Artificial Intelligence & The Ad Tech Industry: Between The Hammer Of Truth & The Anvil Of Fiction

An article about artificial intelligence
Artificial Intelligence

Today, you can easily guess what any two people in the advertising industry are talking about. Artificial Intelligence (AI). It is the trending topic everyone is talking about right now.

Wherever you look, you see indications for artificial intelligence in our lives. Whether through movies or branding of emerging businesses or even with doctors. Everyone is trying to gain your trust by emphasizing on artificial intelligence involvement in the services they are selling. Why? because it implies that there is no room for error.

Sanuto Kolay, senior VP of engineering at Turn has a different opinion. “While there is a lot of smart tech being applied in the industry, but we are still a way off from true artificial advertising advertising.” Moreover, Sanuto continues “Deep learning, machine learning and algorithms, all part of artificial intelligence in the Ad-Tech story. It sounds good, but it is still mostly fictional.”

Artificial intelligence scientists and enthusiasts, describe it as the ability for learning, reasoning and understanding. Will machines ever demonstrate an intelligence equal to human intelligence? That remains a controversy.

The overall environment encourages companies to actually suggest and claim that their platforms are AI driven. Specialists in the artificial intelligence fields say that we are still a few years away from full artificial intelligence take over in the marketing automation. Experts in the artificial intelligence field comment about several platforms tested for the claim. AI’s position today in the industry is more of “enhanced machine learning”. It is for sure has automated some of the steps in the advertising industry for faster and more efficient results. We are headed in that direction for sure.

artificial intelligence and the Evolution of Machine

After world war II, the globe became more open, and technologies became more shareable. Men of the machine industry were always fascinated with the capacities of their machines. They always sought new ways to exceed entrenched limitations. Ever since this fascination started in the 1950s, Artificial intellegence leaders were always aware that limits of the machines are coming from rule-based devices purely. These rule-based devices, abide to rules that were created by people. Hence, the machine/device cannot behave more than being an information retrieving device.

Moving on the time line towards us. The focus shifted more to machine learning through the information retrieving processes. With time, machines are now able to detect patterns and repetitiveness through massive amounts of input data. Experts in the field are rushing now to apply deep learning. The reason is to enhance what was traditionally known as machine learning techniques/processes.

Enthusiasts and experts are speculating to receive more efficient results regarding pattern recognition when it comes to deep learning concept.

artificial intelligence and What is on the ground?

Four businesses in the world today are considered to be pioneers in artificial intelligence when it comes to understanding the spoken language to determine what users are actually looking and asking for; these companies are Microsoft, Google, Facebook and Amazon (Not necessarily in that order.)

For example, the Google voice search and Amazon’s Alexa for instance, are real life example of progression in this industry where machine actually interacts with the users and learns how they behave on the internet. Accordingly, the search of Google or even Alexa of Amazon, will provide results based on the analyzed behaviors of users. For the machine to deliver results that are with positive feedback in nature, the machine must be able to understand each behavior of each user separately and accurately.

The case is far more challenging in Ad Tech industry, and that relates to two variables; the first reason is inconsistency of behavior of the user. Therefore, application of deep/machine learning concepts are much more challenging to automate advertising substantially. The other variable of the equation is the “ROI Drive” that needs to be delivered to advertising companies. The ROI Drive requires more intensified prediction of user behavior.

Ad Tech companies today are trying to achieve this by applying more tweaks to the up and running algorithms for machine learning and by applying selective deep learning methodologies to enhance learning.

artificial intelligence From a business point of view.

Application of artificial intelligence in real life is not as easy as it is said as it requires teams of highly trained individuals and laser beam specific hardware. From a feasibility point of view, there is that point of probability of happening compared to the Cost vs. benefit correlation. Most of new businesses in the industry are attracted because of the increasing numbers of ad spend year over year (YOY) but the for most, momentarily, the investment will not generate the benefit that is desired. All of these facts put together, are resulting in large tendency to focus on improving currently up and running algorithms rather than to focus entirely to deliver the ultimate artificial intelligence technology where the human factor is eliminated.

If you have not read “Holistic Ad Serving“, we recommend it for you. If you are looking to read more about artificial intelligence we recommend the article on artificial intelligence published in Wikipedia.

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