Peering into The Future: Artificial Intelligence is The next Step in Online Advertising

A close look at the business expansion and diversification strategies of technology giants like Google, Apple, and Facebook have led me to a simple conclusion – Artificial Intelligence (AI) is trending and is going to dominate the future technological development. In the month of September 2016, Google acquired API.AI which developed ‘Siri’ like bot that can recognize speech, intent, and context of the commands. While in July 2016, Twitter Inc. had already acquired Magic Pony which works on improving User Experience through better image and videos search.

I was thinking about one thing, why the tech giants were spending crazy amounts to acquire these startups who were working on AI developments? Suddenly one notification popped up on my phone from online shopping marketplace Amazon and it was suggesting me the slashed prices of books on technical writing.I could connect things then! I understood that the era of suggestive advertising may be soon over with application of interactive advertisements.

Surpassing online AI already reached out of the home

A little research on AI led me to the world’s first artificially intelligent poster campaign which ran at a bus shelter outside Selfridges on Oxford Street in the month of July 2015. Though it appeared to be a simple poster for an instant coffee brand created by M&C Saatchi in partnership with Postercope and Clear Channel UK, a camera was integrated with the poster to capture peoples’ engagement based on their emotional reactions (happy, sad or neutral) after seeing the advertisement and the poster was writing creative copies at per those reactions.

I realized the AI has started spreading its influence quite a few years back on advertisement industry to give actionable insights of audience reactions, far from being suggestive; the campaign was a part of the trial which was putting AI to create self-writing ad campaigns in the interactive method!

SMS: Prices slashed by 30% for technical writing books - visit www.amazon.com today!

Coming back to Amazon notification again. I began to think how suggestive advertisements are influencing me? Are such ads still suggestive or the use of AI already has made them interactive? Data analysis is a part of AI and the big data analysis has made filtering of social sentiments, product pricing, predictive customer segmentation and sales forecasting easy. Added to the analysis and prediction is the use of image recognition, speech recognition, and content generation to push the boundary where creativity meets technology.

Is it advertising agencies or technology firms trying to add the human mental action or process of acquiring knowledge and understanding (through thought, experience, and the senses) to mechanical processes? Well, my understanding of AI in the ad creation tells me thatAI is trying to give importance to what works than what a human being thinks it should be. I doubt the creative heads and copywriters must have started scratching their heads!

Let us try to understand few aspects of how AI is putting forward result-oriented advertisements with complete and accurate view on performance against every ad displayed online:

AI is helping to identify pattern of users’ decision making

Millions of people are active online and they have different mindsets towards products, services, and related advertisements. It is difficult to analyze their decisions; when people click on ads there could be predictions following the activities thereafter but what about people who stay neutral? Here comes AI with its deep learning process. The high level of abstraction methodology is put to understand data; the process involves analyses of deep graphs with multiple processing layers to craft features that recognize attitude, intention and overall mindset of the visitors of any web page or website (in any version of display – desktop, mobile or tablet).Added to these is a deeper analysis of historical data available from different e-commerce sites.

Here the funda of AI lies in an analysis process that uses a mathematical structure which is inspired by biological neurons in our brain to interpret user description, for example, in buying or selling analysis.

AI is personalizing ads with self-learning algorithm

A good example of machines learning from mistakes and developing self-learning algorithm could be of Yann LeCun, director of AI research at Facebook, who taught a computer system how to recognize the differences between images of dogs and cats. Every time the machine fails to recognize the difference, he would correct it until the program figured out (learned) the reason for its failure.

Deep data mining to segment content per location, weather, time and even gender, age, profession or interest of the user have been made a projection of adverts possible in a personalized version. AI has started newly to add speech recognition with natural language, and image recognition alongside search analysis. Such processes help in customer segmentation with personalized outlook.

