“Adobe Sensei, our AI and ML technology, is purpose-built for digital experiences and focuses on three intelligence domains: creative, content and experience. Today, it is powering dozens of features across all of Adobe’s products, but I am most excited about what is coming next. For example, we are working to infuse AI into new mediums like augmented reality (AR).”
There are many uses for AI including eCommerce, financial services, medical and military applications but this is one I’m truly excited about…leveraging AI to dominate your family and friends in your March Madness bracket.
For those that are new to my blog, I’ve been in Austin since 2010, but I call Indiana home…where basketball is a religion (queue the movie Hoosiers).
So, I did some research and discovered that Adobe Analytics is attempting to help basketball fans by leveraging their AI and Machine Learning to #HackTheBracket.
Pick your match-up. Predict the winner.
What impact does season-long performance have at the big tournament? We use Adobe Analytics to project head-to-head outcomes and give you a bracket-busting edge.* Select a team from each dropdown list to see the probable result.
Download the full Adobe tournament prediction powered by machine learning, artificial intelligence, and other marketing buzzwords (no promises you’ll beat your family and friends if you copy this).
With that in mind, I’m leveraging these picks as an “AI Experiment” but I do so with great trepidation, because the model is predicting all 4 – #1 seeds to make the Final Four.
Update: I just discovered via a new source (NCAA.org) that all of the #1 seeds making the Final Four has only occurred once in history. Check out this link of details.
One of the best aspects of transitioning to a new calendar is the year-in-review pieces written by popular technology blogs and publications. This morning I discovered a post written by Ana Păstrăvanu of thepaypers.com.
Here are just a few of the key take-always. Check out the post for full details.
In Pakistan ecommerce was expected to surpass USD 1 billion in 2018, propelled by the increase in broadband penetration and the rise in the number of online payment merchants.
In India, ecommerce sales reached USD 32.70 billion (an increase of 31% compared to 2017), with growth being driven by Amazon, Flipkart, and Paytm Mall.
In January, Amazon opened Amazon Go, an automated and checkout-free grocery store in Seattle.
Walmart’s take on cashier-less checkout, Scan&Go, started being tested in stores in the US.
A study released by Juniper Research found that global retailers’ spending on AI would reach USD 7.3 billion per annum by 2022.
Flipkart acquired Liv.ai, an India-based AI-led speech recognition software startup, while Walmart partnered with Microsoft for a wider use of cloud and AI technology.
In August, Visa has created a new category of payment aggregator, the marketplace, and updated the requirements that have to be met in order to qualify as a marketplace under Visa’s rules.
2018 marked the world’s biggest purchase of an ecommerce company, the acquisition of Flipkart by Walmart, in May, for USD 16 billion.
Another important announcement regarded Adobe’s intention of acquiring Magento Commerce from private equity company Permira for USD 1.68 billion.
Another important investment in 2018 is marked by Alibaba, which increased its control of Lazada, investing USD 2 billion into the business.
“Web traffic on smartphones and tablets will, for the first time, surpass desktop (at 54 percent and 46 percent respectively).
Mericle’s points about creating “easy shopping experiences” and “providing a seamless customer journey” are especially important in the ecommerce space, where more and more retailers are leveraging AI-powered customer engagement platforms to create individualized digital shopping experiences.”
“Away from kitting the CEO, Adidas used Dreamforce to launch a new AI-enabled shopping app designed to offer a personalized experience for consumers, based on their individual style and buying patterns. To pay for items, customers can tap-to-buy, using a credit card or digitally via Apple Pay or Android Pay.
Once a purchase has been made, the customer can track their order, and chat with customer services regarding it. Such chats will intially be with a human being, but within a few months, Adidas will introduce chat bots to handle simple queries, with human intervention only when things get more complicated to deal with.
From Adidas perspective, the important thing is that the app’s AI capabilities will learn as it goes. From interaction with a consumer, the app will pick up more and more data about what he or she likes and doesn’t like and start to make recommendations, encouraging upsell opportunities.
With the power of the Service Platform and Einstein built in, when you talk to those agents, they’re smarter and more productive than ever before. Einstein bots are transforming the world of service. They are the ultimate helper. Using Salesforce Einstein bots to power their service interactions, Adidas is able to do everything. It is able to handle all those repetitive tasks, those actions, whether you want to make a return, or you want to exchange something.”
“Join us on Thursday, Nov. 16 at 2 pm EST/11 am PST for “The Rise of the AI-Empowered Marketer: Engaging Smarter to Grow Revenue,” a free live webinar, where we’ll explore what you need to know about AI for marketing success.”
“Research firm, Forrester, predicts that online sales will skyrocket to $459 billion in 2017, totaling 12.9 percent of retail sales.
The vast majority of merchants, however, spend a significant portion of their time just trying to figure out how to compete with Amazon. Understandably so, considering that the retail behemoth is poised to garner nearly half of all online sales this year.
In an effort to contend, many retailers are trying to set themselves apart by creating deeply personal and highly curated experiences online. Most of these are powered by AI technology.”
“Go to any industry conference, blog, meet up, or even just read the popular press, and you will hear and see topics like machine learning, artificial intelligence, and predictive analytics everywhere.
Because many of us don’t come from a technical/statistical background, this can be both a little confusing and intimidating.
But don’t sweat it, in this post, I will try to clear up a some of this confusion by introducing a simple, yet powerful framework – the intelligent agent – which will help link these new ideas with familiar tools and concepts like A/B Testing and Optimization.”