Dig below the surface of some of today’s biggest tech controversies and you are likely to find an algorithm misfiring. These errors are not primarily caused by problems in the data that can make algorithms discriminatory, or their inability to improvise creatively. No, they stem from something more fundamental: the fact that algorithms, even when they are generating routine predictions based on non-biased data, will make errors. To err is algorithm.

iRobot (IRBT on the NASDAQ stock exchange) jumped from $70 to $80 per share on news that iRobot’s quarterly earnings were so good that the company raised their forecast for 2017 to new highs. KUKA also had good Q1/17 earnings as did Intuitive Surgical.

According to AgFunder’s 2016 AgTech Investing Report (supported by The Robot Report’s own research), 2016 drone funding fell 64% from 2015 levels. Also, the type of companies getting funded were sensor, payload and analytics-based add-ons or service-providing companies rather than drone makers.

Víctor Mayoral Vilches offers a concise overview what’s happened and what’s coming next in the world of robotics

There’s a great deal of concern over artificial intelligence; what it means for our jobs, whether robots will one day replace us in the workplace, whether it will one day lead to robot wars. But current research projects show that artificial intelligence (AI) can also be used for the greater good. Here are five global problems that machine learning could help us solve.

What can swarm roboticists learn from policy makers, systems biologists and physicists, and vice versa? It is already widely recognised that Robotics is an inherently interdisciplinary field and that designing even a single robot might require input from multiple domains. In Swarm Robotics, interactions between robots add further layers of complexity.

Agriculture is one of our most important industries. It provides food, feed and fuel necessary for our survival. With the global population expected to reach 9 billion by 2050, agricultural production must double to meet the demand. And because of limited arable land, productivity must increase 25% to help meet that goal.

“Yet another ‘follow me’ drone” says Chris Anderson – after three projects launched this weekend, including his own 3DRobotics’ open source ‘follow me’ feature for android. Extreme sports photography is the most popular application of consumer drones and at first glance it seems like a no-brainer given the success of GoPro, the rise of the sports ‘robot’ camera tripods and the obvious extension of these trends into aerial photography. And really, just what are drones good for aside from extreme sports tracking? Neither the economics nor the regulations favor package delivery and most other inspection operations can’t be commercialized in the US.

120,000 robotics patents have been published in the last 10 years, tripling in rate from 2004 to 2013, according to the UK Intellectual Property Office Informatics Team. Unsurprisingly, there was a huge drop in robotics patent applications in 2009-2010, although not all industries were as affected by the global financial crisis as robotics was. The preeminent country for robotics patents is Japan with 31% of patents published, the majority from Toyota. The US is in second place with 19%, followed by Germany (17%), China (10%), Korea (9%), France (3%) and UK at only (2%). Of course this is only an indication of the innovation activity occurring as some countries have greater propensity to patent than others.

Tesla CEO, Elon Musk, recently announced that the car manufacturer will produce self-driving cars within three years. Nissan has announced that it will have a self-driving car available by 2020, and Google has said it will do so by 2018. But how do these vehicles work?

Google completed a major step in its self-driving cars project by presenting its first purpose-built autonomous car. The car, which has no steering wheel or controls, can accommodate two people and some luggage.

Will a robot take your job? Will a higher minimum wage cause job destruction? Or is it all media hype? What’s the truth?

Guest talk in the ShanghAI Lectures, 2009-11-12

“It has increasingly been realized that some of the key characteristics underlying real-world complex dynamical systems (such as economical, financial and ecological systems) can only been modelled and thus understood and predicted at qualitative level directly.

The popular conception of farming as low-tech is woefully out of date. Modern farmers are high-tech operators: They use GIS software to plan their fields, GPS to guide field operations, and auto-steer systems to make tractors follow that GPS guidance without human hands. Given this technology foundation, the transition to full autonomy is already in progress, leveraging commodity parts and advanced software to get there more quickly than is possible in many other domains.

This article outlines some of the key technologies that enable autonomous farming, using the Kinze Autonomous Grain Harvesting System as a case study.