In the cult classic, Blade Runner, sophisticated androids made with organic body parts, known as'replicants', can match the strength and emotions of their human creators. And according to an expert, advances in soft robotics could see replicants, such as those seen in Blade Runner and the Terminator, become a reality. In an article for The Conversation, Fumiya Iida, a lecturer in mechatronics at the University of Cambridge looks at the future of building robots with human-like abilities. From a scientific point of view, the real challenge is replicating the complexity of the human body. Each one of us is made up of millions and millions of cells, and we have no clue how we can build such a complex machine that is indistinguishable from us humans.

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We'll also be posting a weekly calendar of upcoming robotics events for the next two months; here's what we have so far (send us your events!): Let us know if you have suggestions for next week, and enjoy today's videos. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) had developed a new shape-shifting robot that's something of a superhero: It can transform itself with different "outfits" that allow it to perform different tasks. Dubbed "Primer," the cube-shaped robot can be controlled via magnets to make it walk, roll, sail, and glide.

Twitter just paid $150m for 14-person Magic Pony, a UK-based AI visual search company barely anyone had heard of before the deal. At $10m per employee it marks a high water mark in AI for what is essentially a team acquisition. Magister has tracked 26 AI driven deals since 2014 in the US, Europe and Israel, 11 of which involved companies with less than 50 employees which were acquired largely, or entirely, for the team and capability. Across all 11 deals, the median price paid per employee has reached $2.4m, meaning a high quality AI company with 40 employees would be valued at near $100m. Even if it had little or no revenue.

The startup product is an AI based chatbot with remote identification. Instead of mobile applications and internet banking, all money management, including activation, blocking and unblocking of cards, and free of charge transfers in TalkBank are handled by chatbots, intellectual robot assistants, using text messages. The startup uses machine learning technologies which recognize users' speech and forecasts responses. That's why we – the TalkBank team- created the robot bank. Investors' support will certainly allow us to offer services to wider population in Russia and abroad.

– Digital wallets are becoming the new way to pay. Most interesting factor here is to know companies who are most successful in this field actually came out of payment industry with no prior knowledge or payment intelligence but rather came with Artificial Intelligence. How to pay and where to pay, when to pay etc. Disrupted the most unknown and unsecured payment methods like contactless payment systems. Does any one ask any question from these ventures weather their suggested methods are safer, secured or how much vulnerable than chip-enabled plastic cards, and what it might take for contactless systems to be used as widely as cash. How the data or sensitive data of a customer been treated and used in their systems.

The smart factory of the future will require continuous integration of order information, machines, molds, and logistic peripherals using standardized and transparent information technology. Functional assemblies such as robotic systems are linked with the machine's central control system by means of a real-time Ethernet connection and are automatically identified by this as soon as they are plugged in. According to Industry 4.0, every component of every machine in a "smart factory" can communicate with host-computer devices (such as Arburg's ALS) in order to create a transparent production. Cleanroom production at Plastikos Plastikos Inc. in Erie, Pa., which is implementing elements of Industry 4.0. At Vorwerk in Germany, complete movement of parts is managed via a six-axis-robot integrated with the machine controller (Arburg's Selogica control).

Classyfier smart table is a fun demo of how machine learning can be used to improve the ambience in your home. Thanks to the Internet of Things, breakthroughs in machine learning, and the plethora of cheap sensors that are readily available, virtually every "dumb" piece of household furniture now has a smart counterpart. A table created by researchers at Denmark's Copenhagen Institute of Interaction Design that is able to detect what beverages people are drinking around it and select the appropriate mood music. "Have you been in situations where the mood dropped because someone took forever to decide which music to play?" Kelvyn Marte, one of the three designers (along with Benedict Hubener and Stephanie Lee) who created the table, told Digital Trends. "The Classyfier is a table that automatically chooses music to fits the current situation. It does that by picking up the characteristic sounds of beverages consumed around it, [such as] the clinking of wine glasses or the sound of opening a can of beer. It basically takes the role of the designated DJ so that people can focus on other things. We found it exciting to use sound as an input because it opened up a lot of new interactions that could be either very intentional or completely seamless to your normal behavior."

LONDON – Contrary to popular belief, busy city centers beat suburban living when it comes to human wellbeing, as socializing and walking make for happier, healthier people, according to a new report. Downtown residents -- packed together in tight row houses or apartment blocks -- are more active and socially engaged than people who live in the sprawl of suburbia, according to a report that aims to challenge popular beliefs about city life. Its authors said their findings should encourage politicians to promote the benefits of built-up city living. "If we can convince policy makers that this is a public health opportunity, we can build well-designed communities, and in the long term, you have made a big difference in health outcomes," coauthor Chinmoy Sarkar said. "With evidence, we can plan multifunctional, attractive neighborhoods that promote physical activity, promote social interaction, and shield from negatives such as pollution and feeling unsafe."

Rapid advancements in the field of robotics coupled with the rise of computing power during the latter half of the twentieth century has exponentially increased the breath of tasks that can be assigned to robots and systems based on an artificial intelligence (AI), as well as the autonomy with which such technologies operate. While this can be beneficial for global development and societal change, for instance by contributing to the fulfilment of the United Nations Sustainable Development Goals, it also raises legal, ethical and societal concerns and challenges, some of which may be hazardous for human wellbeing, safety and security. In 2015, UNICRI launched its programme on AI and Robotics. Utilising knowledge and information of experts in the field to educate and inform stakeholders, and in particular policy-makers, UNICRI believes it will be possible to progress discussion on robotics and artificial intelligence governance. Building consensus amongst concerned communities (national, regional, international, public and private) from theoretical and practical perspectives in a balanced and comprehensive manner is integral to its approach.

Google acquired the British artificial-intelligence startup DeepMind in 2014 for a reported £400 million (roughly $525 million), a company its cofounder Demis Hassabis once described as aiming at "solving intelligence, and then using that to solve everything else." Since then, the company's researchers have built a system that beat humans at one of the most complicated board games ever, and is now trying to beat humans at complex video games. It's building AI that's learning to navigate 3D spaces as we do, and is training other systems on British medical data, theoretically to spot illness more quickly. It's also started to integrate with teams in the US to bring its work to Google products where they might be useful. All of this research comes at a price.