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) …
Fox News Flash top headlines for Nov. 21 are here. Check out what's clicking on Foxnews.com NASA recently showed off its new underwater rover that it hopes one day could help in exploring alien ocean worlds in the search for life. The robot, known as Buyant Rover for Under-Ice Exploration (BRUIE), is designed to crawl under an ice cap. Right now, it is being tested in Antarctica, in hopes one day it could go to ocean worlds such as Saturn's moon, Enceladus, or Jupiter's moon, Europa.
Covenant Eyes is not the only tech firm to play on these concerns, however. California-based X3watch, for example, offers a similar tracking and reporting feature, albeit one that works by creating a categorised list of the sites users visit that is then shared with their accountability partners. 'This is an opportunity to know and be known,' the X3watch website argues. 'Whether your chosen partner is a friend or a spouse, or you've come across explicit activity on your children's devices, the true goal is liberation that blossoms from open and honest relationships with others who are dedicated to your well-being.' An annual subscription to X3watch is currently priced at $70 (£54) per year.
Ever since the industrial chemist Leo Baekeland began synthesizing phenol and formaldehyde in 1907, the world has developed a love-hate relationship with the resulting polymer: plastic. While plastic is convenient, durable, and cheap, 50% of all plastics (about 150 million tons every year, worldwide) are used only once and then thrown away. Even for those who dutifully recycle our plastic water bottles and sandwich bags, we're only tackling a small part of the problem. "Considering the size of the problem, there's relatively limited infrastructure in place to capture and treat stormwater," says Tony Hale, program director for environmental informatics at the nonprofit San Francisco Estuary Institute (SFEI). That's where SFEI is looking to use research and data--and most recently, drones--to make a difference.
Developers building with Fritz AI can now more easily apply machine learning features to pre-recorded videos with FritzVisionVideo -- a new high-level, comprehensive API. FritzVisionVideo is currently available when building on iOS only. But we're working on support for Android, so stay tuned. Adding machine learning features to captured video can be tricky. Frame extraction, displaying processed results, and other processes often require difficult-to-manage-pipelines.
This is a talk from GOTO Chicago 2019 by Doug Lenat, Award-winning AI pioneer who created the landmark Machine Learning program, AM, in 1976 and CEO of Cycorp. I've dropped the full talk abstract below for a read before diving into the talk: Almost everyone who talks about Artificial Intelligence, nowadays, means training multi-level neural nets on big data. Developing and using those patterns is a lot like what our right brain hemispheres do; it enables AI's to react quickly and – very often – adequately. But we human beings also make good use of our left brain hemisphere, which reasons more slowly, logically, and causally. I will discuss this "other type of AI" – i.e., left brain AI, which comprises a formal representation language, a "seed" knowledge base with hand-engineered default rules of common sense and good domain-specific expert judgement written in that language, and an inference engine capable of producing hundreds-deep chains of deduction, induction, and abduction on that large knowledge base.
This insight was featured in the November 2019 issue of HealthCare Business News magazine. With over 150 independent software vendors developing machine learning solutions for medical imaging, sorting through the plethora of options to select vendors is a challenge. Here are 10 factors radiologists should consider (and questions they should ask) before partnering with vendors providing AI solutions for medical imaging. The foremost consideration for healthcare providers adopting AI into their clinical workflow is relevancy. Does the AI solution truly address the needs of the healthcare provider, regardless of the associated costs and inconveniences to implement such a solution?
Ever heard of the Nasca Lines? They're literal lines etched in the sands of southern Peru covering an area of nearly 1,000 square kilometers, which depict over 300 different figures including animals and plants. The best evidence suggests that they're pre-Columbian in origin, dating from between roughly 500 BC and 500 AD, and that they might mark solstice points or serve as offerings to ancient deities. Although the Nasca Lines have been studied for decades (and more intensely since they were designated a UNESCO World Heritage site in 1994), they've yet to be fully mapped. Yamagata used IBM's Watson Machine Learning Accelerator (WMLA) -- a framework designed to handle large-scale workloads spanning clusters of machines -- to expedite their analyses.
Mr Coleman announced a partnership with IBM which includes Woodside becoming a member of the MIT-IBM Watson AI Lab, a collaborative industrial-academic laboratory focused on advancing fundamental AI research. Mr Coleman said Woodside had used AI to try to differentiate itself since 2013. The CEO recalled he "looked around the industry and saw people making money who shouldn't really be making money." The Woodside chief said every ten years Woodside builds a "mega project" worth more than $US10 billion ($14.6 billion). "The seminal moment was when I got my management team around the table, I said: 'Look, we just built this mega project, it cost $15 billion, it was about 40 per cent over on cost, give me five lessons learned'. And they couldn't do it."
The real power of machine learning may have nothing to with automating music making, and everything to do with making sound tools hear the way you do. While not a broadly known topic, the problem of source separation has interested a large community of music signal researchers for a couple of decades now. Wait a second – sure, you may not call it "source separation," but anyone who has tried to make remixes, or adapt a song for karaoke sing-alongs, or even just lost the separate tracks to a project has encountered and thought about this problem. You can hear the difference between the bassline and the singer – so why can't your computer process the sound the way you hear? Splitting stems out of a stereo audio feed also demonstrates that tools like EQ, filters, and multiband compressors are woefully inadequate to the task.
We built a bot that automatically reads doctors handwriting on Belgian death certificates with an accuracy of 47% of certificates of the usable data set correctly predicted. The bot supports government officials with the official death registration and allows for a faster such registration. The solution consists of three main components: an image-processing module, a neural net, and a natural-language processing module to output predictions of medical terms. When a person deceases, a medical practitioner must certify the deceased state of the person. There is a standard form which the physician fills in. This is done "in the field," through a handwritten statement on the form, which is subsequently forwarded to other officials under sealed envelope. The physician officially records the direct cause of death, and, if known, any secondary causes. An example of such a death certificate is given below. The example above is fairly straightforward to read, but notoriously difficult-to-read examples also exist. Because the physicians record death causes "in the field," a 100% digital solution is not feasible, and a lot of handwriting will exist for years to come. The raw data are one-page scans, provided as a PDF.