Algorithms have become smarter. They’re learning what websites you frequent, why you typed a certain query and what other search suggestions you’re likely to click. Behind the online results you’re seeing is a highly advanced form of AI: deep learning.
It’s based on artificial neural networks that allow the machine to learn without human supervision. Deep learning requires more data because neural networks need to process more information to be more efficient, to gain better insights — to better answer queries.
So how does it change the way Google does its work and what does it mean for SEO?
With the help of deep neural networks, machines can now analyze vast amounts of data and learn more tasks. Features like identifying photos, accurately recognizing voice commands, and correctly interpreting search queries will be done faster, and at a much bigger scale.
Google’s RankBrain was one of the first algorithms that exhibited deep learning. It’s able to understand the user’s search intent, resulting in more accurate search results. But this is just the beginning.
In an interview with former Google search engineer Edmond Lau, he stated that with machine learning, it’s hard to explain why a particular search result ranks higher than the other. Because the algorithm and ranking signals were designed by humans, it’s difficult to tweak machine-learning based systems to boost certain ranking signals. Engineers are still required to tweak the algorithm whenever they discover a loophole.
With deep learning, they are expecting AI to take over the tweaking. Deep learning technology is expected to achieve more accurate results. But the engineers won’t always be able to explain what led the machine to come up with the result.
Ultimately, what Google aims to do is create successful searches that satisfies users. No matter what pattern deep learning technology discovers, a website that satisfies user queries is more likely to clinch marketing success.
Businesses see a bright future with deep learning. But SEO experts and SEO companies may be anxious at the probability that machines may figure out unique algorithms that deviate from the normal practice and SEO techniques.
As with any top trending technology, marketers will need to adapt to deep learning.
How are other SEOs adjusting to this search innovation?
The goal for any business is to make customers happy. This goal is no different from Google’s aim of continually improving the user experience. Although the rules of ranking will change, the goal and purpose will not.
As search engines become smarter, an SEO company or professional will need to focus on providing the best user experience to make sure that they keep attracting the right visitors, persuading them to return to the website.
How do you get this result?
Make sure your web design is responsive, and that it loads fast. Over 5 billion people in the world are unique mobile users, which is about 66 percent of the global population. Site owners who optimize for mobile will be the ones who will come out on top following the upcoming updates.
Now that people have the ability to talk to their devices and issue voice commands, it will be smart to target conversational keywords or long-tail keywords. This approach creates a more targeted strategy. It will require you to dive deeper into your audience’s psychographics to know what they’re asking and what they expect.
Always create fresh and updated content for your website. No matter the update, both users and Google will prioritize websites that churn out quality and valuable content. One of the main goals of algorithm updates is to sift out irrelevant and low-quality materials.
In 2014, Google acquired DeepMind, a British company specializing in deep learning technology. Fast forward two years later, AlphaGo, an algorithm using Google’s deep learning technology, was able to beat the champion of the world’s hardest game, Go. A historic moment in the world of AI.
So what exactly happened there, and why was it so monumental?
The ancient game of Go is seen as the most challenging game to master because the strategy and objectives are endless, and it’s a much more intuitive game compared to chess — which is more logical. A single game has about 250150 or 10360 probable moves, compared to chess, which has 3580 (or 10123).
This makes it the ideal game to test deep learning since there’s no way to input all the moves into the system, which equates to the number of atoms in the universe. To beat a human, the machine has to learn and absorb new patterns and data to come up with the next move. Mimicking the process of the human brain.
Although machine learning functions to address a predefined purpose, deep learning technology like AlphaGo is not pre-programmed and it learns from experience. Developers and data scientists then use reinforcement learning, feeding it all the information it needs to learn and process new patterns.
The technology can be used in many industries, including healthcare, science, electronics and media.
Deep learning is still in its infancy, so more will be discovered about it. The technology may come up with new ways of helping search engines filter and rank websites. The major factors we’re seeing today, like anchor texts, page speed and meta descriptions may be factors that might not matter so much in the future.
So what’s our takeaway?
New technologies will continue to be developed. And they will continue to disrupt and improve the way you market your business. The key is to make sure you’re always prepared for the future.
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