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) …
Hitachi has entered into a definitive contract for the acquisition of the robotic system integrator business mainly operated by an American headquartered company, JR Automation. Hitachi will conduct the acquisition with Crestview Partners. Subject to the terms and conditions of the contract, Hitachi will acquire JR Automation, which builds production lines and logistics systems using industrial robots. As a result of this acquisition, Hitachi will enter the robotic systems integrator business in North America, which is a region that is expected to see a high rate of growth. The acquisition is expected to be executed by the end of 2019, subject to the satisfaction of certain regulatory and other customary closing conditions.
A group of Google Brain and Carnegie Mellon University researchers this week introduced XLNet, an AI model capable of outperforming Google's cutting-edge BERT in 20 NLP tasks and achieving state-of-the-art results on 18 benchmark tasks. BERT (Bidirectional Encoder Representations from Transform) is Google's language representation model for unsupervised pretraining of NLP models first introduced last fall. XLNet achieved state-of-the-art performance in several tasks, including seven GLUE language understanding tasks, three reading comprehension tasks like SQuAD, and seven text classification tasks that include processing of Yelp and IMDB data sets. Text classification with XLNet saw a marked reduction of up to 16% in error rates compared to BERT. XLNet harnesses the best of autoregressive and autoencoding methods used for unsupervised pretraining through a variety of techniques detailed in an arXiv paper published Wednesday by a group of six authors.
Product suggestions are an ingrained part of the ecommerce experience. With the up- and cross-selling opportunities that a good system can provide, a thoughtful ecommerce experience is invaluable, as Amazon's paid search and display advertising strategy has shown. For consumers, suggested products should bring real value. Rather than being haunted for weeks by a product they searched for once, consumers should experience helpful product suggestions which complement their purchases. Often, this is the case.
Blake Morgan is a leader in customer experience, a keynote speaker, customer experience futurist and the author of two books including "The Customer Of The Future: 10 Guiding Principles To Winning Tomorrow's Business." She is a guest lecturer at Columbia University and adjunct faculty at the Rutgers executive education MBA program. Blake is the host of The Modern Customer Podcast and a weekly customer experience video series on YouTube. She lives in the Bay Area with her husband, daughter and their two dogs.
I'm at the Society for Imaging Informatics in Medicine (SIIM) annual meeting this week, and looking forward to collaborating with the industry and share our latest work at the intersection of AI and medicine with the informatics community. Radiology has had a history of pushing leading edge technology in hospitals. For example, many of the earliest computer networks installed in healthcare were required because of the demands of the earliest networked modalities transmitting images to storage. That trend has continued ever since, where young startups to industry titans are exploring the tremendous potential AI holds to save the medical imaging field time and money while working to improve patient care. The field of radiology is embracing this opportunity.
"One man's trash is another man's treasure," is a familiar expression. When it comes to health and genomics, "junk" DNA may turn out to be a goldmine. In a recent study, Princeton University-led researchers used whole-genome sequencing and artificial intelligence (AI) deep learning to identify the contribution of noncoding mutations to autism risk--demonstrating that mutations in "junk" DNA can contribute to a complex disease. The study was led by Princeton professor Olga Troyanskaya, who is also deputy director for genomics at the Flatiron Institute's Center for Computational Biology (CCB) in New York City, along with professor Robert Darnell of The Rockefeller University, also an investigator at the Howard Hughes Medical Institute. Published on May 27 in Nature Genetics, the study presented an AI deep learning framework that "predicts the specific regulatory effects and the deleterious impact of genetic variants," and used it on autism spectrum disorder (ASD).
For nearly 50 years, FedEx's local package delivery method has largely gone unchanged, but it may soon evolve. The multinational corporation is currently working with the city of Manchester to begin testing a new last-mile delivery method. It involves a highly automated robot, resembling a mini fridge on wheels, that will transport products from local hubs to their final destinations. Thanks to state-of-the-art cameras and sensors, the FedEx Sameday Bot can efficiently cover the last leg of deliveries without a human operator. And because it can travel on sidewalks, this technology could increase shipping speed while reducing roadway congestion – greatly benefiting New Hampshirites.
In this report, we highlight the AI applications retail banks should be looking at right now. Over 3.3K startups across every major industry have raised equity to sell AI software-as-a-service or AI-enabled products. Meanwhile, public company executives are increasingly discussing AI on earnings calls. But banks are still lagging behind in AI adoption. In this report, we look at what's holding banks back, and how can retail bank execs can break through the AI hype to find solutions that will help them today.
Every year, the OECD Forum brings together experts, academics and thought leaders from the private and public sector to discuss key economic and social challenges on the international agenda. The theme of this year's Forum was "World in EMotion" – a theme that reflects the profound changes brought about by globalisation, shifting politics and digitalisation, and the challenges and opportunities that they present. Nowhere are these changes more rapid – and perhaps far-reaching – than in the field of artificial intelligence (AI), and its implications for values and ethics. I attended a very interesting panel on this subject, alongside Peter Gluckman, Chair of the International Network for Government Science Advice in New Zealand; Geoff Mulgan, Chief Executive of NESTA in the UK; Eric Salobir head of Optic; Pallaw Sharma, Senior Vice President at Johnson & Johnson; and Jess Whittlestone, Research Associate at the Centre for the Future of Intelligence at Cambridge University. As Pallaw explained, technology and AI are not magic powers; they are just extraordinary amplifiers and accelerators that add speed and accuracy.
Harshajit is a writer / blogger / vlogger. A passionate music lover whose talents range from dance to video making to cooking. Football runs in his blood. He is also a self-proclaimed technician and likes repairing and fixing stuff. When he is not writing or making videos, you can find him reading books/blogs or watching videos that motivate him or teaches him new things.