Are Machines Better At Advertising Than Humans?
At the Marketing AI Institute, we read dozens of articles on artificial intelligence every week to uncover the most valuable ones for our subscribers and we curate them for you here. We call it 3 Links in 3 Minutes. Enjoy!
Machines Succeed at Crazy Advertising Tactics
If you’ve ever worked on an ad campaign before, you know that audience segmentation options are practically unlimited. While this means vast opportunities for advertisers to hit their target audience, it also makes it nearly impossible to know exactly which audience subsets to target. Lucky for us, this is where machine learning shines.
VentureBeat’s recent machine learning article highlights some of the craziest wins advertisers have had since letting machines take over their ad spending.
One company ran a video game advertisement without actually showing any visuals of the game itself. Instead of flopping, it generated a huge amount of interest and conversation with a certain type of gamer. John Koetsier, VP of insights for Singular expands:
“You can try many, many things, because you can let the machine [learning] then figure out in real time what’s generating impact.”
This capability has become more valuable since GDPR and other privacy acts have been put into place.
Applied computer vision company GumGum can target audiences simply by using website session context. For example, for its client Jeep, they were able to analyze images on webpages and place pop-up ads for the Jeep Cherokee over a portion of any Toyota RAV4 images (which users can click to close).
AI and Machine Learning Experts Are Most Concentrated in These 5 Cities
What do New York City, San Francisco, San Jose, Washington D.C., and Boston all have in common? They’re hoarding the most AI and machine learning experts.
According to the study, 11.6% of AI/machine learning jobs are in New York City, 9.6% in San Francisco, 9.2% in San Jose, 7.9% in Washington D.C., and 6.1% in Boston.
Although in second place, San Jose currently has the most job openings for algorithm engineers, computer vision engineers, machine learning engineers, and research engineers.
If your skillset aligns with one of these positions, you could be cashing in very soon. According to Dice’s Salary Calculator, an AI expert with five years of experience could “can earn as much as $121,000 per year.” Some researchers have been known to make between $800,000 and $2,000,000, according to The New York Times.
Right now, McKinsey & Company estimate there are less than 10,000 AI and machine learning experts in the field, which results in these competitive salaries.
13 Artificial Intelligence Terms Marketers Should Know in 2018
Our friends over at HubSpot put together an extremely helpful guide on the 13 artificial intelligence terms all marketers should know. The full list can be found here. Below, check out the ones we think are most important.
Artificial Intelligence: The science behind making a computer do something that would normally require human intelligence.
Deep Learning: Similar to the human mind, scientists refer to this type of AI as the “neural network” of machine learning. With this, machines can discover complex patterns by using layers of correlations.
Machine Learning: Making machines smart by feeding them loads of data and letting them learn over time through experience. An example of this would be Netflix. The more movies and shows you watch and rate, the better Netflix’s algorithm can deliver personalized recommendations.
Natural Language Processing (NLP): The act of machines learning to “understand” text and voice commands, like when using Amazon Alexa or Siri.