Audi Reveals The AI:ME, Its Vision For A Clean Autonomous City Car

“The AI:ME follows on from the AIcon, Audi’s study for fully automated long-distance travel. The clue, of course, is in the AI of the naming under which Audi says it is “bundling an entire cluster of innovative mobility technologies”. The car marque is using strategies and technologies from the field of artificial intelligence and machine learning so the AI cars combine vehicle intelligence, which makes automated driving possible. Audi says its AI systems are capable of learning and thinking, while also being proactive and personal.”

AI, Metro Bank and Personetics

How AI and Big Data will Transform Banking in 2019

Metro Bank is already doing that with Insights, an in-app money management tool that gives customers complete control of their finances. It alerts customers when there’s not enough money to cover a likely spend, recommends a top up before an automated payment is due, flags if a customer has accidentally been charged twice and alerts the customer when there has been any kind of unusual activity.

Metro Bank personalises advice with Insights

Metro Bank has gone live with Insights, an in-app money management tool, which uses artificial intelligence (AI) to generate bespoke tips and alerts.

The feature was developed with Personetics, a developer of an opt-in tool for predictive analytics of users’ spending patterns.

As well as alerts that anticipate customers’ spending, users will be able to see a breakdown of where their money goes each month, delve into individual spending categories, and receive bespoke tips about how to manage their finances, based on their specific circumstances.

Predicting the ROI of AI – Pitfalls to AI Adoption in the Enterprise (Part 3 of 3) – Daniel Faggella

  • If you work for a results oriented company, the topic of ROI will be central to your pitch for funding/capital. In this post Daniel from does a really nice job offering suggestions to get your project started. Here are a couple snippets. A link to the full post at the bottom.
    • “If you’re a banking executive and all you do is read banking press releases before you spend money with AI vendors, you are inevitably going to be investing in the wrong places. It makes sense to get a deep understanding of where a return on investment is being garnered with AI in your sector.
    • They’re re-imagining their business in the era of Amazon, and recommendations is a very big priority for them. If that’s the case, it’s worth understanding which facets of recommendations within the world of eCommerce and brick-and-mortar retail are actually garnering a return.
    • So when we’re looking for an ROI as a business, we might want to look for a technology we’re already shopping for that might be served via an artificial intelligence vendor in a way that is going to be relatively easy in terms of integration.”

    AI and the bottom line: 14 examples of artificial intelligence in finance

    “Builtin put together a rundown of how AI is being used in finance and the companies leading the way. 

    Credit Decisions

    ZestFinance –

    Scienaptic Systems – –

    DataRobot –

    Managing Risk

    Kensho –

    Ayasdi –

    Quantitative Trading

    Kavout –

    Alpaca –

    Personalized Banking 

    Kasisto –

    Abe AI –

    Trim –

    Cybersecurity & Fraud Detection

    Shape Security –

    Darktrace –

    Vectra –

    How AI is already influencing our shopping

    • “Pepper the robot, depicted above, has been used since 2010 and has become very popular in Japan, where it works as a customer service greeter and representative in 140 SoftBank mobile stores, with excellent results.
    • Product recommendation is another area where AI has brought dramatic changes: when Amazon introduced a new algorithm that provides tailor-made recommendations on the homepage, their sales increased by 29%.”

    Masters 2019: Tiger Woods finds a way to beat Artificial Intelligence, too

    • “This year for the first time, the Masters used enterprise-grade AI to capture every shot by all 89 players in the field to produce a three-minute highlight video for almost instantly at the end of each round.
    • Even more fascinating, the IBM Cloud stored and integrated data for each shot measuring the Crowd Roar and Player Gestures—hand, arm and facial movements—to create an overall excitement score.
    • At least four of his shots in the last round scored a perfect 1.0 in crowd reaction
    • The highest non-Tiger excitement score of the week belonged to Bryson DeChambeau’s hole-in-one at the 16th during Sunday’s final round. The Crowd Roar was .94 on a 1.0 scale, and Bryson’s body and facial reactions scored a perfect 1.0.”

    Getting Personal: How AI-powered personalization is helping retail bands stand out from the crowd

    • “With one in every five pounds spent with UK retailers now being spent online, experiences and brand are oftentimes the only way brands can differentiate away from the supply chain behemoth that is Amazon.
    • However, our research has shown that 63% of shoppers currently only shop with two to five different brands.
    • Personalisation isn’t just about inserting a name in an email or simple product recommendations. The latest AI and ML models are now being used to increase the relevancy of online personalisation to an audience of one.
    • Qubit has built numerous models, that when used in combination (model-stacking, so-to-speak), can build customer loyalty. These include the propensity to purchase, lifetime value predictions, category preferences, demand prediction, product recommendations and more.”

    Google’s AI is growing up

    “Deployment is the word we’ve been using most commonly in Cloud AI at the moment,” Moore said at a press briefing April 11. “It is all about taking a project from initial inspiration all the way through to it running for your business reliably. We’re no longer interested in the world of proof of concept being the main form of AI in product.”

    Over half of consumers will choose a chatbot over a human to save time

    • “Voice of customer (VoC) platform Usabilla has released a report showing that humans love AI and chatbots.
    • Almost three out of four (70 percent) of respondents said that they have used chatbots already, and of those who have not, 60 percent said that they would feel comfortable doing so.
    • However, almost one in five (18 percent) of customers say they always prefer to interact with humans when engaging with brands, regardless of the circumstance.
    • The survey found 35 percent of customers report the No. 1 reason they would use a chatbot would be to save time.
    • 54 percent of respondents said they would always choose a chatbot over a human customer service rep if it saved them 10 minutes.
    • Almost nine out of 10 (87 percent) customers report that they are satisfied or very satisfied with their ability to solve problems or answer questions on their own by using  a brand’s website.”

    The Hidden Mystery Behind Using AI to Create Awesome Customer Experience

    “Integrate this type of valuable technology into your eCommerce store. You can vastly improve your customers’ shopping experiences. There exist so many eCommerce brands across the web. But you risk losing business to another competitor just from small issues like slow loading speed or a confusing navigation bar. Design your entire online shop around the user. Make their experience as easy as possible. This includes guiding them towards products they may like. It also means creating clear menu categories and informing shoppers of potential shipping costs.

  • How AI Can Improve User Experience
    1. Integrate Chatbots
    1. Provide Next-Level Personalization
    1. Suggest Higher Quality Recommendations
    1. Improve Retargeting Strategies
    1. Predict Consumer Behavior”