If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Honeywell, a company best known for making control systems for homes, businesses and planes, claims to have built the most powerful quantum computer ever. Other researchers are sceptical about its power, but for the company it is a step toward integrating quantum computing into its everyday operations. Honeywell measured its computer's capabilities using a metric invented by IBM called quantum volume. It takes into account the number of quantum bits – or qubits – the computer has, their error rate, how long the system can spend calculating before the qubits stop working and a few other key properties. Measuring quantum volume involves running about 220 different algorithms on the computer, says Tony Uttley, the president of Honeywell Quantum Solutions.
Stéphane Fymat, the head of that new business, said Honeywell expects the hardware and software market for urban air taxis, drone cargo delivery, and other drone businesses to reach $120 billion by 2030 and Honeywell's market opportunity would be about 20% of that. He declined to say how much of that market Honeywell was targeting to capture, adding only that the unit has hundreds of employees with many engineers. Honeywell doesn't build drones itself but provides autonomous flight controls systems and aviation electronics. The new business creation comes as the coronavirus pandemic creates a surge of interest in drone deliveries; Fymat said it's accelerating the drone cargo delivery programs of some of its partners. Some of Honeywell's customers include Intel-backed Volocopter, Slovenia-based small aircraft maker Pipistrel, which is developing an electric vertical take-off and landing aircraft for cargo delivery, and UK-based Vertical Aerospace, which has test flown a prototype vehicle last year that can carry 250 kilograms and fly at 80 kilometers an hour.
Quantum computers have been quite the rage recently with different tech companies vying for the top spot when it comes to building the most powerful quantum machine. While IBM and Google were in the headlines last year for achieving quantum supremacy, other companies like the Industrial giant Honeywell have been quietly working on its own quantum tech. The company plans to make available its quantum machine to clients via the internet in the next three months. However, Honeywell's approach is a little different than the traditional quantum computers which use superconducting qubits to operate. Honeywell's quantum computer uses a different technology, called ion traps, which hold ions in place with electromagnetic fields.
Quantum computing isn't yet far enough along that it could have helped curb the spread of this coronavirus outbreak. But this emerging field of computing will almost certainly help scientists and researchers confront future crises. "Can we compress the rate at which we discover, for example, a treatment or an approach to this?" asks Dario Gil, the director of IBM Research. "The goal is to do everything that we are doing today in terms of discovery of materials, chemistry, things like that, (in) factors of 10 times better, 100 times better," And that, he says, "could be game-changing." Quantum computing is the next big thing in computing, and it promises exponential advances in artificial intelligence and machine learning through the next decade and beyond, leading to potential breakthroughs in healthcare and pharmaceuticals, fertilizers, battery power, and financial services.
Honeywell announced investment and partnership with Daedalean.ai, Honeywell has invested in and signed a technological partnership with Swiss startup Daedalean.ai A longtime major player in aviation, Honeywell is working quickly to secure its position as a supplier of navigation, flight controls and other avionics for many of the 200 electric and hybrid VTOL concepts under development. Daedalean's computer vision and machine learning expertise, which is already used by Volocopter and likely other OEMs, is a sensible fit. The two companies plan to cooperate "towards the development of a fully autonomous AI pilot for [GA and UAM]," according to the joint press release.
If you have already looked at how to invest in robotics stock and perused a list of the biggest robotics stocks, it's now time to take a look at five stocks that give investors the best way to play the theme of rising adoption of robotics automation. Let's take a look at five of the top companies playing the field of robotics and why their stocks are attractive for investors. Deere (NYSE:DE), an agricultural and construction machinery equipment manufacturer, might not be the first name that springs to mind when looking at robotics automation stocks; however, the Internet of Things (IoT) and the increasing use of automation will be key drivers of Deere's growth in the future. The company's core business is agricultural machinery. To be clear, a stock that operates in the farming sector will always be susceptible to the vagaries of the industry.
Bottom Line: The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields. Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30%, increasing production throughput by 20%, reducing maintenance costs 30% and delivering up to a 35% increase in quality. Accenture, Manufacturing The Future, Artificial intelligence will fuel the next wave of growth for industrial equipment companies (PDF, 20 pp., no opt-in) How the IIoT can change business models. How emerging technologies can transform the supply chain.
Relax while these deals help you during the holidays. If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA Today's newsroom and any business incentives. We've already been on the hunt for tons of early Black Friday deals you can get right now from Amazon, Target, L.L.Bean, eBay, and so many other retailers, which is already getting us pumped for the big shopping weekend. This is probably the best time to save on the things you'll need for the holidays, gifts, and maybe something special for yourself.
Honeywell is working with robotics researchers at Carnegie Mellon University (CMU) to develop new technologies for distribution centers. The focus is on building an architecture that relies on artificial intelligence and advanced robotic systems to ease supply chain demands for complex e-commerce operations. The goal is to create an architecture that can control and operate multiple robotic applications with intelligent motion and collision avoidance, and reliable sensing. The idea is have robots that can make critical decisions in unpredictable environments, like unloading shipping containers or filling individual e-commerce orders. Read also: What are the best Raspberry Pi alternatives?
Most examples of artificial intelligence in the enterprise today are just on the fringe of what's possible with the technology in the future, according to a group of 10 industry thought leaders who met in New York City on Monday as part of the latest edition of Think Tank by Adobe. Kathryn Hume, VP of product and strategy at Integrate.ai, offered some early perspective by saying that AI is not a new concept. In fact, the exploration of AI has been going on for well over 50 years. "We are swimming in data," Hume said. "There's a tremendous amount of it, and we are seeing an increase in the importance of the machine-learning algorithm.