Researchers from University of Pennsylvania, Northwestern University, University of Maryland, Columbia University, and Emory University published a new article in the Journal of Marketing that provides an overview of automated textual analysis and describes how it can be harnessed to generate marketing insights. The study, forthcoming in the January issue of the Journal of Marketing, is titled "Uniting the Tribes: Using Text for Marketing Insights" and authored by Jonah Berger, Ashlee Humphreys, Wendy Moe, Oded Netzer, and David Schweidel. Online reviews, customer service calls, press releases, news articles, marketing communications, and other interactions create a wealth of textual data companies can analyze to optimize services and develop new products. By some estimates, 80-95% of all business data is unstructured, with most of that being text. This text has the potential to provide critical insights about its producers, including individuals' identities, their relationships, their goals, and how they display key attitudes and behaviors.

At the ongoing the In ter na tional Motor Show (IAA) in Frankfurt, technology company Continental, together with the French company EasyMile, of which Continental has been a shareholder since 2017, are demonstrating the mobility of the future -- quite literally. Trade fair visitors can commute autonomously and powered only by electricity between two stops. The two companies have set up a demonstration track for a driverless Robo-Taxi between Hall 9 and the IAA Test Drive on the West Outdoor Area.German Chancellor Angela Merkel was one of the visitors to the fair who took a ride in the Cube robo taxi. The Robo-Taxi Cube is a Continental development platform for driverless vehicles technologies based on the EZ10 shuttle and driverless software from EasyMile. The shuttle service runs on all days of the fair during opening hours.

It sounds like something from an episode of Netflix series "Black Mirror" but the prospect of a virtual reality lover could be closer than you think. San Francisco-based tech company Virtual Mate has launched its VirtualMate system - the world's first virtual intimacy system. "VirtualMate is real-time interaction with a life-like virtual character," Jeff Dillon, the company's CEO and co-founder told British Newspaper Metro. "Real-time is the key here as all other attempts at this market are with pre-recorded content or a live cam model," said Dillon. "With the advancements in AI our system will know the user's name, habits, likes and dislikes."

In an age of uncertainty with the arrival of artificial intelligence (AI) tools and technologies in the healthcare field, many in the industry question how the addition of AI will impact their careers. One particular area is not immune to these changes: radiography. We spoke with Dr. Nick Woznitza, a reporting radiographer at Homerton University Hospital and a clinical academic at Canterbury Christ Church University in the United Kingdom, to gain some insight into what kind of effect AI will have on radiographers' tasks, workflow, and training and what the future holds for the field of radiography. Which routine tasks do radiographers perform that AI cannot assist with? Effective and compassionate communication is a core skill of all radiographers.

While tech giants like Google and Amazon build and invest in a multitude of artificial intelligence applications to grow their businesses, a startup has raised a big round of funding to help those that are not technology businesses by nature also jump into the AI fray. Element AI, the very well-funded, well-connected Canadian startup that has built an AI systems integrator of sorts to help other companies develop and implement artificial intelligence solutions -- an'Accenture' for machine learning, neural network-based solutions, computer vision applications, and so on -- is today announcing a further 200 million Canadian dollars ($151.3 million) in funding, money that it plans to use to commercialise more of its products, as well as to continue working on R&D, specifically working on new AI solutions. "Operationalising AI is currently the industry's toughest challenge, and few companies have been successful at taking proofs-of-concept out of the lab, imbedding them strategically in their operations, and delivering actual business impact," said Element AI CEO Jean-François (JF) Gagné in a statement. "We are proud to be working with our new partners, who understand this challenge well, and to leverage each other's expertise in taking AI solutions to market." The company did not disclose its valuation in the short statement announcing the funding, nor has it ever talked about it publicly, but PitchBook notes that as of its previous funding round of $102 million back in 2017, it had a post-money valuation of $300 million, a figure a source close to the company confirmed to me.

September 13, 2019: Brain-machine interfaces (BMI) applications, be they noninvasive (positioned on the body) or invasive (inserted into the body) significantly amplify the liability concerns that we are already familiar with through experience with, for example, implantable medical devices. The liability amplifying variable here is capability: the BMI's potential to cause wide-ranging harm is far greater than a legacy medical device. For instance, injecting a virus carrying nanobots to fight a disease or to carry out another mission is vastly different and carries an intrinsic operational risk that is vastly greater than implanting a pacemaker. Iterative liability, XAI, and the regulation of AI discussed in this post coalesce into a normative and legal safety net that can help mitigate the risks associated with BMI. July 19, 2019: Regulating AI behavior is necessary in order to mitigate harm.

A recent study, titled Milwaukee's Tech Talent Impact, found that nearly one-quarter of the total regional economic output was dependent on technology talent.

Between this, the GAN evaluation paper which happened to be really similar to a previously published paper by other authors, and DeepMind's PR machine while lacking in exhibiting the crucial details which make their Go models so good, I am definitely more and more disappointed in DeepMind ...

McDonald's [MCD] share price has gained 19% this year. The purchase of Apprente, which is aimed at automating its drive-thru operations, is a clear indication of a more tech-focused direction for McDonald's. Apprente's voice-based, conversational technology, "will allow for faster, simpler and more accurate ordering", McDonald's said on Tuesday. The Big Mac seller added that Apprente's technology could also be incorporated into mobile ordering and self-order kiosks. At the end of trading without disclosing the deal's financial terms, McDonald's shares were down 0.11% to $209.45.

Globally the healthcare industry is at an inflection point. While the industry continues to evolve at a rapid pace, there are related aspects to be taken care so as to ensure adequate consideration to the overall administration of accessible healthcare. Such aspects include regulatory norms that keep on changing at frequent intervals particularly in a globalised economy, lack of integration and data security as well as analytics. AI is already in use, there are various successful applications of AI in healthcare. But do we really require such AI applications? Let's find out where and how AI is helping healthcare.