A fruit sorting robot built by a British consulting firm may not sound like a riveting leap forward. In fact, it's one of the clearest indications yet that industrial automation is on the verge of a big change and that we may be entering a new industrial revolution. Later this month, Cambridge Consultants will demonstrate its fruit sorting robot at the AgriTechnica show in Germany. During the demonstration, fruit will be stacked randomly in a bowl. The robot will use machine vision and smart software to identify the piece on top.
AI might be a hot topic but you'll still need to justify those projects. When I was eight, I got lost in the woods on a camping trip with my mom. Rangers eventually found me and hiked me out, which is actually kind of miraculous. I was a couple miles from where they assumed I'd be, trudging haplessly through a remote backwoods area on unmarked terrain. Every year hundreds of thousand people get lost in the wild worldwide.
AI might be a hot topic but you'll still need to justify those projects. The Toyota Research Institute (TRI) just announced its technology leadership team at CES. In November Toyota announced an initial five-year, $1 billion investment in TRI, which will be a research and development enterprise designed to bridge the gap between fundamental research in robotics and artificial intelligence and product development. In other words, the mandate is to develop all the cool AI stuff happening in labs and DARPA-backed research projects and bring it to market. Comparisons have been drawn to famous industrial laboratories like Bell Labs and PARC, which are jointly responsible for an impressive chunk of silicon-age advances.
AI might be a hot topic but you'll still need to justify those projects. In partnership with Yamaha, robotics developer SRI has created a humanoid that can ride an unmodified motorcycle. Motorcycle racing is about the most thrilling lesson in physics and material science imaginable. In order to turn a motorcycle, riders need to lean. Thanks to some truly extraordinary tires, riders flirt with the terminal edge of physics at screaming speeds during race laps, leaning their bikes far enough to scrape knees, shoulders, and elbows.
A scanning robot from 4D Retail Technology can scan an entire grocery store in about an hour. AI might be a hot topic but you'll still need to justify those projects. The reason you're hearing more about robots these days has a lot to do with non-robotic technologies. After all, for the last fifty years mechanical engineers have been able to make some pretty snazzy machines that move on their own. It's only with the rise of complementary sensor and computing technologies that robots are starting to show their true usefulness outside of factories.
SAS on Tuesday marked the general release of SAS Factory Miner, an automated tool that uses machine learning techniques to develop, test and identify hundreds of best-fit predictive models within minutes. Announced last month, Factory Miner promises better, segment-specific predictive performance, and it also goes a long way toward easing the analytic talent shortage. See how the cloud is disrupting traditional operating models for IT departments and entire organizations. SAS Factory Miner is a response to all of these imperatives. It helps companies with find-grained segmentation by automating model building across hundreds of segments and, potentially, thousands of sub-segments.
Carnegie Mellon University, working in conjunction with researchers at Johns Hopkins, Harvard, and other institutions, plans to reverse engineer the human brain. Let's just hope Igor doesn't grab the one marked "Abby Normal." CMU announced this week that it's embarking on a five-year, $12M research effort to unlock the secrets of neural circuitry and the brain's learning methods. Researchers will use these insights to make computers think more like humans. AI might be a hot topic but you'll still need to justify those projects.
Graphics chipmaker Nvidia easily topped second quarter earnings targets Thursday after the bell. The company posted record-revenue for the quarter, and once again credits strong sales of its GPUs and deep learning technology for the boost on its balance sheet. See how the cloud is disrupting traditional operating models for IT departments and entire organizations. Nvidia co-founder and CEO Jen-Hsun Huang said the convergence of graphics, computer vision and artificial intelligence is fueling growth across the company's specialized platforms, including gaming, pro visualization, datacenter and automotive. "We are more excited than ever about the impact of deep learning and AI, which will touch every industry and market.
Nvidia CEO Jen-Hsun Huang said the partnership illustrates the commitment both companies have made to advancing the use-cases of AI. Nvidia and Chinese search engine giant Baidu are teaming up to develop a cloud-based platform for use in artificially intelligent, self-driving cars. See how the cloud is disrupting traditional operating models for IT departments and entire organizations. The partnership combines Nvidia's self-driving computing platform with Baidu's cloud and mapping technology to develop an algorithm-based operating system capable of powering complex navigation systems in autonomous vehicles. The open platform will be available for branded car OEM consumer vehicle offerings, as well as fleets of driverless commercial vehicles.
In 1961, a robotic arm nicknamed Unimate joined the General Motors assembly line to perform basic welding tasks that were unpleasant and particularly dangerous for humans. The 4000-pound, six-axis robot ran off of magnetic tape. "If you start with Unimate," says Melonee Wise, CEO of Fetch Robotics, an industrial robotics startup that received a $20M investment from SoftBank in June, "you see that industrial robots were developed and entered the workforce based on a very specific way of thinking." Though subsequent robots would achieve greater dexterity, strength, and speed, Unimate served as the proto-model. For the next half century most industrial robots were caged-off behemoths that handled repeatable tasks adroitly but required costly physical reconfiguration to take on new tasks or change operating environments.