If 2017 saw artificial intelligence receive mainstream attention, 2018 will surely be a year of solidification. The general public are starting to garner a better understanding of how AI works and impacts their daily lives.
Hopefully more knowledge lends itself to even more positive coverage and less doom mongering around the so-called robot uprising. With minds and money pouring in at an incredible rate, AI should reach even greater levels of achievement.
It’s expected to double the economic growth rates of the 12 largest developed countries by 2035. From machine learning to deep learning to neural networks, here are the techniques that will push technological boundaries in 2018 and beyond.
1. Neural language
Despite the huge improvement AI has seen over the last few years, getting it to understand language has proved tricky. In the past, AI has been able to understand distinct commands, with ‘figures of speech’ and ‘tone of voice’ often lost on the tech.
With chatbots playing a more prominent role in the customer experience, the tech needs to attain a certain level - one that makes it impossible for humans to tell the difference. Chatbots need to recognize the subtleties in human speech.
Giants such as Google are investing more time and resources into the tech, and 2018 looks promising. It could be the year that AI finally cracks human language and is able to adapt and understand the nuances in our conversational tones.
2. Emotion recognition
After the intricacies of the human language, AI’s other big hurdle to clear in 2018 is the ability to recognise emotion. For all the things AI can do, empathy and a clear understanding of emotions is not something it has been able to replicate to great effect.
Again, mastering these techniques will play a major role in any interaction directly between AI and humans. If AI can determine when someone is getting upset, frustrated or angry, it can adapt its own way of thinking to deal with the issue.
The results could go as far as producing AI counsellors to help mental health experts achieve a better understanding of their patients.
3. Image recognition
84 percent of communications on the internet will be visual by the end of 2018. The importance of image recognition can’t be understated. The value of visual content is through the roof, which means it’s important that brands can select images with minimum fuss.
Image tagging cuts through the noise and provides those searching for content with an easy way to get the photo they want. The engineers at Lobster use a large volume of correctly marked data and rely on deep learning algorithms to distinguish features on images.
The result means that people find the content they are looking for in the fastest time possible. Head of Machine Learning at Lobster, Vladimir Pavlov, says, “We are actively creating an AI system that will understand not only what should be on the image, but also the meaning of the scene and the style of the image. We create our own algorithms for computer vision and data analysis. We use classical machine learning approaches (SVM, Xgboost) and neural networks (TensorFlow, Caffe, Torche) for problems solving.”
4. Marketing automation
Marketing divisions have perhaps been one of the biggest benefactors of AI. Clever algorithms have given them the ability to personalise marketing campaigns and create better relationships with their audience.
55 percent of marketers are sure AI will have a greater impact on marketing than social media has. That is quite the statement, but also shows the level of faith placed in the tech. We’re already seeing direct communications from big brands that include our name. But the level of personalisation will grow further.
AI engines can provide everyone with their own personal shopper, while predictive customer services will allow brands to understand how and when customers will get in touch with them about products.
5. Data-driven machines
Most companies rely on data to provide accurate information for a number of aspects, including future projections. Machine learning is becoming an increasingly popular way to get data, and businesses will continue to use it to provide trends and analyze information.
We could see up to 80 percent of companies relying on data insights from machine learning in 2018. AI is able to sift through information at a much faster rate than humans, which should free up the human mind for more creative tasks.
Machine learning is perhaps the must-have accessory in 2018 for any brand hoping to utilise the power of data. In fact, we may even see new departments arise across companies. Don’t be surprised to see AI data strategy divisions in the near future.
6. More AI in creativity
Creativity was seen as the one untouchable from AI. After all, how can something that is artificial match the complexities of a human mind? With the improvement in neural languages and emotion recognition, these theories are already being challenged.
We’ve already seen AI try its hand at creative concepts with Japan McCann, who tasked the tech with creating an advert. It was then put up against a human counterpart and put to public vote. Although the human won; the results were marginal. The difference was 54 to 46 percent in favour of the human.
These advancements in AI’s understanding of what it takes to be creative look set to continue in 2018. While some may feel that it could spell the end of their job, the reality is more akin to AI aiding human creativity. Art Directors and Copywriters have long been the dynamic duo of ad agencies. 2018 might just see a welcomed third wheel to the set up.
2018 and beyond
As tech improves, so will the ways that we go about our professional and personal lives. We’re already happily integrating with personal voice assistants and chatbots, while using algorithms for our internet searches.
2018 will see a continuation of such methods but with even greater precision. 2017 was the year AI emerged in the mainstream. 2018 looks likely to the when it becomes a part of our everyday furniture as we become more comfortable with it entering our ecosystem.
Olga Egorsheva, CEO and Co-Founder of Lobster
Image Credit: Lobster