Today, software-as-a-service (SaaS) companies can choose from several cloud computing providers, dozens of monitoring providers and hundreds of different apps to increase their efficiency and help bring their solutions to market. While great marketing and brand awareness efforts can make it seem like some companies are more favored in the marketplace, sustained customer growth only occurs with a great product experience. This is especially true given that most cloud solutions are available on a freemium basis, which further inspires prospective customers to try before they buy. As a result, SaaS companies are taking advantage of user-collected data to provide customized experiences, intelligent functions and improved product support. These product improvements are easily deployed thanks to APIs and solutions that make use of artificial intelligence (A.I.).

New York University's Center for Data Science is at the cutting edge of fields with revolutionary implications such as machine learning, natural language processing, computer vision and intelligent machines. Because computing speed is critical to accelerating experimentation and advancing research, the center's Computational Intelligence, Learning, Vision and Robotics (CILVR) lab recently acquired a NVIDIA DGX-1 AI supercomputer to fuel this work like never before. The CILVR lab has "unsupervised learning" as its focus. The lab's faculty, research scientists and graduate students are developing techniques that allow machines to learn from raw, unlabeled data by, for example, observing video, looking at images or listening to speech. These techniques are then applied to computer vision applications like self-driving cars that can understand the environment around them, medical image analysis that can detect tumors or disease earlier and more accurately than traditional methods, and natural language processing that can translate languages, answer questions or hold a dialogue with people. "The DGX-1 is going to be used in just about every research project we have here," said Yann LeCun, founding director of the NYU Center for Data Science and a pioneer in the field of AI. "The students here can't wait to get their hands on it."

Researchers have tried for decades to create computers capable of learning. Recently, using the human brain as a model, they have had some success. Complicated algorithms have been developed, allowing computers to learn on a limited scale. Deep Learning (DL) is the name used for the process of computers "learning" appropriate responses as they interact with their users, or seek patterns in Big Data. This Big Data "pattern seeking aspect" has the potential to replace Data Scientists as Big Data pattern seekers.

Football is also one of the most popular sports to gamble on with a myriad of bet types to choose from. The in-play market is particularly busy for bettors with prices constantly updating during the ebb and flow of the game. Because of its popularity, football attracts a lot of academic interest. Here is a citation list for academic papers concerned with football. NOTE - If any links to papers are broken then just Google the paper's title to find an alternate.

Google DeepMind's system is a move closer to the goal of creating a neural network that can navigate something as complex as the London Underground without any human-written programming. Researchers at Google-owned DeepMind in the UK have developed AI that can store knowledge, such as a map, and use it to navigate a system as complicated as London's Underground. Sure, you can already get directions from Google Maps to navigate transport networks, but DeepMind's new system inches it towards the goal of building a neural network that can navigate without any human-written programming, instead using knowledge to work out a route. Its latest efforts combine deep-learning algorithms with a machine equivalent of a human's working memory. We read the Obama Administration's report on artificial intelligence in full.

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here. Huawei's R&D arm, Noah's Ark Laboratory, announced on Tuesday a partnership with the University of California, Berkley's artificial intelligence (AI) lab focused on researching AI in all its forms. Initially, the Chinese smartphone company will fund UC Berkley 1 million as it covers areas like deep learning, reinforcement learning, machine learning, natural language processing (NLP), and computer vision. Huawei is likely investigating AI in order to ensure its not left behind by rival smartphone companies like Samsung, Apple, and Google, all of which have begun implementing AI into their devices. As hardware shipments begin to decelerate, hardware companies are looking at AI as the next growth platform.

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers. To learn more and subscribe, please click here. Baidu unveiled on Monday a medical chatbot that aims to simplify the process of collecting and sharing information between patient and doctor, VentureBeat reports. Dubbed "Melody," the bot -- which is housed within the Baidu Doctor app -- collects and aggregates medical information from users that it then passes on to doctors who use the information to make diagnoses. Melody, which is only available in China, provides a proof-of-concept that could be replicated in Western markets and lay the framework for the wider implementation of chatbots within the mobile health (mHealth) industry.

Advances in robotics and artificial intelligence (AI) are going to completely change how we live and work but the UK government is totally unprepared, MPs have warned. The Science and Technology Committee released a report on Wednesday warning that the UK government "does not yet have a strategy" for equipping citizens with the skills they need to flourish in a world where AI is more prevalent. It also has no strategy for dealing with the social and ethical dilemmas that AI advances present, according to the report. Acting chair of the Science and Technology Committee, Dr Tania Mathias MP, said in a statement: "Artificial intelligence has some way to go before we see systems and robots as portrayed in the creative arts such as Star Wars. At present, 'AI machines' have narrow and specific roles, such as in voice-recognition or playing the board game'Go'. "But science fiction is slowly becoming science fact, and robotics and AI look destined to play an increasing role in our lives over the coming decades.

With Omni-channel becoming the new norm, new prospects, activities and service requests could be generated from any source. Accordingly, insurers need to ensure that they are continuously engaged with the ever-connected and digitally-aware customers from the millennial generation to improve the overall experience and loyalty. Products Structuring AI will play a vital role in launching innovative insurance products that are structured to change dynamically and contextually for individual customers. With the help of AI, policies will be monitored on an ongoing basis for behavioral or other pattern changes, so that the coverage, price, and terms and conditions of the contract can be auto-altered. Actuarial and Product Pricing AI will play a core role in building new and dynamic risk models for products.

This system, created by a team at St. Andrews University in Scotland, uses radar technology and Google's Project Soli to identify a wide variety of items. In the future, when you come across a strange thing or material, all you'll need to do is give it a scan before promptly receiving an answer.