Lucidyne’s software engineering manager.

In a talk at the GPU Technology Conference last month, two of the organization’s AI developers shared how it’s adopting deep learning for a variety of applications — from prior authorization of medical procedures to directing phone calls. The datasets required to solve these problems are enormous,” said Dima Rekesh, senior distinguished engineer at Optum, the health services platform of UnitedHealth Group. “AI solutions actually impact not just the operational costs for our company, but also patient services,” said Julie Zhu, chief data scientist and distinguished engineer at Optum. By implementing AI in its call system, UnitedHealth Group can use natural language processing models to understand what callers are looking for and answer automatically, or route them to the right department or service representative.

The startup’s GPU-driven tree analytics platform relies on image recognition algorithms, sensors, drones and an app for collecting data on the ground. Farmers need to move quickly to replace trees hit by citrus greening to blunt the advance of the disease throughout orchards. The company’s analytics platform enables customers to track the performance of their farms, as well as get the best results from their use of fertilizer, pesticides, water and labor. The startup taps NVIDIA GPUs on Google Cloud Platform to train its image recognition algorithms on thousands of images of fruit.