Relatively few healthcare organizations have the resources or analytics maturity to develop their own intricate big data analytics infrastructure from scratch, but a growing number of vendors are starting to make the daunting and costly process easier by offering Artificial Intelligence and machine learning as a service (MLaaS). The "as a service" industry, which has quickly branched out to cover a number of critical data-heavy use cases, allows organizations to contract with third-party vendors that do the heavy lifting in terms of data collection, storage, movement, and analytics. Many healthcare stakeholders are already familiar with MLaaS technologies, even if the acronym itself is new to them. On the consumer side, voice-driven personal assistants like Siri, Alexa, Cortana, and Google Home use machine learning techniques to create smart environments and automate technical tasks. In the enterprise space, IBM Watson's commercialized analytics and precision medicine services are a good example, as is Partners Healthcare's IDEA platform, which uses data lake technology to streamline the development of research projects targeting a number of high-value use cases.

According to a survey by online dating app "Coffee Meets Bagel," the perception of Valentine's Day appears to have changed dramatically. Singles are loud and proud, feeling empowered and less pressured to have a date for the hallmark occasion -- and this isn't the best news for dating apps. As a result, some operators are trying to head off dating-app fatigue with tech solutions: from the creation of in-person authentic experiences such as concerts and cultural experiences, to leveraging blockchain and artificial intelligence for courtship advice. Others may even accept cryptocurrencies for payment to match-making platforms. With men twice as active on relationship sites, according to numerous surveys, a slew of dating apps have emerged catering to women already, allowing ladies to call the shots.

SpaceX is now a step closer to launching broadband-powering satellites into orbit. Editor's Remarks: The Federal Communications Commission (FCC) announced that the agency would approve SpaceX's application to leverage satellite technology to provide broadband to the US and wider world. FCC chairman Ajit Pai said that the opportunity would help remove the US' digital divide and bring online rural parts of the country that are still without reliable internet. SpaceX declined to give an immediate statement regarding the progress but previous releases show that the company wants to launch 4,425 satellites that will form a constellation 800 miles above the Earth. Apple's latest offering costs $216 to build, giving it a lower margin than the company's other goods.

Artificial intelligence (AI) is poised to radically shift the way professionals use technology to get work done. With the proper dataset behind it, AI can help alleviate many repetitive and redundant tasks, changing the way humans approach work. While the biggest controversy around AI is its potential to replace jobs, the technology will affect other aspects of the economy in major ways. A recent report from CB Insights highlights some of the key AI trends worth paying attention to in 2018. SEE: IT leader's guide to the future of artificial intelligence (Tech Pro Research) As AI-powered robots and other forms of automation take over repetitive roles, those roles previously held by humans will shift.

Artificial Intelligence (AI) has a long history, starting in the 1950s with the theoretical concept of the Turing test and gaining considerable momentum since the early 2000s. This development has been driven by the significant increase in computing power which makes computation-intensive Deep Learning algorithms easy and effortless to handle. The intelligent processing of images (computer vision) and speech (natural language processing) is becoming a routine part of our customers' daily lives as found in mass market applications such as Apple's Siri or Amazon's Alexa. Artificial Intelligence is defined as the imitation of human intelligence or intellectual processes by machines, especially computer systems. These processes include learning, reasoning, and automatic correction.

An upcoming update for dating app Tinder will allow women to initiate all conversations with potential matches. During an interview with Marketwatch, Match Group CEO Mandy Ginsburg said it plans to add a "women-talk-first setting" to Tinder, where any time a woman is matched by swiping right, she starts the dialogue. The setting is similar to one found on rival dating app Bumble. The key difference is Tinder users can choose to flip this setting on or off. On Bumble, women always initiate the conversations.

The area of online machine learning in big data streams covers algorithms that are (1) distributed and (2) work from data streams with only a limited possibility to store past data. The first requirement mostly concerns software architectures and efficient algorithms. The second one also imposes nontrivial theoretical restrictions on the modeling methods: In the data stream model, older data is no longer available to revise earlier suboptimal modeling decisions as the fresh data arrives. In this article, we provide an overview of distributed software architectures and libraries as well as machine learning models for online learning. We highlight the most important ideas for classification, regression, recommendation, and unsupervised modeling from streaming data, and we show how they are implemented in various distributed data stream processing systems. This article is a reference material and not a survey. We do not attempt to be comprehensive in describing all existing methods and solutions; rather, we give pointers to the most important resources in the field. All related sub-fields, online algorithms, online learning, and distributed data processing are hugely dominant in current research and development with conceptually new research results and software components emerging at the time of writing. In this article, we refer to several survey results, both for distributed data processing and for online machine learning. Compared to past surveys, our article is different because we discuss recommender systems in extended detail.

Tinder is handing women more power on its online dating app with a new'ladies-first' feature. The new option allows women to choose whether or not to start a conversation, with their matches who are blocked from messaging them until they initiate the chat. The feature is similar to the ladies-first chat policy that forms the core policy of dating app Bumble, but unlike its younger rival, Tinder's version can be switched off. A Tinder executive revealed the upcoming feature in an interview this week, claiming the update aims to give users more choice in how they use the app. Tinder is handing women more power on its online dating app with a new'ladies-first' feature.

This story was delivered to BI Intelligence Apps and Platforms Briefing subscribers hours before appearing on Business Insider. To be the first to know, please click here. Chinese internet search giant Baidu credited its solid revenue growth in Q4 2017 to its mobile and artificial intelligence (AI) businesses, according to the company's earnings report. Revenue for the quarter jumped 29% year-over-year (YoY) to reach 23.6 billion yuan ($3.7 billion). In 2017, Baidu refined its focus and began restructuring its resources, shifting them from less profitable ventures to emerging segments such as AI, big data, cloud, and mobile, according to Baidu CEO Robin Yanhong Li.

Contrary to earlier reports, Facebook isn't going to debut its Amazon Echo Show competitor in May. Mark Zuckerberg's company has reportedly decided to delay the release of its Portal-named smart speaker and the other model that's currently known for its codename, "Fiona." DigiTimes recently learned from supply chain sources that Facebook won't be launching its highly anticipated Portal smart speaker -- internally referred to as "Aloha" -- this coming May. The company has opted to reschedule its debut because it still needs more time to perfect the device's acoustic quality and make some changes to its software. Instead of May, Facebook is targeting a mid-2018 release, with sources claiming that the device could most likely launch in July at the latest.