Artificial Intelligence (AI) is changing everything from marketing to healthcare. And this holiday season is the beginning of the future for how marketers will leverage AI to better understand, connect with, and create superior experiences for consumers. To better appreciate the impact that AI is having on retailers, I connected with IBM's first CMO, Michelle Peluso. Peluso has a strong background in retail, having served at the CEO of Gilt as well as the Global Consumer Chief Marketing and Internet Officer at Citigroup. Peluso provides her thoughts below on how Watson's AI capability is changing the way retailers impact the consumer shopping experience.

AWS has announced three new features for its artificial intelligence portfolio at re:Invent 2016 in Las Vegas this week. Artificial intelligence is a development which could have wide ranging impacts on businesses throughout the world, and while many have been sceptical about its effectiveness the technology is starting to make waves. Google recently announced a few changes to the way its translation tool works with AI, IBM's Watson seems to be making progress constantly and Salesforce's Einstein is paying off with the company growing year-on-year. Considering the normalization of artificial intelligence and growing acceptance in the technology world, it wasn't going to be long before the public cloud leader started making itself known. And sure enough just in time for Christmas, the AWS team has put forward three new features for developers to play with.

Which authors of this paper are endorsers? Disable MathJax (What is MathJax?)

It's one thing to create computers that behave like brains, but it's something else to make them perform as well as brains. Conventional circuitry can only operate so quickly as part of a neural network, even if it's sometimes much more powerful than standard computers. However, Princeton researchers might have smashed that barrier: they've built what they say is the first photonic neural network. The system mimics the brain with "neurons" that are really light waveguides cut into silicon substrates. As each of those nodes operates in a specific wavelength, you can make calculations by summing up the total power of the light as it's fed into a laser -- and the laser completes the circuit by sending light back to the nodes.

For a long time, hiring in India (or for that matter anywhere in the world) meant candidates would have to be active on job portals and scout through the various jobs listed. It would then be up to the recruiter of a company to go through all the CVs and schedule interviews with potential candidates and the entire process took around four to five months. As companies run into increasingly competitive talent markets, recruiting costs and cycles are escalating. To overcome these challenges and help businesses meet their goals, recruiting teams need radically new capabilities and technologies, something Bengaluru-based startup Belong is helping companies to achieve. Basically, the premise is simple: for an employer and potential employee to connect with each other they must connect on something beyond skills and experience.

The solution uses artificial intelligence technology to help financial institutions increase the accuracy of real-time approvals of genuine transactions and reduce false declines. This is the first use of AI being implemented on a global scale directly on the Mastercard network. Current decision-scoring products are focused primarily on risk assessment, working within predefined rules. Decision Intelligence is a radical new approach that goes much further. It takes a broader view in assessing, scoring and learning from each transaction.

Thanks to the relentless work of dedicated engineers, artificial intelligence, or AI, becomes smarter by the day. But while computers become better at replicating human tasks, reading comprehension, an area where machines have yet to catch up, is declining among young people, suggesting a chilling future in which AI may put people out of work. That is why Noriko Arai, a mathematician at the National Institute of Informatics, decided in November to change the direction of her project from teaching an AI to pass the entrance exam for Japan's most prestigious school -- the University of Tokyo, better known as Todai -- to focusing on improving the reading comprehension of future generations using AI technology. "AI engineers have always said that humans don't have to worry because only menial jobs will be taken over by machines. But what about the people who do such jobs?"

In an evaluation of retinal photographs from adults with diabetes, an algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy, according to a study published online by JAMA. Among individuals with diabetes, the prevalence of diabetic retinopathy is approximately 29 percent in the United States. Most guidelines recommend annual screening for those with no retinopathy or mild diabetic retinopathy and repeat examination in 6 months for moderate diabetic retinopathy. Retinal photography with manual interpretation is a widely accepted screening tool for diabetic retinopathy. Automated grading of diabetic retinopathy has potential benefits such as increasing efficiency and coverage of screening programs; reducing barriers to access; and improving patient outcomes by providing early detection and treatment.

A lot of Machine Learning (ML) projects consist of fitting a (normally very complicated) function to a dataset with the objective of calculating a number like 1 or 0 (is it spam or not?) for classification problems or a set of numbers (e.g., weekly sales of a product) for regression ones. Yes, it's all about numbers and loads of operations which a computer is very good at. Consider the gender recognition by voice dataset which can be found in this Kaggle page. The objective with this dataset is, when given a speech signal, to identify whether it is from a male or female. This challenge falls under the category of a classification problem.

The Telegraph has proclaimed: "The end of apps is here…" TechCrunch, Mashable, VentureBeat, and others also shared their belief that mobile applications as we know them are a dying breed. But how did mobile apps become endangered? Recently, IO's creators changed the app's name to Luka and added several little helpers, meaning it's now in charge of 12 other bots: Foodie (for restaurant recommendations), Weather, Wiki, Video, Gif, Pic, News, Founders, Search, Calculator, Quiz, and QuestHero. As of July 2016, Luka had around 5,000 downloads on App Store, with a monthly income of less than $5,000 (according to Sensor Tower). Nevertheless, having announced the recent close of a $4.42 million Series A funding round, Luka's creators are more than optimistic about the app's future.