Artificial intelligence (A.I.) is expected to significantly influence the practice of medicine and the delivery of healthcare in the near future. While there are only a handful of practical examples for its medical use with enough evidence, hype and attention around the topic are significant. There are so many papers, conference talks, misleading news headlines and study interpretations that a short and visual guide any medical professional can refer back to in their professional life might be useful. For this, it is critical that physicians understand the basics of the technology so they can see beyond the hype, evaluate A.I.-based studies and clinical validation; as well as acknowledge the limitations and opportunities of A.I. This paper aims to serve as a short, visual and digestible repository of information and details every physician might need to know in the age of A.I. We describe the simple definition of A.I., its levels, its methods, the differences between the methods with medical examples, the potential benefits, dangers, challenges of A.I., as well as attempt to provide a futuristic vision about using it in an everyday medical practice.
As more and more businesses become fully digitized, the instantiation of their business processes and business capabilities becomes software based. Any software implementation involves decisions being made which can result in a business getting stuck in time or creating a basis for business differentiation. A lot of these decisions have to do with simple things like what fields are made operational and what functions get implemented or not. Several years ago, I was involved in helping an insurance company with its analytics software implementation. Everyone on the management team wanted the analytics software completed so they could improve their business, but one of the project leads wanted the analytics task completed after an upgrade to their key transactional processing software.
Vast Data Universal Storage serves all data from flash. Its "shared everything" architecture uses lower cost QLC SSDs for bulk storage with more expensive Intel Optane storage class memory acceleration, connected via NVMe over Fabrics in the box. File and object protocols are presented as container-based microservices. Vast claims its method ensures data remains highly available on the fastest storage media. The Vast Data storage targets applications that hinge on fast random access, said Eric Burgener, a research vice president of storage at IT analyst firm IDC.
Microsoft announced the general availability of Microsoft SharePoint Syntex as of Oc. 1, 2020. This is the first packaged product to come out of the code-name Project Cortex initiative first announced in November 2019. Project Cortex reflects Microsoft's ongoing investment in intelligent content services and graph APIs to proactively explore and categorize digital assets from Microsoft 365 and other connected sources. Teams need tools to help them collaborate and stay productive while remotely working. SharePoint Syntex will be available to M365 customers with E3 or E5 licenses for a small per-user uplift.
This article is a summary of a three-hour discussion at Stanford University in September 2019 among the authors. It has been written with combined experiences at and with organizations such as Zilog, Altera, Xilinx, Achronix, Intel, IBM, Stanford, MIT, Berkeley, University of Wisconsin, the Technion, Fairchild, Bell Labs, Bigstream, Google, DIGITAL (DEC), SUN, Nokia, SRI, Hitachi, Silicom, Maxeler Technologies, VMware, Xerox PARC, Cisco, and many others. These organizations are not responsible for the content, but may have inspired the authors in some ways, to arrive at the colorful ride through FPGA space described here. Field-programmable gate arrays (FPGAs) have been hitting a nerve in the ASIC community since their inception. In the mid-1980s, Ross Freeman and his colleagues bought the technology from Zilog and started Xilinx, targeting the ASIC emulation and education markets.
Frances E. Allen, an American computer scientist, ACM Fellow, and the first female recipient of the ACM A.M. Turing Award (2006), passed away on Aug. 4, 2020--her 88th birthday--from complications of Alzheimer's disease. Allen was raised on a dairy farm in Peru, NY, without running water or electricity. She received a BS degree in mathematics from the New York State College for Teachers (now the State University of New York at Albany). Inspired by a beloved math teacher, and by the example of her mother, who had also been a grade-school teacher, Allen started teaching high school math. She needed a master's degree to be certified, so she enrolled in a mathematics master's program at the University of Michigan.
RingCentral, Inc., a leading provider of global enterprise cloud communications, collaboration, and contact center solutions, announced that its unified communications platform including team messaging, video meetings, and cloud phone system will now be available in Germany with a new data center in Frankfurt, and a new office in Hamburg, Germany. As RingCentral continues its global expansion efforts, Germany remains a key strategic location for the company. The new data center will also give users access to local phone numbers and emergency services in compliance with local laws and regulations. RingCentral will offer customers local data storage, the ability to register endpoints in-country and keep voice and video call media local. The new datacenter will also give users access to local phone numbers and emergency services in compliance with local laws and regulations.
Earlier in the year, Microsoft detailed the ways Bing has benefited from AI at Scale, an initiative to apply large-scale AI and supercomputing to language processing across Microsoft's apps, services, and managed products. AI at Scale chiefly bolstered the search engine's ability to directly answer questions and generate image captions, but in a blog post today, Microsoft says it's led to Bing improvements in things like autocomplete suggestions. Bing and its competitors have a lot to gain from AI and machine learning, particularly in the natural language domain. Search engines need to comprehend queries no matter how confusingly they're worded, but they've historically struggled with this, leaning on Boolean operators (simple words like "and," "or," and "not") as band-aids to combine or exclude search terms. But with the advent of AI like Google's BERT and Microsoft's Turing family, search engines have the potential to become more conversationally and contextually aware than perhaps ever before.
Companies in all business sectors are competing to recruit top-notch AI teams, but are these investments productive? With millions worldwide working in AI now, and over 90% of mid-size and larger companies having specialized AI or Data Science teams, researchers and engineers in this field are literally drowning in the pace of innovation. Per day, an AI expert needs to scan several hundred new research publications to stay up to date. Leading researchers, like Yoshua Bengio and Yann LeCun, openly admit they find it impossible to keep up. Amsterdam based startup Zeta Alpha is now launching AI Research Navigator, a new deep learning-based search platform, to help AI experts with this.