In this episode, Audrow Nash interviews Dor Skuler, CEO and co-founder of Intuition Robotics, about a socially assistive robot for older adults named ElliQ. Skuler discusses the motivation for ElliQ, how it infers context and changes its behavior accordingly, and how ElliQ adapts its behavior over time. Below is a video that shows what interactions with ElliQ look like. Dor Skuler has co-founded five ventures, the most recent being Intuition Robotics. Skuler holds an MBA and Master's of Science in Marketing from Temple University, has co-authored'Cloud Computing: Business Trends and Technologies' published by Wiley in 2016 and holds board level advisory and director roles for several telecoms, cyber security and tech-led social impact ventures.

Nuro has partnered with Fry's Food Stores to utilize its autonomous vehicles to deliver groceries in Scottsdale. Supermarket giant Kroger said it soon will end a pilot program in which more than 2,000 grocery deliveries were made in self-driving vehicles from a store in Scottsdale, Arizona. The program, launched last August, featured deliveries in autonomous vehicles from robotics company Nuro from the Kroger-owned Fry's store at 7770 E. McDowell Road for customers in ZIP code 85257. The companies described it as the nation's first program featuring deliveries to the general public from fully unmanned vehicles. Wednesday will mark the final day of deliveries.

If you thought IBM using "quietly scraped" Flickr images to train facial recognition systems was bad, it gets worse. Our research, which will be reviewed for publication this summer, indicates that the U.S. government, researchers, and corporations have used images of immigrants, abused children, and dead people to test their facial recognition systems, all without consent. The very group the U.S. government has tasked with regulating the facial recognition industry is perhaps the worst offender when it comes to using images sourced without the knowledge of the people in the photographs. The National Institute of Standards and Technology, a part of the U.S. Department of Commerce, maintains the Facial Recognition Verification Testing program, the gold standard test for facial recognition technology. This program helps software companies, researchers, and designers evaluate the accuracy of their facial recognition programs by running their software through a series of challenges against large groups of images (data sets) that contain faces from various angles and in various lighting conditions.

Google and others have developed smart clothing with built-in integrated circuits, but what if the textile itself formed the circuit? That's the idea behind The Embroidered Computer, an interactive installation from artist and researcher Irene Posch and designer/artist Ebru Kurbak, shown at this year's Instanbul Design Biennial. It's a working 8-bit electromechanical computer made from gold, linen, hematite, wood, silver and copper that functions equally as a decorative textile. As Posch notes on her website, the piece explores "the appearance of current digital and electronic technologies surrounding us, as well as our interaction with them." At the same exhibition, the artists also showed off The Yarn Recorder, a device that can record and playback sounds using steel-cored yarn.

Shrimp may be small, but some of them can pack quite a wallop. One of the pistol shrimp's claws, for instance, delivers such an explosive amount of force that it creates a shockwave of superhot plasma that can take out prey or create impromptu shelters. It only makes sense, then, that scientists hope to harness that power. A team has developed a robot claw that mimics the pistol shrimp's basic behavior to generate plasma and, potentially a valuable tool for underwater science and industry. The researchers started by creating a 3D-printed replica of the shrimp's claw, which includes a top half that cocks back like a gun, and a plunger that smacks into a socket in the bottom half.

MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a new system that gives robots the power to pick up and handle any object, even those they haven't seen before. Despite how smart machines have become, most factory robots still need to be preprogrammed with the objects they're going to handle -- that's why roboticists are taking it upon themselves develop technologies that can teach themselves how to manipulate various items. CSAIL's system called kPAM works by creating visual roadmaps of objects by seeing them as collections of 3D keypoints. CSAIL says kPAM or Keypoint Affordance Manipulation is more accurate than other similar technologies. After it detects all the coordinates on an object, it determines what it can do with it.

But if you judge a fish by Its ability to climb a tree, it will live Its whole life believing that it is stupid." While commonly attributed to Einstein the above quote is likely apocryphal. Nonetheless, it's instructive in pointing out that fact that, despite obvious misalignment, we in the tech industry often persevere in trying to make square pegs fit into round holes. Recently, nowhere is this more endemic than in Machine Learning initiatives. Two of the most common "fish climbing a tree" scenarios include "data science unicorns" and "data-driven hypotheses."

How exactly are principal component analysis and singular value decomposition related and how to implement using numpy. Principal component analysis (PCA) and singular value decomposition (SVD) are commonly used dimensionality reduction approaches in exploratory data analysis (EDA) and Machine Learning. They are both classical linear dimensionality reduction methods that attempt to find linear combinations of features in the original high dimensional data matrix to construct meaningful representation of the dataset. They are preferred by different fields when it comes to reducing the dimensionality: PCA are often used by biologists to analyze and visualize the source variances in datasets from population genetics, transcriptomics, proteomics and microbiome. Meanwhile, SVD, particularly its reduced version truncated SVD, is more popular in the field of natural language processing to achieve a representation of the gigantic while sparse word frequency matrices.

Success at games helps develop more powerful AI that can be used directly in more practical applications in the real world. DeepMind's AI agents also assist in medical research, are involved in diagnosis of diseases and the organization of patient records. With regard to the latter, DeepMind has taken some heat for data protection issues related to patients during its work with the UK's National Health Service. After being criticized for this, the company has emphasized its commitment to ethical and socially beneficial uses of AI, founding the DeepMind Ethics & Society group dedicated to directing the use of AI in a socially responsible manner. DeepMind has also contributed to subtle conveniences on your smartphone.

According to a recent TNG survey, 73 percent of job seekers in Sweden believe they've been discriminated against during the job application process. By replacing the human recruiter with Tengai, TNG and Furhat believe they can make the screening process more fair while still providing a "human" touch. "I was quite sceptical at first before meeting Tengai, but after the meeting I was absolutely struck," healthcare recruiter Petra Elisson, who has been involved in the testing, told the BBC. "At first I really, really felt it was a robot, but when going more deeply into the interview I totally forgot that she's not human." As for ensuring that Tengai doesn't reflect the biases of its creators and training data -- a problem that has cropped up with other AIs -- Furhat's chief scientist, Gabriel Skantze, told the BBC the company is making it a point to conduct test interviews with a diverse mix of recruiters and volunteers before Tengai is ever in the position to actually decide an applicant's employment fate.