A few tips on where to put the AI into your product

The future scenarios about artificial Intelligence outsmarting humans is certainly a big topic. But how does the AI improve our lives today?

Current possibilities of building ”smart applications” are better than ever. When the machine learning is happening under the hood, on the surface it delivers experiences that are “not surprising at all”. Well, isn’t that the ultimate goal of a technology? Let’s take a look.

Analysing the market and saving your money

Airbnb uses machine learning to help hosts make as much money as possible by analyzing market demand. It will set up a default recommended price and the users can review it and see the average price of the market. You could sit and analyse it manually all day, or let thr magic work for you.

Price change forecasting of flight fares and hotel prices are ever-changing and vary depending on the provider. Fareboom monitor sends out timely alerts with hot deals currently in high demand in the travel industry.

Helping you to be more specific

You no longer have to think to find the right words. Just start typing and select from the suggested options, as the algorithms “read your mind” based on data from your history and the history of others.

Amazon search suggestion

Google images related categories

Making sense of tons of data

Analysts want to be alerted when something important happens. Take transaction monitoring for example — tons of data are recorded, but only a few of importance needs to be reviewed. The AI highlights the relevant alerts for review, which saves a lot of time.

Anti-money laundering application by SAS

Automatic translations

Machine learning increased the efficiency of Google translations. Facebook takes it a step further by automatically translating posts in a foreign language; but only when having high confidence in the match. Otherwise it shows an original post and presents you the translate button below.

Displaying information based on context

“In our Foursquare City Guide app, we use machine learning in tip ranking. We spent some time manually extracting signals about tips, such as: What is the sentiment in the tip? Does this tip have a photo? How long ago was it written? How many upvotes has it received? etc. We calculated these features and then had tips ranked by an audience so we could understand how each tip is valued by real users. Those tips were ranked, and then we applied that learning to all of our tips. That’s why City Guide tips aren’t ranked by date or popularity, but by how valuable they are to our users. So tips are spot-on and relevant as often as possible.” — Jeff Glueck, CEO of Foursquare

When you search for craft beer foursquare highlights and promote searched keywords in interface

Presenting you engaging information

When creating a new account, Pinterest is interested in your taste. Profiling starts while on-boarding and models are able to provide you the most engaging and relevant information. A friend of mine recently said “the people on Pinterest have good taste!” I replied, “Actually, it’s just the AI showing you the things you like”…

Pinterest onboarding new users

Spotify brings you mixes with music you will like on daily basis

On-boarding is only the initial part. Your “personalized profiles” are adjusted based on all your activity. Quora has implemented more advanced feedback loops for machine learning, and when you downvote a question in the feed, they take it really seriously.

Quora is serious about its tailored content in your feed.

Understanding a language

Imagine you are planning a trip to Iceland. You have browsed through some articles, and then the AI suggests the name of the place that you have trouble spelling. Converting raw text into structured data is used to improve interaction between user and device.

iOS Keyboard understand context and provide suggestion based on that.

Apple mail when finds contact information in your mail automatically highlight it and user can add it.

Recognizing you, your friends and people in general

You are taking photo of your friend… pull out the/ your phone and shoot while the automatic face dedication selected point of the camera focus for you. Google has recently launched a camera that takes photos constantly and uses AI to present you only the best ones.

Google Clips

Face recognition for unblocking phone

Recognising objects

Similar like faces, but just for things…

Hilarious application will tell you if you see hotdog or nothotdog. Smart, huh?

Pinterest is able to identify objects and find similar ones.

Google photos recognize photos and allow you search by keyword

Highlighting the data on the maps

DroneDeploy uses data from drones to highlight specific parameters like terrain evaluation and help users to make a more informed decisions.

Machine Learning brings great possibilities for designing the great experiences. Companies like Facebook, Twitter, Instagram, Quora, Netflix, Spotify, Google, Amazon already use it. Almost all internet products these days end up with the main interface driven by it AI.

So, what about yours?

Published on February 2018