Robots in the work place can perform hazardous or even 'impossible' tasks; e.g., toxic waste clean-up, desert and space exploration, and more. AI researchers are also interested in the intelligent processing involved in moving about and manipulating objects in the real world.
Data-driven experiences are rich, immersive and immediate. Think pizza delivery by drone, video cameras that can record traffic accidents at an intersection, freight trucks that can identify a potential system failure. These kinds of fast-acting activities need lots of data -- quickly. So they can't sustain latency as data travels to and from the cloud. That to-and-fro takes too long.
Over 72.5 million connected car units are estimated to be sold by 2023, enabling nearly 70% of all passenger vehicles to actively exchange data with external sources. The amount of data resulting from these smart vehicles will be overwhelming for traditional data processing solutions to gather and analyze, as well as the associated latency of processing this data-- leading to potential life-or-death scenarios, according to Ramya Ravichandar, from Foghorn. We speak with Ravichandar, about how connected car manufacturers are implementing edge AI solutions for real-time video recognition, multi-factor authentication, and other innovative capabilities to decrease network latency and optimize data gathering, analyzing and security. Digital Journal: What are the current trends with autonomous and connected cars? Ramya Ravichandar: Automotive companies are looking to improve real-time functionalities and accelerate autonomous operations of passenger vehicles.
NEW YORK: Scientists have developed an artificial intelligence (AI) tool that may accurately predict which patients newly infected with the virus that causes Covid-19 would go on to develop severe respiratory disease. The study, published in the journal Computers, Materials & Continua, also revealed the best indicators of future severity, and found that they were not as expected. "While work remains to further validate our model, it holds promise as another tool to predict the patients most vulnerable to the virus, but only in support of physicians' hard-won clinical experience in treating viral infections," said Megan Coffee, a clinical assistant professor at New York University (NYU) in the US. "Our goal was to design and deploy a decision-support tool using AI capabilities -- mostly predictive analytics -- to flag future clinical coronavirus severity," said Anasse Bari, a clinical assistant professor at New York University. "We hope that the tool, when fully developed, will be useful to physicians as they assess which moderately ill patients really need beds, and who can safely go home, with hospital resources stretched thin," Bari said.
In a previous blog post, we explored the importance of machine learning (ML) and delved into the five most important things that business leaders need to know about ML. First, recall that supervised learning is concerned with the prediction and classification of data. Now it's time to dive deeper. We saw that accuracy (the percentage of your data that your model predicts/classifies correctly) is not always the best metric to measure the success of your model, such as when your classes are imbalanced (for example, when 99% of emails are spam and 1% non-spam). Another space where metrics such as accuracy may not be enough is when you need your model to be interpretable.
These can be clicked together easily for a myriad of 3D configurations. MOTOR INCLUDED – The K'NEX Power and Play Motorized Building Set is the only set on the market that includes a motor. Watch your child's creations come to life when you attach the battery-powered motor to them! SUITCASE STYLE PACKAGING – Fuel your child's curiosity and let him look for inspiration everywhere by bringing this building set along on family trips! The handy, reusable box allows hassle-free carrying of this educational toy.
Autonomous technology continues to make an impact on the supply chain. The autonomous supply chain, applies to moving goods without human intervention (to some degree at least) or aiding in achieving inventory accuracy. One of the more interesting examples is the Belgian brewery De Halve Maan, which in an effort to reduce congestion on the city streets, built a beer pipeline under the streets. The pipeline is capable of carrying 1,500 gallons of beer an hour at 12 mph to a bottling facility two miles away. Autonomous technology is seen in warehouses and stores, on highways and in mines, and in last mile deliveries.
Google researchers developed an AI system that learns from the motions of animals to give robots greater agility, reveals a preprint paper and blog post published this week. The coauthors believe their approach could bolster the development of robots that can complete tasks in the real world, for instance transporting materials between multilevel warehouses and fulfillment centers. The teams' framework takes a motion capture clip of an animal -- a dog, in this case -- and uses reinforcement learning, a training technique that spurs software agents to complete goals via rewards, to train a control policy. Providing the system with different reference motions enabled the researchers to "teach" a four-legged Unitree Laikago robot to perform a range of behaviors, they say, from fast walking (at a speed of up to 2.6 miles per hour) to hops and turns. To validate their approach, the researchers first compiled a data set of real dogs performing various skills.
Robots are increasingly becoming common in everyday life. From robots that assist in blowing out fires to robots that help the elderly, it seems that robots are here to stay and, more importantly, here to help humanity. But how do you ensure that robots only help humanity? What ethics should robots abide by? And what do you do about potential lethal robots, robots meant to be used in war?
Given the outsized hold Artificial Intelligence (AI) technology has acquired on public imagination of late, it comes as no surprise that many are wondering what AI can do for the public health crisis wrought by the COVID-19 coronavirus. A casual search of AI and COVID-19 already returns a plethora of news stories, many of them speculative. While AI technology is not ready to help with the magical discovery of a new vaccine, there are important ways it can assist in this fight. Controlling epidemics is, in large part, based on laborious contact tracing and using that information to predict the spread. We live in a time in which we constantly leave digital footprints through our daily life and interactions.
Automation Anywhere, a global leader in Robotic Process Automation (RPA), announced the launch of Bot Security, the industry's first security program to set the standard for securing software bots that enable business continuity. The magnitude of the coronavirus (Covid-19) outbreak has organizations around the world looking to technologies like RPA and intelligent automation to help mitigate disruptions and advance public health, keep global supply chains moving and governments afloat. Today, the company introduced a flexible, multi-tiered framework to certify that bots built by customers, partners, and publishers of bots on Bot Store – the world's largest intelligent automation marketplace with more than 850 pre-built bots – are pre-certified and trusted to scale RPA more rapidly and securely. With Bot Security, users downloading ready-to-deploy intelligent software bots no longer have to compromise on security as they build RPA solutions to access critical data, track the virus' spread and direct citizens to vital information from trusted sources. Automation Anywhere leads the industry as the first vendor to offer a web-based, cloud-native RPA platform that is System and Organization Controls (SOC) 2 Type 1 certified.