Understanding SEO is the first rule for being able to optimize your site and its content so that would-be customers can actually find your company online. When your SEO is on point, you are more likely appear in search engine results when someone looks for the type of products or services you sell. However, to be able to truly understand SEO, you need to comprehend how modern search engines work — and that means understanding artificial intelligence, or AI.
What is AI?
AI is a technological advancement that enables a combination of hardware and software to function like a human brain — minus the inherent flaws in logic and the relatively small memory capacity. It makes it possible to not only analyze large amounts of data but to draw meaningful insights about the information. In some cases, these AI-enabled insights are more insightful, quicker or on a much larger scale than would be possible with human involvement — usually all three.
And those insights can help build better search engine results. “If you feed enough photos of a platypus into a neural net, it can learn to identify a platypus,” writes Cade Metz, formerly of Wired. “If you show it enough computer malware code, it can learn to recognize a virus. If you give it enough raw language — words or phrases that people might type into a search engine — it can learn to understand search queries and help respond to them.” In other words, AI learns over time.
In general, there are three types of artificial intelligence:
- Artificial Narrow Intelligence (ANI): This type of AI focuses on one function (e.g. chess, spam filters).
- Artificial General Intelligence (AGI): When AI has a general, overall function. Usually, this is equated to the ability of a single human.
- Artificial Superintelligence (ASI): This is AI that is beyond Artificial General Intelligence. The neural network operates at a much higher capability than AGI.
Google’s RankBrain is a type of ANI. Specifically, it is a connection-based system that mimics the way people learn. Also called deep learning, connectionist ANI uses back-propagation to identify flaws in the output of the system (e.g. misidentifying a duck as a platypus) and uses that information to inform future…