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June 2, 2017

Artificial Intelligence - Unconventional use cases which will be reality soon.

As our CEO, Dr. Sikka says AI - Pursuit of building something intelligent is as old as humanity. It has grown leaps and bounds from the time AI was discussed in 1956.

Since its inception for what determined a machine to be "intelligent" AI has evolved overcoming challenges during 90's and has entered its golden era.

Increasing investments from Nvidia on GPU and Google in TPU has made Moore's law more and more relevant in current scenario. Availability of these powerful processing units have accelerated Deep learning, Automate Machine learning and artificial neural networks.

Startups have revolutionized AI world and are providing disruptive solutions to solve complex business problems, these days every organization is adapting AI in some or other forms, may be as simple as for customer segmentation, social integration, personalized offers, supply change or building complex solutions for solving human problems around cancer treatment, self-driving cars and many more.

Over next couple of years maturity of AI will rapidly increase and more unconventional use cases will turn into reality for consumption.

Here is first in series of few such use cases in my view as Infrastructure, platform and products becomes available to implement.

Emotional AI:

Deep learning is the study of artificial neural networks related to machine learning algorithm containing more than one hidden layer similar to human brain. Based on deep learning AI can distinguish between dogs and cats, good vs criminals but how do you feel when you are treated from a robot, how does families feel when AI is able to identify depression in struggling students?

Among lot of other things AI is able to recognize faces, turn sketches to pictures, identify voice and many more.  

Days are not far when Siri or Alexa can detect emotions based on the sound of your voice and have a conversation, recommend a therapy session or send an alert to your loved ones to order a bunch of flowers to make you happy.

As human beings, we understand contexts and empathy. Not many AI models have it today. Companies that can implement these into their technology will have more success.

AR Chatbot:

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Chatbot is common platform these days and everybody has a version of right from Microsoft, Facebook, Watson, Google or custom built.

People are probably going to be more drawn into engaging with chatbots which has personality; it has to be companion to whom people can engage with.

AI integrated with augmented reality can do wonders. If bots can be integrated with AI, emotional AI and AR then humans-robot interactions will take a huge leap forward. Humans often struggle with appropriate responses due to complexity of emotions, if technologies can decipher this then the output will be very impressive.

To be continued...

February 20, 2013

Big Data, Multimedia, Sentiment Analysis & Monetization

As I mentioned in my previous post, Big Data must create value - real and tangible economic value for it to be meaningful. And it must do more than just what a traditional Datawarehouse could achieve. Taking structured transactional data, putting it in a Datawarehouse and mining it for statistical analysis to obtain customer insights is nothing new or revolutionary for all of us to spend so much time talking about. The maximum amount of data (and one with largest growth rate) that is being generated nowadays is unstructured and with cameras in every phone, a lot of this data consists of multimedia like video and pictures. Tagging these videos with metadata and annotations tries to put some structure around these large files. For example, when you watch a video on Youtube, how does it know what else to "recommend", what to "feature" and what to "suggest"? Youtube's search ranking algorithm tries to constantly stay ahead of the game by delivering the most relevant and engaging content, so as to optimise the return-on-investment for its advertisers. Similarly, TripAdvisor's ability to put structure around the large volume of its unstructured data (namely hotel reviews, pictures, ratings, etc.) is proving to be financially successful for both itself and its partners. One reality of all this large volume of data being created rapidly is how do you stay ahead of the game and continuously innovate to make more money than your competitors?

 

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For purposes of illustration, we can look at Hotel industry, its adoption of Sentiment Analysis and how it has used the technology to positively influence its room pricing abilities. Hotel industry is abuzz with something called Online Reputation Management. Companies like Radian6 (SalesForce Subsidiary in Canada), ReviewPro (Spain), Brand Karma (US) Hootsuite (US), ViralHeat (US) and SocialNuggests (US), ClaraBridge, SentiRate and TrustYou(with US based subsidiary called Review Analyst) along with the field's largest player TripAdvisor are all trying to tame the large volume of data consisting of hotel reviews in meaningful manner. Additionally, it is creating substantial all-round economic value. For hotels it's creating the ability for them to charge higher premiums compared to their competitors. For customers it is giving them the ability to get maximum value for their money. For technology providers, it is creating ability to offer a host of new age services both to the businesses like hotels as well as directly to customers. Larger technology players like Tripadvisor are minting money multiple ways. From offering value added services to customers by becoming the default site for hotel value comparisons (both price and reputation comparisons), they are able to sell digital real estate to the highest bidder for ad space as well as charging commissions to hotels for bookings generated from their website. In the end both the customer and the hotels get exactly what they are looking for -increased value for their money....

Monetization of Big Data is one of biggest challenge that the technology players are constantly working to solve and when done right, it unlocks tremendous economic potential for everyone...

Next imagine a world of video reviews (like Youtube) and picture reviews (hint: Pinterest) all getting organised and sorted to provide meaningful analysis for customers shopping the market for their ideal honeymoon destination or their dream vacation or just a weekend getaway... Tremendous opportunity with lots of money for everyone to make...

Big Data Enabled Enterprise

Larger enterprises have extremely high volumes of data, coming in at a rapid pace from a wide variety of sources. Without a proper Big Data solution, finding relevant relationships is like fishing in the dark. For chief information officers, priority is to enable their businesses to make better decisions faster.

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