In a recent article, Boston Consulting Group (BCG) points out that spending on robots worldwide is expected to grow from $15 billion in 2010 to $67 billion in 2025. The $52 billion increase in 15 years is a compounded annual growth rate of 10%. They attribute this growth to a convergence of falling hardware prices, performance improvements, and easier application software combined with increased flexibility and finesse. This results in robots being useful in a much broader set of applications than you might traditionally think of – such as automotive assembly and welding.Read More >>
Clint Reiser points out in the linked article that a new revolution in supply chain analytics is occurring. There is new level of data detail, it’s coming at us faster, providing bigger patterns and better insights.
The detail isn’t just point-of-sale information, customer buying patterns, or fleet telematics. From Universal’s perspective, the combining of machine learning and machine vision into robust automated solutions for material handling processes previously thought as random is a unique source of this data.Read More >>
As noted by ImpactLab.net, Pew Research questioned 1,896 experts about whether artificial intelligence (AI) applications and robots will have displaced more jobs than they have created by 2025. Fifty-two percent think more jobs will be created, 48% think more jobs will be displaced. So, its up for grabs as to who is right.
Note that if history repeats itself, technology has always been a job creator – not a job destroyer. However, the type of jobs, the skills required, and even entire industries will certainly go through massive change as part of the transition. As Vint Cerf, vice president for Google stated, “Historically, technology has created more jobs than it destroys and there is no reason to think otherwise in this case. Someone has to make and service all these advanced devices.”Read More >>
Note from Bob Ferrari’s Post on Aug 7, 2014 entitled Permanent Shifts in Consumer Shopping Trends Have Supply Chain Implications. He comments on a quote in the article: Online Customer Fulfillment, Retail Supply Chain, Supply Chain Business Process that cites the following from Shopper-Trak: “Online sales have grown more than 15% every quarter for the past two years and are having a big impact on the way many companies are looking at their brick-and-mortar stores…. Rather than networks of distribution centers and fleets supporting individual physical stores, the new emphasis will be on high-volume online fulfillment supported by combinations of fulfillment centers and multi-purpose retail outlets.”Read More >>
Artificial Intelligence / 12.08.2014
Artificial intelligence is taking yet another step forward. Here’s an update on a new effort by those who helped create Apple’s Siri. It’s consumer friendly, and teaches itself as it goes. Sounds familiar… 🙂Read More >>
Check out this interesting article on advances in deep learning for robots: Robots Helped Inspire Deep Learning and Might Become Its Killer App?
It’s worth comparing/contrasting between deep learning techniques and Neocortex. Neocortex is Universal Robotics’ patented machine learning platform, based on a seven-year development effort between NASA and Vanderbilt University. Even though the technology is currently employed on Robonaut 2 on the International Space Station, Universal’s focus with Neocortex is material handling tasks. By learning to recognize new objects or recognize previously seen objects that have changed, Neocortex machine intelligence brings flexibility to material handling automation.Read More >>
Check out this video showing Universal Robotics Neocortex – a patented next-generation machine intelligence software platform. It is guiding a robot to pick up a wide range of parts, providing flexible automation.
Traditionally, flexibility consisted of manually reconfiguring mechanical systems and sensors, and manually re-engineering algorithms to accommodate new parts. Neocortex’s machine learning can automatically handle a wide range of changing parts, reducing the need for manual changeovers. In the past, when a new part was introduced, even if the robot could pick up the new part, the robotic work cell would still require changes in fixturing, sensors, machine vision algorithms, and machine control.
In this video, see Neocortex guide the robot to handle various parts. Also shown is a demonstration of the simple training method for those occasional times an operator needs to teach Neocortex something new – a process that takes less than two minutes.Read More >>
We’ve recently discussed how the Microsoft Kinect can be used in robotic mobile manipulation. See above a video showing what is, to our knowledge, the first commercial integration of the Kinect with an industrial robot. Signal from standard webcams is also used. A software from Universal Robotics crunches the data to obtain a 3D representation of the scene. The application shown is the palletizing of randomly-placed boxes with Motoman robots.
Seeing consumer priced sensor entering into the industrial arena is very exciting, as long as the integration can prove to be robust enough.Read More >>