Artificial Intelligence (AI) is a very trendy term right now and companies of all sizes and shapes are trying to find a way to exploit this technology for their own needs. Captivating and futuristic, Artificial Intelligence is indeed an essential tool to supercharge a business, enhance its business processes and improve the quality of the user experience.
The adoption and democratization of AI by industry giants (Google, Microsoft, Amazon, IBM, etc.) is an important driver of change for any technology company. Fortunately, Cloud computing and open source automatic learning APIs fill the gap in the technical gap that small businesses can face and allow them to take advantage of the opportunities that AI offers. More than ever, it’s time for small businesses to dive and start experimenting. The real challenge, however, is how to use these new resources well. Once again, companies can take inspiration from big companies like Google to develop their ideas. Here is what is relevant to know.
Democratize AI: an open world
This movement of democratization of the AI is a big change for companies. Two of the biggest efforts come from Google’s TensorFlow and IBM’s Watson software tools. Watson Group EMEA Director Paul Chon, explains, “we want to get to this point where the use of technology is simplified to the point where it is in the hands of business owners. We are therefore creating a cognitive platform that will be the API of choice in economics for building cognitive systems. We leave everything open and free. ”
TheVerge describes this even better by saying, “the difference between a command-line interface and a modern computer running OS” at the same time, the move from DOS to the graphical user interface was a radical change that had opened to the entire platform. The implementation of drag and drop of the AI will be a similar revolution.
So this is great news for all of us who are smaller than Google. On one hand, these companies see themselves as responsible for doing philanthropic activities to make the world a better place, but on the other hand, they also benefit from what they will gain by creating a world filled with data. Both of these factors were addressed in the Google Cloud Next Keynote this year.
Dr. Fei-Fei Li, Scientific Expert and Head of Artificial Intelligence and Machine Learning at Google explains: “We are witnessing the greatest improvement in the quality of life in history. That’s why enabling Machine Learning and Artificial Intelligence through Google Cloud is exciting. ”
Eric Schmidt, Executive Chairman of Google’s parent company , Alphabet , adds, “We see people using Big Data to analyze consumers, associate habits and target customers and all this really produces additional information worth millions! ”
As explained by Tom Simonite, Microsoft has become the giant it is today, because Windows is where the developers were going to reach PC users. Apple is now the largest Tech because the store App Store for iOS has made the iPhone a huge success. “A story based solely on charity would be a bit suspicious in this race to acquire customers and become the most important AI provider, but as we can see, the goal of the democratization of AI is to prove that it is a winning solution for all who use it.
Image recognition: See further
Image recognition is an essential skill currently offered by APIs with Artificial Intelligence. For example, the Google Cloud Vision is able to determine the content of images in a wide range of uses:
- Identify and report inappropriate content
- Identify and read texts in images
- Detect faces (without identifying them)
- Detect logos
- Recognize places
- Isolate dominant colours
- Suggest a crop in art apps
- Search and find similar images on the web
Other APIs for image recognition such as IBM, Watson Visual Recognition, Amazon Rekognition, Microsoft Computer Vision, Clarifai and CloudSight offer similar features.
Ideas for web applications are also numerous. Let’s say, for example, that you are creating an app or a website where you take photos of your users as feedback from their experience, showing their purchases, experimenting with beauty products or fashion items or their own travel photos. Thanks to the image recognition of the AI, a very large number of photos can be processed in order to group them according to their contents, to filter them according to the quality of the image or by other useful characteristics like blur and brand logos. Another facet of AI takes shape when users communicate their needs on an application through photos: an outfit they would like to wear.
Just imagine the potential in the health and medical industries. Artificial Intelligence and Machine Learning will undoubtedly provide considerable development and technical aids in radiology for individuals with cancer or tumors.
Conversational Spaces: Stimulating Environments
Natural language understanding (NLU), Natural language processing (NLP) and Automated speech recognition (ASR) have also seen impressive improvements and progress over the last year. The structures have been intelligently designed to analyze both written texts and audio files with a precision and understanding comparable to those of humans.
While this is not yet perfect, companies like Google are making great strides. The Google Cloud Natural Language API and the Watson Natural Language Understanding offer the possibility of obtaining feasible advice on product reception and user experience by taking metadata and determining feelings and emotions from the content, all this being possible in a wide variety of languages. The richness of this information can be derived from conversations on social media, messaging applications and conversations in call centers.
AI in generally is applicable to business because customer service, experience and customer relationship are major components of every business. Small businesses should make the most of these conversational technologies and use them to gain better customer insights, enhance their value-added and create a community around their brand in a meaningful way to ultimately solidify loyalty to their customers.
Location Detection: Anywhere, Anytime
Location and context APIs use the data provided by mobile detection devices to determine a user’s current actions and environment. The Google Awareness API has made it a priority to offer these services while respecting the privacy of the user and reducing the speed of battery depletion. In the field of location and context detection, collected data points include:
- Time (current / local)
- The location (GPS and contextual, ex: Starbucks, park)
- Activities (race, driving)
- Interests (subscriptions to nearby businesses)
- Earphones (on the head or in the ears?)
- Weather (current / local)
Location and context information offers a number of benefits for both users and businesses. Users can access information about everything in their area, record their own data as with training apps, find and communicate with nearby devices, and receive relevant notifications based on context. Businesses now have the new opportunity to connect or re-engage with customers and potential customers nearby. They may also have their own products or services that target users more appropriately, increasing the likelihood of satisfying consumers.
Imagine that you are a tourist in a new city and you suddenly find yourself in the rain when you receive a notification on your phone telling you that the pretty little business around the corner is selling umbrellas. Or, you use a recreational app and the AI of your location and context gives you the ability to suggest games or send notifications to the user when you detect a combination of certain contextual factors like sitting at home during the weekend. In addition to all these opportunities to personalize the context, companies will also gain valuable information from user data collected by device sensors.
There is a wealth of opportunities available to us today and I encourage you all to start thinking about how Artificial Intelligence can add value to your businesses. I do not think it is an exaggeration to see the democratization of AI as the great evolution that scientists suggest. We are only limited by our imagination when we use these skills and as skills become more refined and their execution is smarter, the range of opportunities for start-ups increases.