How long has Yandex used machine learning as part of it’s algorithms?
Yandex has partially implemented this technology since 2009, when it introduced the Snezhinsk algorithm (patented by Matrix Next). After 2016, Palekh, Korolev and Yati (the latter at the moment) were introduced.
How does YATI learn and improve?
YATI learns through tolokers ‘and assessors’ assessments, preliminary training per click, separately collected data (exact query, synonyms, sample fragments / ideal, streams).
Have traditional SEO methods become irrelevant with the introduction of the latest neural network?
No, they have not.
The basic principles of ranking remain, but now more attention will be paid to the semantic proximity of the request and the document.
What does the word “transformer” mean?
In this case, it is a relatively smart neural network with powerful computational potential, which can quickly cope with various tasks in the field of analysis of language structures.
How YATI is fundamentally different from Palekh?
There are more streams and machine understanding of the page’s content has reached its highest level at the moment. The robot now understands short articles (up to 10 sentences), and breaks only large materials into separate fragments.
Does YATI discriminate between sites?
Most likely, he focused on diversity. The opinion that the new algorithm will be more loyal to large projects is not confirmed. The main thing is the quality and authority of your content (so nothing has overly changed in this regard).