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.
USA TODAY Sports' Gabe Lacques breaks down how MLB is trying computer generated strike zones in the Atlantic League. An automated strike zone that converts the home-plate umpire from arbiter to mere messenger is right far more often than it is wrong. A ban on mound visits and relief specialists undeniably speeds the game's pace. And rules changes aimed to encourage balls in play and runners in motion – Thou shalt not shift defensively, but you may "steal" first base – gives hitters options beyond launching balls over a vexing alignment of fielders. Yet as its experiment with a "robotic" strike zone and other nuances enters its second month, the formal partnership between MLB and the Atlantic League illustrates the upsides and consequences of optimization.
Disease Diagnosis & Medication: Data privacy and regulatory barriers will cause a delay in disrupting this segment. If the patient is able to access their own data, they should be able to use AI for diagnosis of their X-rays or MRI scans as a second opinion. A soldier in war zones can get the AR/VR experience with instructions to help treat themselves and remove a bullet. DNA based personalized medicine to extend the life of humans. Robots to remind you to take medicine pills (e.g.
In the past few years, advanced industrial companies have made solid progress in improving productivity along the manufacturing value chain. In the US, for instance, the productivity of industrial workers has increased by 47 percent over the past 20 years. But the traditional levers that have driven these gains, such as lean operations, Six Sigma, and total quality management, are starting to run out of steam, and the incremental benefits they deliver are declining. As a result, leading companies are now looking to disruptive technologies for their next horizon of performance improvement. Many are starting to experiment with technologies such as machine-to-machine digital connectivity (the Industrial Internet of Things, or IIoT), artificial intelligence (AI), machine learning, advanced automation, robotics, and additive manufacturing.
A newly-developed pair of smart robotic shorts puts a literal bounce in the wearer's step. In an article published in the journal of Science, researchers from Harvard demonstrate what they call the'hip exosuit' -- a type of smart bionic shorts that boosts the wearer's ability to run and walk. Scientists say that unlike other exoskeletons which focus on increasing strength, the hip exosuit -- which already has a working prototype -- is designed for endurance. Using cables that line the inside of the shorts' legs, the device is able to boost the wearer's movement using the help of an algorithm that discerns their gait. A motor pack in the back then pulls the cables in sync with the wearer's motions and helps propel them forward as they move.
The race to fully autonomous vehicles is on. In April, Elon Musk declared that Tesla should have over a million level 5 autonomous vehicles manufactured by 2020. To clarify, that means over a million cars equipped with the necessary hardware capable of driving with no help from a driver. In addition, government approvals will be necessary (read: mandatory) long before self-driving Teslas will be commonplace. In addition, Musk also sparked some lively debate when he commented that Tesla will not be relying on lidar, the laser sensor technology that self-driving cars from many other companies (most notably Google's Waymo) currently depend on for "seeing" lines on the road, pedestrians, and more.
There is no better way to learn coding and AI than getting some hands-on practice. You can teach the robot to follow objects, avoid collisions, and a whole lot more with simple tutorials available. It is compatible with TensorFlow, PyTorch, Caffe, and MXNet frameworks. The kit includes a Leopard Imaging 145FOV wide angle camera, EDIMAX WiFi Adapter, SparkFun Micro OLED Breakout, and all the parts you need to get started.
Allied Market Research recently published a report, titled, "Artificial Intelligence Chip Market by Chip Type (GPU, ASIC, FPGA, CPU, and others), Application (Natural Language Processing (NLP), Robotic, Computer Vision, Network Security, and Others), Technology (System-on-Chip, System-in-Package, Multi-chip Module, and Others), Processing Type (Edge and Cloud), and Industry Vertical (Media & Advertising, BFSI, IT & Telecom, Retail, Healthcare, Automotive & Transportation, and Others): Global Opportunity Analysis and Industry Forecast, 2019-2025". According to the report, the global AI chip market was pegged at $6.64 billion in 2018 and is projected to attain $91.18 billion by 2025, registering a colossal CAGR of 45.2% during the forecast period. Rise in demand for smart homes & smart cities, surge in investments in AI startups, and advent of quantum computing have boosted the growth of the global AI chip market. However, dearth of skilled workforce hampers the market growth. On the contrary, rapid adoption of AI chips in the emerging countries and development of smart robots are expected to create numerous opportunities in the near future.
From all indicators, robots as a service (RaaS) is growing rapidly. ABI Research predicts there will be 1.3 million installations of RaaS by 2026 generating $34 billion in revenue. Let's look at what robots as a service entails, the reasons for its growth and some companies that offer RaaS solutions and the tasks it can support. Many are now familiar with the concept of software as a service (SaaS) or big data as a service (BDaaS), the pay-as-you-go or subscription-based service model. In a similar set-up, those who sign up for robots as a service get the benefits of robotic process automation by leasing robotic devices and accessing a cloud-based subscription service rather than purchasing the equipment outright.
Here's the good news about artificial intelligence: the Terminator vision of the future, where smart machines turn on humanity, is unlikely. But here's the bad news: we could be heading for disaster anyway thanks to this revolutionary technology. That, at least, is the conclusion of the filmmakers behind Machine, who spent the past year researching the state of play in AI in the hope their documentary might provoke some serious thinking on the subject before it's too late. The documentary Machine ponders the ethical questions posed by the rise of artificial intelligence, including the nature of interactions between humans and sexbots.Credit:Finch "There's a lot of decisions we're making right now that will have ripple effects for decades to come," says Justin Krook, the director of the film. "In the whole history of humanity we've never had so much power at our disposal, and we only have one chance to get these decisions right. "People are worried about the robot apocalypse but that's not exactly the biggest threat we're facing here.
Scale AI Inc., a three-year-old startup run by a 22-year-old, is teaching machines how to see. For that, it just joined Silicon Valley's list of unicorns with a fresh $100 million investment that puts its valuation above the coveted $1 billion mark, and its artificial intelligence (AI) technology has already attracted big-name customers in the field for autonomous vehicles, according to Bloomberg. Alphabet Inc.'s (GOOGL) Waymo, General Motor Co.'s (GM) Cruise, and Uber Technologies Inc. (UBER) are all buying what Scale has to offer, because well, self-driving cars are machines that need to be able to see. Scale stands out because it has built a set of software tools that are significantly reducing the time it takes to train a machine how to process and interpret visual imagery. And less time means lower costs.