What's fundamentally wrong with Google, or why Alphabet fails with intelligent services
https://www.matrics360.com/google-products-and-services/

What's fundamentally wrong with Google, or why Alphabet fails with intelligent services

How many Google products and services do you use??Gmail, Google Drive, Google Maps, Google Chrome, YouTube, or an Android. ?The 10 most popular Google products are Google Search, Mail, Docs, Plus, Drive, Translate, Maps, AdWords, Play Store, and Google News.?But Google is well beyond that. A year ago

Over 3 billion Google Searches per day. Over 1 billion YouTube users. Over 1 billion Gmail users. Over 1 billion Chrome users. Over 1 billion Maps users. Over 1 billion Google Photos users. Over 2 billion Android users. Over 1 billion Google Play Store users.

$1.726 trillion is market cap of Alphabet (Google), with 71% revenue coming from its ads, being actually a giant ads company. Google Ads (formerly Google AdWords) platform is where advertisers bid to display brief advertisements, service offerings, product listings, or videos to web users.

Google's mission is to organize the world's information and make it universally accessible and useful. And its Search Engine is supposed to make it easy to discover a broad range of information from a wide variety of sources.

In all, Google occupies a 91.45% market share of the global search engine market .

How dull, dumb and deficient Google Search Engine, one might found while searching for a new topic on Google MUM AI Search Engine replacing its last one, BERT. Instead, it retrieves you a Google Mumbai SEPR with its paraphernalia.

Google is lacking a comprehensive model of the world, with all its entities, substances, states, changes and relationships, underlying the world's data/information/knowledge.

Google's poor conceptions of entities or topics, things and relationships, revolving around the schema.org types, are key obstacles to make its digital information services really intelligent.

What's fundamentally wrong with Google's entity?

Entities matter because, at their core, they are the world. Humans and machines understand everything around in the terms of entities and their relationships. This is how developed intelligence, human?or machine, tends?to think.

Ontology is the science of entities and relationships,?where the maximum entity is everything, the universe, and the minimum entity is nothing.?

An ontic?entity?is something that exists?as itself and by itself, as a subject or as an object, actually or potentially, concretely or abstractly, physically, socially, mentally or virtually. As it is in computer science, "an entity is an object that has an identity, which is independent of the changes of its attributes".

It is easily confusing entities with states, changes, processes, space or time, with all the heavy consequences.

Defining what an entity is, it is?to decide all your further science and technology, business and policy.

If you wrongly define the foundational concept, all your heavy constructions are doomed to fail.?

Here is an example of Google, its search engine and knowledge graph panels.

Entities matter for Google's ML search because, at their core, they are the world's information.

We know that an entity is defined by Google as:

“A thing or concept that is singular, unique, well-defined and distinguishable.”

Google's entity could?be?“… an entity may be a person, place, item, idea, abstract concept, numbers, dates, colors, concrete element, other suitable thing, or any combination thereof.

Entities could?be substances, states, quantities, qualities, space and time, or any combination thereof.

Google is lacking a comprehensive model of the world underlying the world's data/information/knowledge. Instead, it relies on the schemas as a set of 'types', each associated with a set of properties . The types are arranged in a hierarchy, where the most generic type of item is Thing. More specific Types are:

The vocabulary currently consists of 792 Types, 1447 Properties 15 Datatypes, 83 Enumerations and 445 Enumeration members.

Entity Metrics: Techniques, Algorithms, and Mechanisms

Ranking Search Results Based On Entity Metrics is the title of a Google patent they were granted in 2015 and could be the first patent on entities, which followed with its extensions.

According to the patents, the ranking of entities for search with learning about entities and their relationships involves the following algorithms and techniques.


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https://beanstalkim.com/learn/articles/patent-ranking-search-results-based-on-entity-metrics/

What is a SERP: a visual guide to Google search results page

All SERPs are unique, even when two users search the same query.

That’s because Google?personalizes search results ?for its users in an attempt to display results that are relevant to each specific individual.

In general, you can break SERPs down in the following four ways:

  • Sponsored results .?Results that appear because advertisers paid money to put them there are called sponsored results. These are typically text ads or shopping results, and you’ll seem Google Ads clearly tagged as such. They may occur at the top or bottom of the page, as well as in the Google Knowledge Graph.
  • Organic listings .?These are the listing of sites that you peruse when you search a query. In the above example, our?SEO for Beginners ?guide represents the first organic result, followed by Moz’s guide of the same name. (Learn more about rankings in?How Search Engines Rank Pages .)
  • Rich features .?These add a visual layer (sometimes multiple layers) to the SERP. They include things like featured snippets, carousels, and much more.
  • Google knowledge panels .?These display on the right side of the page, offering snippets of information to enhance search results. In the above example, it’s the box about search engine optimization.

What Is a SERP: A Visual Guide to Google Search Results & Features

Google Knowledge Graph Search API?

The Knowledge Graph Search API lets you find entities in the?Google Knowledge Graph . The API uses standard?schema.org ?types and is compliant with the?JSON-LD ?specification.

Knowledge Graph entities

The Knowledge Graph has millions of entries that describe real-world entities like people, places, and things. These entities form the nodes of the graph. Some examples of how you can use the Knowledge Graph Search API include:

  • Getting a ranked list of the most notable entities that match certain criteria.
  • Predictively completing entities in a search box.
  • Annotating/organizing content using the Knowledge Graph entities.

The following are some of the types of entities found in the Knowledge Graph:

What is Google’s MUM?

The Google Multitask Unified Model (MUM) update, aims?to answer ?modern search demands by using an AI-powered algorithm to improve online search capability. When searching the internet, contradictory to?expectations ?users are faced with multiple searches, geographical, and language barriers due to a lack of intuition on the search engine.

Google Multitask Unified Model (MUM) is a new technology for answering complex questions that don’t have direct answers.?Google has published research papers that may offer clues of what the MUM AI is and how it works.

MUM is likely comprised of multiple innovations . For example, the Google research paper,?HyperGrid Transformers: Towards A Single Model for Multiple Tasks ?describes a new state of the art in?multi-task learning that could be a part of MUM.

Resources

The World Hypergraph: Global Causal Graph Network: Meta-AI WWW


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