Walmart’s startup incubator, Store No. 8, is working on an under-the-radar project, dubbed Project Kepler. This effort aims to reimagine the in-store shopping experience with the help of technologies like computer vision.
Multiple people familiar with the project tell Recode that one goal of the initiative is the creation of physical stores that would operate without checkout lines or cashiers — in a similar fashion to Amazon’s futuristic Amazon Go store, which was announced a year ago but has yet to open to the public.
Joe Lobo (Inbenta) and Jordi Fontseca ask: Which language is the best for your chatbot? As they write, Facebook, Slack and Telegram all support the most popular languages, while API platforms such
as Dialogflow, LUIS and wit.ai offer SDKs for the majority.
While it is arguably much simpler to use spaCy and TextBlob, understanding how NLTK works provides a solid grounding in order to help grasp the concept of sentiment analysis. Using NLTK, we can train a bot to recognize sentiment by first examining a set of manually annotated data. We create this by taking three lists: one of positive comments, another of negative comments and a test list that contains a mixture. The more examples we have on each
list the more reliable the sentiment analysis will be. The manually annotated data will test the exactitude of our classifier.
Al already transforms business models and opens doors for unprecedented enterprise innovation. Rick Rider writes that by automating monotonous tasks, AI enables employees to focus efforts on critical thinking and higher-level tasks. We’re already seeing this happen with voice-driven software navigation, which automates tasks with simple commands and removes the need for deep, multi-level UIs to complete jobs or find answers.
LinkedIn released data on the jobs that have been experiencing the most growth in numbers over the past few years, and it’s fair to say that tech and data skills are among the fastest-growing categories — especially those that involve working with data.
Topping the list is machine learning engineer, a job category that has grown 10-fold between 2012 and 2017. This was followed by data scientist, multiplying by a factor of seven during this same time. There are also six times as many big data developers, as well full-stack engineers.
When Jewelry.com partnered with omnichannel personalization technology firm, Dynamic Yield, to integrate personalised product recommendations on its website, it saw revenue increases per visitor of 39% from the homepage, 13% from product pages, and 18% from cart pages.
The key, according to the team, was not just to focus on the usual ‘most popular’ or ‘similar to current item’ suggestions, but instead to turn to machine learning to automatically select the most effective strategy for each user.