Robotics & Automation


Florida Eases Self-Driving Car Rules: Are States And Cities On The Hook For Mishaps?

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Jurisdictions might be on-the-hook for their self-driving car laws that allow autonomous cars and for which might get into mishaps or crashes. Florida just passed a law that widens the door for self-driving driverless cars to roam their public roadways and do so without any human back-up driver involved. Some see dangers afoot, others see progress and excitement. Ron DeSantis, governor of Florida, declared that by approving the new bill it showed that "Florida officially has an open-door policy to autonomous vehicle companies." There are now 29 states that have various driverless laws on their books, per the National Conference of State Legislatures: Alabama, Arkansas, California, Colorado, Connecticut, Florida, Georgia, Illinois, Indiana, Kentucky, Louisiana, Maine, Michigan, Mississippi, Nebraska, New York, Nevada, North Carolina, North Dakota, Oregon, Pennsylvania, South Carolina, Tennessee, Texas, Utah, Virginia, Vermont, Washington, and Wisconsin, plus Washington, D.C. Here's a question that some politicians and regulators are silently grappling with, albeit some think that they have the unarguably "right" answer and thusly have no need to lose sleep over the matter: Should states, counties, cities and townships be eagerly courting self-driving autonomous cars onto their public roadways, or should those jurisdictions be neutral about inviting them into their locales, or should they be highly questioning and require "proof until proven safe" before letting even one such autonomous car onto their turf?


Quick demo of Computer Vision performing objects recognition (CV, ML, AI)

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Quick demo of Computer Vision (CV) - Machine Learning (ML) - Artificial Intelligence (AI) performing objects recognition that can be used in industry, line production, quality lines, autonomous car, and even at home - to identify who's ringing the doorbell:) There are lots of applications. For further infos, don't hesitate to contact me.


Students to use artificial intelligence to program self-driving cars

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Students at the Pearl Technology/ Richwoods Township STEM Academy had the opportunity to learn from, and operate cars of the future. The program focuses in on autonomous 1/18th- scale cars developed by Amazon Web Services. The cars- called AWS DeepRacers– learn through rewards and students' controls. It's a platform that only some engineers and developers have had an opportunity to experience. "In my day we didn't have these opportunities, but when you see kids that are fifth through eighth grade actually teaching cars how to drive themselves and that their thought process can get wrapped around artificial intelligence, it's an amazing thing to watch," said Dave Johnson, President of Pearl Technology.


Inside The First-Ever Self-Driving Race Cars

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Roborace is an all-electric autonomous-vehicle racing series. Each racing team features programmers responsible for customizing the algorithms within the self-driving software that controls these autonomous cars. Competitions within the series even include self-driving cars versus human drivers.


MIT's neural network aims to create the perfect pizza ZDNet

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Cooking well takes patience, time, practice, and skill, and so is it possible for a machine to do what professional human chefs take years to perfect? A new study in deep neural networking, titled "How to make a pizza: Learning a compositional layer-based GAN model" and recently published on arxiv.org The PizzaGAN project is described as an experiment in how to teach a machine to make a pizza by recognizing aspects of cooking, such as adding and subtracting ingredients or cooking the dish. The Generative Adversarial Network (GAN) deep learning model is trained to recognize these different steps and objects, and by doing so, is able to view a single image of a pizza, dissect and peel apart each object or change'layer,' and recreate a step-by-step guide to cook it. "Given only weak image-level supervision, the operators are trained to generate a visual layer that needs to be added to or removed from the existing image," the research paper explains.


The Future of Work and Your Place in It

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It is the year 2035. Your self-driving car has dropped you in front of your office and your robot receptionist is giving you a list of all visitors. You are hungry and are checking your food (hydroponic plants for fruits and vegetables and in-vitro cloned meat) source on a vertical building plant on a mind-controlled phone. You unload your package, sign the delivery ledger and walk back to your AI controlled cabin that has everything set as per your preferences. No, this is not fiction we are talking about.


5 ways artificial intelligence will affect SEO

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Artificial intelligence is not just about science-fiction and robots anymore. In today's digital landscape, artificial intelligence technology is pervading and reshaping various industries in the form of self-driving cars, chatbots, & smart devices and digital marketing is no exception. The Search engine optimization medium has faced innumerable fundamental strategic changes over the years, due to revolutionary new intelligent algorithms and ever-adapting process of improving user experience. Marketers agree that any chances of using tactics and tricks to outsmart Google's algorithms are now over. In fact, the SEO is now subjected to the concept-based content, powerful content strategy links the building, and optimization of meta tags.


The Future of Artificial Intelligence Comes Alive in Our Buildings - USC Viterbi School of Engineering

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USC Viterbi Professors Burcin Becerik-Gerber and Gale Lucas launch CENTIENTS, a center aimed at fostering research and collaboration toward human-centered design and integration of intelligent technologies into built environments. In the 1960s cartoon The Jetsons, the future was a world full of self-driving cars and sassy, meticulous robots. Individuals, like the patriarch George, could move through space--and the shower--without having to lift a finger. The mechanisms around him played a pivotal role in making decisions on his behalf, based on a learned understanding of his most basic preferences. For a while, this future seemed distant, but upon us now is an unprecedented opportunity to merge human behavior and preferences with automation to create a personalized, dynamic and improved daily reality for individuals at work and at home.


How Singapore is using AI

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Self-driving vehicles, dating apps which give out relationship advice, humanoid robots that crack jokes and get upset... With a global market that is expected to reach US$35,870 million by 2025 from its direct revenue sources, artificial intelligence (AI) is no longer just the subject of science fiction books. According to a study carried out by IDC, in the ASEAN region, AI adoption rates are currently on the rise and growth has almost doubled in comparison to last year. When it comes to adopting this emerging technology, Indonesia is leading the way, with 24.6% of companies already embracing AI in some capacity. Thailand comes in second and the bronze medal goes to Singapore.


AI adoption advances, but foundational barriers remain

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The adoption of artificial intelligence (AI) is rapidly taking hold across global business, according to a new McKinsey Global Survey on the topic.1 1.The online survey was in the field from February 6 to February 16, 2018, and garnered responses from 2,135 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures. To adjust for differences in response rates, the data are weighted by the contribution of each respondent's nation to global GDP. AI, typically defined as the ability of a machine to perform cognitive functions associated with human minds (such as perceiving, reasoning, learning, and problem solving), includes a range of capabilities that enable AI to solve business problems. The survey asked about nine in particular,2 2.The nine capabilities are natural-language text understanding, natural-language speech understanding, natural-language generation, virtual agents or conversational interfaces, computer vision, machine learning, physical robotics, autonomous vehicles, and robotic process automation (RPA). Some would argue that RPA should not be classified as AI in and of itself, but in our experience, RPA systems are increasingly incorporating AI capabilities.