Prominent members of Europe's so-called "Skype Mafia," all co-founders or early employees of the voice-over-Internet conferencing service, are backing Pactum, a startup that uses artificial intelligence to automate business contract negotiations. Founded late last year but only emerged from stealth mode on Wednesday, Pactum uses a chatbot-like interface to conduct contract talks. The bot can offer changes to standard terms, including price, delivery conditions and days to pay, in order to reach a better deal. The company is based in Mountain View, Calif., with engineering offices in Tallinn, Estonia, where Skype's first engineering offices were also located. Among those investing in the small startup are Jaan Tallinn, a Skype co-founder who has become a prominent backer of A.I.-related startups and research groups, Taavet Hinrikus, an early Skype employee who went on to found international payments firm TransferWise, Ott Kaukver, another early Skype employee who is now the chief technology officer at Twilio, and Sten Tamkivi, a general manager at Skype who is now chief product officer at Topia.

The oldest known knitting item dates back to Egypt in the Middle Ages, by way of a pair of carefully handcrafted socks. Although handmade clothes have occupied our closets for centuries, a recent influx of high-tech knitting machines have changed how we now create our favorite pieces. These systems, which have made anything from Prada sweaters to Nike shirts, are still far from seamless. Programming machines for designs can be a tedious and complicated ordeal: When you have to specify every single stitch, one mistake can throw off the entire garment. In a new pair of papers, researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have come up with a new approach to streamline the process: a new system and design tool for automating knitted garments. In one paper, a team created a system called "InverseKnit," that translates photos of knitted patterns into instructions that are then used with machines to make clothing.

LONDON (Reuters) - "This is nice, it tickles me," Kaspar the social robot tells four-year-old Finn as they play together at an autism school north of London. Kaspar, developed by the University of Hertfordshire, also sings song, imitates eating, plays the tambourine and combs his hair during their sessions aimed at helping Finn with his social interaction and communication. If Finn gets too rough, the similarly sized Kaspar cries: "Ouch, that hurt me." A therapist is on hand to encourage the child to rectify his behavior by tickling the robot's feet. Finn is one of around 170 autistic children that Kaspar has helped in a handful of schools and hospitals over the last 10 years.

Future Tense is a partnership of Slate, New America, and Arizona State University that examines emerging technologies, public policy, and society. KASPAR (Kinesics and Synchronization in Personal Assistant Robotics) is a robot originally conceived as part of a research project begun in the late 1990s by artificial intelligence researcher Kerstin Dautenhahn and her collaborators at the University of Reading in England. Initially, the objective was to develop "robotic therapy games" to facilitate communication with autistic children and to help them interact with others. In 2005, now at the University of Hertfordshire, the KASPAR Project was formally launched with the aim of developing a "social" robot having two missions: first, and mainly, to be a "social mediator" responsible for facilitating communication between autistic children and the people with whom they are in daily contact--other children (autistic or not), therapists, teachers, and parents--and also to serve as a therapeutic and learning tool designed to stimulate social development in these children. The objective was to teach young people with autism a variety of skills that most of us master, more or less fully, without any need of special education: understanding others' emotions and reacting appropriately, expressing our own feelings, playing in a group while letting everyone take turns, and imitating and cooperating with others.

In Part 1 of a four-part series, we explore disability in the digital age: how tech is offering new solutions, and new questions, for the future of human interaction. In a recorded therapy session, humanoid robot Kaspar blankly bats his large, round eyes at a young autistic boy. The boy timidly tickles Kaspar's feet, then flashes an ecstatic grin when the robot says, "This is nice. Ben Robins, a Kaspar researcher at Hertfordshire University in southern England, hopes that such modest breakthroughs could help children on the autism spectrum learn to socialize. "Every autistic child is so different, but most open up to robots," says Robins.

"This is nice, it tickles me," Kaspar the social robot tells four-year-old Finn as they play together at an autism school north of London. Kaspar, developed by the University of Hertfordshire, also sings song, imitates eating, plays the tambourine and combs his hair during their sessions aimed at helping Finn with his social interaction and communication.

'This is nice, it tickles me,' Kaspar the social robot tells four-year-old Finn as they play together at an autism school north of London. Kaspar, developed by the University of Hertfordshire, also sings song, imitates eating, plays the tambourine and combs his hair during their sessions aimed at helping Finn with his social interaction and communication. If Finn gets too rough, the similarly sized Kaspar cries: 'Ouch, that hurt me.' A therapist is on hand to encourage the child to rectify his behaviour by tickling the robot's feet. Finn is one of around 170 autistic children that Kaspar has helped in a handful of schools and hospitals over the last 10 years.

A playful child-size humanoid robot with a face inspired by comics and Japanese Noh theater is being used to help teach autistic children social skills. Kaspar (Kinesics and Synchronisation in Personal Assistant Robots), developed at the U.K's University of Hertfordshire, has a minimally expressive face so it doesn't "overwhelm" its play partners with social cues, thus allowing them to individually interpret the expressions as "happy," "neutral," "surprised," and so on, as they interact with the robot toy. Makers of the bot--which has been in development for a few years now but is currently on display to the public through Friday at London's Science Museum--deliberately took a low-cost approach to Kaspar so future research or commercial versions would be simple to make and easy to transport with on-board processing and battery power. They built the robot for $2,500 using a child-shaped mannequin for the body's base, off-the-shelf parts, and silicone-rubber RoboSkin with embedded tactile sensors that detect different kinds of touch. Kaspar has minimal motors, only enough to simulate the most salient gestures involved in human communication.

Robot designers commonly emphasize humanlikeness as an important design feature to make robots social or user-friendly. To understand how users make sense of the design characteristics of robots, we asked 6 participants to classify and interpret the appearance of existing robots in relation to their function and potential usefulness. All the robots had humanlike aspects in their design, and participants most commonly remarked on these humanlike features of the robots. However, the commonsense logic of the “Uncanny Valley” (UV) in HRI design, which suggests that robots should be similar to humans to some degree without being too humanlike, was not supported by participant comments, which did not correlate humanlikeness to user-friendliness in line with the UV hypothesis. Rather, participants related the design features of robots to their everyday contexts, and focused their commentary on context-dependent design implications. As a result, we suggest our understanding of the design characteristics of robots should include the perspectives of users from the earliest stages of design so we can understand their contextual interpretations of different design characteristics. Open and modularized technical platforms could support the inclusion of users in the creation of future social robots.

As a precursor to learning to use language an infant has to acquire preliminary linguistic skills, including the ability to recognize and produce word forms without meaning. This develops out of babbling, through vocal interaction with carers. We report on evidence from developmental psychology and from neuroscientific research that supports a dual process approach to language learning. We describe a simulation of the transition from babbling to the recognition of first word forms in a simulated robot interacting with a human teacher. This precedes interactions with the real iCub robot.