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) …
DIGITIMES Research report shows that Taiwan's ICT industry development has shifted from focusing on hardware to hardware/software integration models. The industry is combining big data analysis and AI applications in public IoT to facilitate the development of smart city management. Tools such as IoT, AI, cloud computing, and communications technologies are efficiently integrated with urban infrastructure to ultimately produce economic benefits and improve quality of life. It is estimated that the business opportunities of smart cities will reach $2.6 trillion in 2025, mainly in the Asia Pacific region. This includes sectors such as smart poles, building, parking, monitor, government, transportation, fire protection, water conservancy and WITMED.
We can only begin to imagine the possibilities Artificial Intelligence holds, but one of the most well-known topics related to AI potential is that of autonomous driving. The concept of machines that mimic human cognition – Artificial Intelligence, or AI for short – dates back as early as ancient Greece, though the term wasn't coined and developed into a field until 1956. In recent years the technology has rapidly progressed and its uses have broadened significantly to include areas like agriculture, medicine, voice assistance, and even autonomous driving. Also Read: What are smart cities? The convergence of AI and autonomous vehicles is a big step for both the automobile industry and the AI industry.
The advancement of artificial intelligence (AI) is gradually blurring the lines between the physical and digital worlds. For many industries, AI is no longer just a conceptual idea for the future, but a very real technology with innovative applications. Even so, society is only beginning to feel the impact of AI as experts strive to understand all the possibilities. It is clear that the true potential of AI has yet to be discovered, but the current advancements in AI do give us a decent idea of what it may look like. Here are some of the advancements in AI that you may soon see in your daily life.
We tend to take our sense of touch for granted in everyday settings, but it is vital for our ability to interact with our surroundings. Imagine reaching into the fridge to grab an egg for breakfast. As your fingers touch its shell, you can tell the egg is cold, that its shell is smooth, and how firmly you need to grip it to avoid crushing it. These are abilities that robots, even those directly controlled by humans, can struggle with. A new artificial skin developed at Caltech can now give robots the ability to sense temperature, pressure, and even toxic chemicals through a simple touch.
For spontaneous photography, the best camera for the job is the one you happen to be holding. For the overwhelming majority of casual photographers, that camera is the one in your smartphone. The very first cameras appeared on commercial mobile phones around the turn of the century (although as ever with tech milestones, there are multiple claims to the title of pioneer). The early work of companies like Kyocera, Motorola, Samsung, and even Apple, opened the floodgates to what is now best called'computational photography'; relatively small sensors and lenses, paired with massively sophisticated algorithms and processing to deliver the kind of images that even the best DSLR cameras would struggle to match. One company believes that mobile photography could be better.
We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. During CES 2022 in January, John Deere debuted a fully autonomous tractor, powered by artificial intelligence, that is ready for large-scale production. According to a press release, the tractor has six pairs of stereo cameras that capture images and pass them through a deep neural network – that then classifies each pixel in approximately 100 milliseconds and determines if the machine continues to move or stops, depending on if an obstacle is detected. And in March, the Iowa-based company launched See & Spray Ultimate, a precision-targeted herbicide spray technology designed by John Deere's fully owned subsidiary Blue River Technology. Cameras and processors use computer vision and machine learning to detect weeds from crop plants.
Despite being released more than a decade ago, NASA's turbofan engine degradation simulation dataset (CMAPSS) remains popular and relevant today. In this series, I plan to demonstrate and explain multiple analysis techniques while providing a solution for more complex datasets. The Turbofan dataset has four datasets of increasing complexity. Engines start normally but develop a malfunction over time. For train sets, engines are run to fail, while on test sets the time series expires'a period' before they fail.
Is it feasible to build a computer with a sense of taste? In response to this question, IBM Research scientists developed HyperTaste, a chemical taste sensing tool. It performs analyses and detects the chemical composition of liquids using its "electronic tongue" status. "HyperTaste was inspired by advances in AI and machine learning to mimic human senses like sight and hearing for recognizing images and interpreting speech. We wanted to present a new lens for chemical sensing," explained Patrick Ruch from IBM Research, the coauthor of the study.
The first step towards understanding IoT is rather easy. Thankfully, in a welcome break from acronyms and complex nomenclature, the term IoT – Internet of Things – quite literally means just that. Things connected to the internet so the data they produce (or data about them) can be accessed from anywhere. Viewed through a different lens, IoT is a result of faster and cheaper Internet connectivity trying to meet our insatiable hunger for data. The underlying technology is not a complex one - college students rig up IoT proof of concepts as projects; electronics hobbyists can buy simple IoT kits online to play with.
Research in the field of machine learning and AI, now a key technology in practically every industry and company, is far too voluminous for anyone to read it all. This column, Perceptron (previously Deep Science), aims to collect some of the most relevant recent discoveries and papers -- particularly in, but not limited to, artificial intelligence -- and explain why they matter. This week in AI, engineers at Penn State announced that they've created a chip that can process and classify nearly two billion images per second. Carnegie Mellon, meanwhile, has signed a $10.5 million U.S. Army contract to expand its use of AI in predictive maintenance. And at UC Berkeley, a team of scientists is applying AI research to solve climate problems, like understanding snow as a water resource.