The aim is precision in advertisement campaign management

All the AI elements right from deep learning process to image or speech recognition aim at providing a complete and accurate view of advertisement performance. Detailed reporting enables optimized delivery of ads to the targeted audience. It helps the businesses to invest in buying or selling of advertisement space in real-time at per their value to users. The AI has also made real-time bidding of advertisement space to generate more revenue without affecting the interest of the advertiser/investors.



To conclude, some questions would always remain open for the use of mechanical reaction or the Artificial intelligence in an advertisement. Even if it becomes possible to write code for any unlimited number of situations to present personalized advertisements via AI, how long it will take to rectify wrong mechanical manufactured expressions (“It’s late excellent blend time” and “Bahio is the new steam” as found in AI driven poster ad campaign mentioned earlier)? Will it be possible to add a genuine emotional (human) touch in presenting copies and content of advertisement through machine/program? AI developers and users are hopeful. I found Neil ChapmanfromClear Channel (though he is basically from out of home ad agency)being quoted in Marketing Week: “We know that this is merely scratching the surface of the potential for artificial intelligence in the digital out of home arena and are very much looking forward to exploring the possibilities this kind of technology presents for advertisers in the near future."



image courtesy - www.tech.co/

video courtesy - www.thedrum.com/

video courtesy - www.finance.yahoo.com/

2016 Saw Large Corporates Finding Reasons to Acquire Promising Start-ups

In the year 2016,the world of Information Technology, along with us, sawthe giants like Apple, Google, and Intel acquiring promising start-ups Turi, Moodstocks, Itseez and the likes. Should we identify these as acts of killing the competition and competitor or gaining grounds in the field of nascent technology? Let’s script a drama around some acquisitions in anew unconventional structure.

Denouement (intention and outcome)

The general outcome of any acquisition and merger is the increased strength of acquirer and dilution of the acquired. Under the name of acquisition the act of silent butchery of growing competitors and establishing market supremacy take place. It would not be an exaggeration if we mark the year 2016 as breeding and budding time of machine learning, artificial intelligence and similar technologies that grew and showed its promising future from the nests of IT start-ups?

Let’s have a look at the activities of some giant corporates who acquired many start-ups. These may help us to understand what made them acquire rapidly growing and promising start-ups. Salesforce alone acquired 12 companies spending $5 billion; in other words, every month it acquired one company!

(set –Data Analysis, Artificial Intelligence, Machine learning)

Act I, scene I:
Intel Corporation acquired computer vision and machine learning start-up Itseez in the month of May 2016 as part of its strategic shift from PC chip to cloud computing, the Internet of Things, and analyzing data from devices.

Scene II:
It seemed as if Google was waiting for a few months to analyze the outcome of Intel’s acquisition. In the month of September, it acquired API.AI which developed ‘Siri’ like bot that can recognize speech, intent, and context of the commands.

Act II, Scene I:
In Jan 2016 Apple acquired Emotient that works on Artificial Intelligence to develop technology for detecting emotion from facial expressions. After a few months, in July 2016, Twitter Inc. acquired Magic Pony which works on improving User Experience through better image and videos search.

Scene II:
How can any other company think something that relates to search bypassing Google! Yes, Google could not tolerate Twitter’s move and in the same month of July 2016, it acquired Moodstocks which develops machine-learning based image recognition technology.

Prolog (break the convention)

An Acquisition is no sudden incidents only from the likes of Google, Apple, Twitter or Intel. Cloud computing and king of CRM, Salesforce, was found to acquire PredictionIO in the month of February 2016. The start-up develops an open source-based machine learning server which would strengthen Salesforce’s grip in machine learning and data analytics. It also repeated the acquisition in April 2016 by acquiring MetaMind which works on predictive analysis to predict outcomes for language, vision, and database task. The end of the year 2016 saw Salesforce acquire Twinprime which works on app User experience optimization. Hat’s off to the aggressiveness of Salesforce for going to the ‘extreme’ level of acquisition (more than 40 acquisitions) which forced them to post a negative profit.

Image courtesy www.appannie.com