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) …
Discussed much more thoroughly in the last article AI in Banking, Artificial Intelligence (AI) is a powerful force for business. Does it have a place in Healthcare, too? In this country, healthcare is a business, even if it is full of altruistic individuals that are just seeking to help others. We thwart disease; we repair damage; we cope with aberrations in bell-curve physiology; and most importantly, we make lives better. But that doesn't work very well without a solid business foundation!
AI World 2017 is coming up quick! Whether you're a dev looking to hone your knowledge on the latest in machine learning or a tech exec trying to stay up to date on industry trends, this conference has something for anyone tuned into the AI space. Going on from December 11-13th at the Boston Marriot Copley in Boston, Ma, AI World describes its mission as "to enable enterprise business and technology executives to learn how to successfully harness intelligent technologies to build competitive advantage, drive new business opportunities and accelerate innovation efforts." Below, I'll briefly dive into some of the highlights of the upcoming show, giving you a glimpse into the speaker line-up as well as the different learning tracks that AI World is offering. You can find the agenda which outlines the events & corresponding times here, or if you'd like more details, then download the brochure here.
Now that artificial intelligence is living up to the potential that future-minded commentators have touted for a long time, many healthcare providers are considering how to factor AI and big data projects into their processes to improve care and increase efficiency. However, investing in one platform or one focus area can be risky because of the pace of change. Putting millions or billions into one platform or project, which could be obsolete or fall flat in a few years is a huge risk. Nooman Haque, Managing Director for Healthcare and Life Sciences at Silicon Valley Bank believes the industry needs "runaway successes" to drive wider global adoption. The key issue for me is around workflow.
The new Google venture is called the Launchpad Studio and it was unveiled in November 2017. The aim is to provide a new health-orientated artificial intelligence access path to Google experts for start-up companies to take advantage of. The service, PharmaPhorum reports, also aims to assist new ventures via product validation and also to give them feedback with their new projects and to help to nurture them into commercially viable healthcare solutions. As part of this process, Google will give eligible new ventures $50,000 in funding plus full access to business focused Google products, such as Google Cloud. Malika Cantor, a program manager with Launchpad, told TechCrunch: "It's our hypothesis that there's a lot of learning to be extracted by looking at an industry and all the ways machine learning can be applied across that industry.
They're not coming to destroy us, they will take some jobs -- and if it's your job, that's nearly as frightening. We're no strangers to seeing jobs replaced by automation. Despite various claims that we're losing trade jobs to China and Mexico, the majority of lost manufacturing jobs in the United States -- which a Ball State study estimates to be 87 percent -- are due to increased productivity and efficiency (i.e., better machines and automation). But, the losses aren't going to stop there. One PwC study found that by the early 2030s, approximately 38 percent of all United States jobs could be replaced by artificial intelligence (AI) and automation.
When Amazon first came out with a smart recommendation algorithm for customers, millions of consumers receive their first tailored shopping experience personalized to their own interests. This changed the consumer world and introduced us to a whole new era of shopping. Amazon's algorithms, using a method called "item-to-item collaborative filtering", are able to provide targeted shopping recommendations by creating a personalized experience for each person. Even in a very basic form, this was the beginning of using machine learning in a very practical manner. But can such artificial intelligence and machine learning also act as an enabler for changes in medicine and healthcare, as much as Amazon's algorithm changed consumerism?
Latest Report Available at Orbis research Artificial Intelligence (AI) in Healthcare Market provides pin-point analysis for changing competitive dynamics and a forward looking perspective on different factors driving or restraining industry growth. Orbis Research always aims to bring their clients the best research material and in-depth analysis of the information for any market. This new report Global Artificial Intelligence (AI) in Healthcare Sales Market for 2017 aims to fulfil the needs of the clients looking for a fresh outlook towards the Global Artificial Intelligence (AI) in Healthcare Sales Market, or fill in the knowledge gaps with the data available in the report. The well-presented and curated report is compiled by seasoned and professional research experts and subject matter experts in the field. The clients will find the report complete in all aspects as it covers all key components with valuable statistics and expert opinions in all regards.
Speaking at the Misk Global Forum in Riyadh, Saudi Arabia this week, Microsoft co-founder and now billionaire philanthropist Bill Gates shared his thoughts on today's technological advancements, including artificial intelligence (AI). Gates, who has previously warned about the challenges AI could bring, told audiences at a CNBC-moderated panel during the forum that the benefits of AI will far outweigh these potential pitfalls -- particularly in the case of healthcare AI. "We are in a world of shortage, but these advances will help us take on all of the top problems," Gates said, CNBC reports. "We need to solve these infectious diseases … We need to help healthcare workers do their job." Gates also pointed out how AI and robotics will reshape the labor landscape in the developed world. "As we free labor up from things like manufacturing, we can shift it to some of these very human-centric needs," he explained, giving society time to take care of the elderly, for example.
We've been overusing the term Artificial Intelligence and AI with everyone we meet online and offline. Mostly inspired by its influence in multiple industries. The way industries are employing this smart technology is indeed overwhelming. In fact, the use of machine learning, artificial intelligence, and deep learning is becoming pervasive in all walks of life. This ubiquitous and generous use of AI gives us a tonne of hope and curiosity about how Artificial Intelligence is going to help us deal with our day-to-day hardships.
Since heart disease is a primary killer of human beings around the world, it's no surprise that effort and focus from many AI innovators is on heart disease diagnosis and prevention. The current process to determine an individual's risk factor for a heart attack is to look at the American College of Cardiology/American Heart Association's (ACC/AHA) list of risk factors that include age, blood pressure and more. However, this is really a simplistic approach and doesn't take into account medications someone might be on, the health of the patient's other biological systems and other factors that could increase odds of a heart ailment. Several research teams, including those at Carnegie Mellon University and a study from Stephen Weng and his associates at University of Nottingham in the United Kingdom, are working toward enhancing machine learning so algorithms will be able to predict (better than humans) who is at risk and when they might be at risk for a heart attack. Preliminary results of the AI algorithms were significantly better at predicting heart attacks than the ACC/AHA guidelines.