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) …
This company has developed a new anti-cancer drug (against pancreatic, breast, liver or brain cancer) called BPM 31510, which has been discovered by an algorithm. The major technology companies are using millions of people data to find treatments. In addition to the start-ups, all major technology companies have already begun to apply Big Data and artificial intelligence to the service of health. Big Data and artificial intelligence, combined with genetic analysis, allow researchers to search for and find patterns among patients with rare diseases, who may be separated by distance but carry the same mutation.
Branch of AI: Artificial intelligence is the study and development by which a computer and its systems are given the ability to successfully accomplish tasks that would typically require a human's intelligent behavior. Supervised learning: in this type of learning, the correct outcome for each data point is explicitly labeled when training the model. In a classification context, the learning algorithm could be, for example, fed with historic credit card transactions each labeled as safe or suspicious. Machine learning is used to find meaningful relations and to predict outcomes while data experts serve as translators to make sense of why the relation exists.
While robots and computers will probably never completely replace doctors and nurses, machine learning/deep learning and AI are transforming the healthcare industry, improving outcomes, and changing the way doctors think about providing care. Machine learning is improving diagnostics, predicting outcomes, and just beginning to scratch the surface of personalized care. Lumiata has developed predictive analytics tools that can discover accurate insights and make predictions related to symptoms, diagnoses, procedures, and medications for individual patients or patient groups. The Care Trio team has developed a three-pronged approach that helps doctors devise and understand the best care protocols for cancer patients.
Clarifai, a startup providing an application programming interface (API) that offers a type of artificial intelligence (A.I.) known as "deep learning," is announcing a $30 million round of funding today. Beyond its core application programming interface (API) for image and video recognition, Clarifai has launched the Forevery photo storage app for iOS and recently introduced Custom Training and Visual Search services. To date, Clarifai has raised $41.25 million, including the $10 million round from last year.
The new effort by Toyota is also the latest indication of a changing of the guard in Silicon Valley's basic technology research. In September, when Dr. Pratt joined Toyota, the company announced an initial artificial intelligence research effort committing 50 million in funding to the computer science departments of both Stanford and M.I.T. In addition to focusing on navigation technologies, the new research corporation will also apply artificial intelligence technologies to Toyota's factory automation systems, Dr. Pratt said. A version of this article appears in print on November 6, 2015, on page B3 of the New York edition with the headline: Toyota Planning an Artificial Intelligence Research Center in California.
The Obama administration's report on the future of artificial intelligence mentions the word "ethics" 11 times and "bias" 23 times. There are some things that machines are simply better at doing than humans, but humans still have plenty going for them. Here's a look at how the two are going to work in concert to deliver a more powerful future for IT, and the human race. What unclear about the future of artificial intelligence (AI) is whether you can put ethics into an algorithm and test it. It's also unclear whether you can eliminate bias whether it's embedded into AI systems on purpose or by accident.
The Obama administration released a report on the future of artificial intelligence and addressed everything including job loss, ethics, bias, and positive outcomes for multiple industries. There are some things that machines are simply better at doing than humans, but humans still have plenty going for them. Here's a look at how the two are going to work in concert to deliver a more powerful future for IT, and the human race. There's a lot to digest in the full report, which has been noted in multiple places. I pulled out a few key talking points to ponder as AI advances.
Today digital transformation is a well-known concept. The growing connectivity of people, machines and even businesses has changed the demands of the markets. In order to keep up and stay competitive, business have to adjust to these demands by digitizing their processes and business models. But the digital transformation also holds a lot of new opportunities to grow or even establish new branches of business. Therefore companies should embrace innovation, ensure effective customer engagement, bring in fresh ways of thinking, and empower a company to make well informed decisions as a collective whole.
PRNewswire has recently reported on ABI Research regarding Mobile Broadband Operators. They are ramping up spending for big data and machine learning as they transform into digital service providers. With a long history of handling huge datasets, and with their path now blazed by the IT ecosystem, mobile operators will devote more than 50 billion to big data and machine learning analytics through 2021, forecasts ABI Research. Machine learning technologies will lead operators to profoundly change how they manage the telecom business. "Machine learning-based predictive analytics are applicable to all aspects of the telecom business," says Joe Hoffman, Managing Director and Vice President at ABI Research.
The tech craze du jour is machine learning (ML). Billions of dollars of venture capital are being poured into it. All the big tech companies are deep into it. Every computer science student doing a PhD on it is assured of lucrative employment after graduation at his or her pick of technology companies. One of the most popular courses at Stanford is CS229: Machine Learning.