In the last few days we’ve seen a spate of headlines like 2029: the year when robots will have the power to outsmart their makers, all occasioned by an Observer interview with Google’s newest director of engineering Ray Kurzweil.
Much as I respect Kurzweil’s achievements as an inventor, I think he is profoundly wrong.
The incoming second wave of contextual agents
There’s a virtual lobby of Intelligent Virtual Assistants (IVAs) waiting to help us these days. These multi-million dollar systems include Yahoo’s Donna, Samsung’s SAMI, Google’s Now, Nuance’s Nina, Motorola’s Assist, Microsoft’s Cortana and of course Apple’s Siri. They can give you driving directions, book a dinner table, launch an app, tell a joke, take a memo, send a text, post a tweet, ring a phone, update Facebook, check stocks, search the web, turn off the lights when you go to bed, and set an alarm to wake you up in the morning. They can do incredible things, but they’re not very valuable for one weird and very general reason.
After laughing uncomfortably at the headline from The Moscow Times reporting about the recent Skolkovo Robotics Conference, I parsed through the wording and found the intended meaning. But that process … from shock and incongruity, to amusement, through multiple second thoughts and a bit of research, to an understanding of the headline … is the same process I went through as I participated in and spoke at the conference.
My interpretation of that headline – removing any sense of political rhetoric1 – is that robots are getting cheaper and becoming more available to average consumers. This was one facet of the conference and exhibition, but not the main goal.
The world may be a harsh critic, but most good ideas die because they are given too much love. If you’ve got a startup or project, you’re probably loving it to death right now, and your friends and family are supporting you in this too. But the more time you spend working on your project, the more likely you are to kill it. And this is exactly why you should enter Robot Launch 2014.
The ‘system’ behind the Google robotic cars … which have driven themselves for hundreds of thousands of miles on the streets of several US states without being involved in an accident, or violating any traffic law, all the while analyzing enormous quantities of data fed to a central onboard computer from radar sensors, cameras and laser-range finders and taking the most optimal, efficient and cost effective route … is built upon the 18th-century math theorem known as Bayes’ Rule.
What is one to make of this focus series … Big Deals: What It Means to Have the Giants Investing in Robotics … with the giants being Google, Amazon and Apple (as given in the preamble)? The assumption, of course, is that robotics investments by these companies represent a turning point in the evolution of robotics — perhaps something wholly different, outside the normal ebb and flow of robotics investments, acquisitions, and mergers. It is also assumed that the investments represent some type of trend, or at least have something in common.
In this 4th interview of our four-part ECHORD series, conducted last June, Sascha Griffiths from TUM talks to Raffaello D’Andrea, Professor of Dynamic Systems and Control at ETH Zurich and technical co-founder of Kiva Systems. The series explores success stories and common obstacles in industry-academia collaborations in the field of robotics, and examines the differences between these collaborations in the US, Europe and Asia.
Collective systems play very important role on Earth, and we encounter them in all sizes, scales and forms; in biological and technological areas; in ocean, air and on the ground. Examples include viruses, different colloidal systems, nano- and micro-scale particles, huge world of social insects and animals; collective systems in robotics vary from nano- up to large space exploration robots. To some extent, collective systems are ubiquitous. Such a prevalence and diversity and can be explained by several unique properties: scalability, reliability, flexibility, self-developmental capabilities. This guest lecture introduces the area of collective robotics and answers the questions “what and why”. Special attention is given to reconfigurable robotics, we discuses a big vision of “universal modularity” and several ways of its achieving.
In November 2013 Morgan Stanley announced their blue paper report: “Autonomous Cars: Self-Driving the New Auto Industry Paradigm.” The authors predicted trillions in savings but the announcement provided little data on where those savings would come from. However, thanks to a research note released yesterday on Tesla Motors, Inc. (TSLA’s New Path of Disruption) Morgan Stanley provided an extract from the initial report which provides an outline of how they arrived at the annual $1.3 trillion in savings.
10. Focus Focus Focus. When I started at Willow Garage, we had two projects (an autonomous car and an autonomous boat) and were planning to grow to 60 people, and I thought we needed to “round out the portfolio.” WRONG. Well, kind of wrong… the third project, the personal robot, ended up being the one we focused on. But it was absolutely the right thing to do to focus.
When you’re shopping for the best online deals you’re probably not thinking much about the massive distribution network required to bring that pair of shoes to your doorstep. Is your quest for the best possible deal helping to usher in the next wave of automation?
I am often asked which jobs will thrive as we move into the next phase of the robot revolution. My answer is that people will need to be multi-skilled. They will need critical thinking and design skills, they will need to be able to think statistically, and they will need a deep knowledge of human behavior.
When IBM’s Watson supercomputer triumphed over two top Jeopardy champions in February 2011, the media buzzed with talk of artificial intelligence (AI), just as it had fourteen years earlier when Watson’s predecessor, IBM’s Deep Blue, won a match with world chess champion Garry Kasparov. Bloggers, journalists, and radio hosts were asking a question as old as the field of computer science itself: When will computing machines surpass human intelligence?