The North Face, Macy's and 1-800 Flowers are some of the brands collaborating with the supercomputer to glean insights from the increasing mounds of data they collect from customers. Its name, "Gwyn," stands for "gifts when you need." Gwyn is not a chatbot, though, said vp of marketing and customer experience Jon Mandell. "No two conversations are the same." Here's what 1-800 Flowers has learned, nine months in.

Many Collaborative Filtering (CF) algorithms are item-based in the sense that they analyze item-item relations in order to produce item similarities. Recently, several works in the field of Natural Language Processing (NLP) suggested to learn a latent representation of words using neural embedding algorithms. Among them, the Skip-gram with Negative Sampling (SGNS), also known as word2vec, was shown to provide state-of-the-art results on various linguistics tasks. In this paper, we show that item-based CF can be cast in the same framework of neural word embedding. Inspired by SGNS, we describe a method we name item2vec for item-based CF that produces embedding for items in a latent space. The method is capable of inferring item-item relations even when user information is not available. We present experimental results that demonstrate the effectiveness of the item2vec method and show it is competitive with SVD.

On the flight back to San Francisco, I could not help wondering, will retail ever be the same? The National Retail Federation is the cream of the crop of retail events and New York never seems to disappoint. A massive and immersive experience, NRF seems to find the golden mean between human interaction, thought leadership and the ultimate display of retail tech booths, including a great mix between both big and small exhibitors. To say that #nrf17 is a global event would be an understatement, as retail professionals from over 90 countries attend. Our team at Star Cloud noticed a lot of innovation in tech this year (emphasis on data & tech) that's shifting the retail industry quickly into the 21st century.

Alphabet Inc. subsidiary Google's (GOOG) artificial intelligence (AI) assistant is failing to catch on. A Bloomberg report this morning states that Chinese smartphone manufacturer Huawei, which uses Google's Android operating system for its phones, is developing its own voice-activated AI assistant. According to the report, Huawei's AI assistant, which will use local languages in China for communication, is targeted at the Chinese market and is intended to compete with the likes of Apple Inc.'s (AAPL) Siri and Amazon.com, This is the second such announcement after Samsung Electronics Co. Ltd (SSNLF), which also uses Google's mobile operating system in its phones, announced its own digital assistant last year. While Samsung has the largest number of mobile phone shipments, Huawei is ranked third. Huawei has also announced that it will pre-install Alexa, Amazon's voice assistant, on its Mate 9 phones.

"Data Scientist is the sexiest job of the 21st century" So, what exactly is data science and why all the hype around data scientists. Frankly speaking, multiple job descriptions and explanations of the same role make it harder for businesses to clearly understand what a data scientist is and does. This complicates the ROI business leaders expect when investing in them. To me, data Science involves mining actionable and sensible insights from multiple data formats by applying mathematics, statistics, machine learning, etc. Data scientists typically analyze data sets, or data depositories that are maintained within an organization and/or they analyze data scraped from publicly available sources.

With Amazon, Facebook and Google all adopting an open source approach to development of their artificial intelligence (AI) services, what could this innovation mean for a family shopping on the High Street? An end to Saturday morning parking mayhem – having to spend half an hour queuing to get into a shopping centre car park only to find out the only spaces left are on the hundredth floor can be a miserable start (and end) to a Saturday shop for the whole family. An AI personal assistant could reduce the friction of this inconvenience by reserving a suitable car parking space at the shopping centre in advance, based on the family's store preferences, accessibility requirements and other factors, like forecast weather. It can then send the reserved space location to the family's in-car GPS and automatically pay for its ticket. The more an AI can effectively integrate or communicate with other systems the greater the convenience for customers.

Retailers need to embrace next generation technology such as artificial intelligence (AI) and augmented reality (AR) if they want shoppers to continue using their apps, new research has found. The study found that nearly 30% of consumers would like to see more innovation in mobile apps, so that they provide a better, more personalised shopping experience. Shoppers surveyed said they would be more likely to download a retail app if it featured technology that helped them to make a buying decision, or let them preview products before purchasing them. The report, by mobile app developer Apadmi, surveyed 2,000 consumers who use retail apps to find out what they expect from apps and what they would like to see more of in the future. More than a quarter (26%) said they would like to see retailers implement AI tools in shopping apps, particularly if they help to remember past purchases and recommend products and deals based on shopping history.

A machine that can handle basic tasks -- think the self-service checkout at Walmart or an ATM machine -- is a better option for one particular segment of the population. That's right -- introverts already know the benefits of machine learning. Full disclosure here: I have not paid a human for gas in about eight years. There have been a few times when I go into the gas station, but it's always to scour around for donuts or to find the restroom. A few friends and relatives are in the same boat.

The retail space is changing drastically through the evolution of technology, such as artificial intelligence (AI), which can offer retailers better control over stock flows and better customer service. This technology, and in particular machine learning, can step in to help retailers cater to the needs of their customers in smarter ways. Retail goods, even the most niche products, are becoming more and more commoditised and price parity means retailers have to look continuously for more innovative ways to keep customers loyal. A high-end jewellery retailer, a sporting goods store and a grocer all have very different target markets and their customer's behaviour patterns are very different, but the beauty of machine learning, an emerging technology, is that it quickly adapts to any type of environment. Machine learning is a form of AI that allows computers to learn without being programmed.

The answer is a resounding no! Fortunately, there's still time left to prepare for one of the biggest digital transformations of all time. Reports suggest that a collection of the world's leading tech companies, including Microsoft, Apple, Samsung, Huawei, LG, Acer, Intel, Meta, Magic Leap, and ODG are all planning to double down on mixed reality (MR) this year by bringing affordable devices to the masses. In particular, excitement continues to grow over speculation that Apple may be ready to unveil its MR device in the coming months to coincide with the 10-year anniversary of the iPhone. Tim Cook has recently made bold statements about augmented reality (AR), indicating his company will have a major horse in the race. Many analysts believe that horse will be the dominant front-runner.