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How Google Search Understands Human Language

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How Google Search Understands Human Language

Google Search is capable of understanding human language with the assistance of multiple AI models that all work together to find the most relevant results.

Information about how these AI models work is explained in simple terms by Pandu Nayak, Google’s Vice President of Search, in a new article on the company’s official blog.

Nayak demystifies the following AI models, which play a major role in how Google returns search results:

  • RankBrain
  • Neural matching
  • BERT
  • MUM

Neither of these models work alone. They all help each other out by performing different tasks to understand queries and match them to content searchers are looking for.

Here are the key takeaways from Google’s behind-the-scenes look at what its AI models do and how it all translates into better results for searchers.

Google’s AI Models Explained

RankBrain

Google’s first AI system, RankBrain, was launched in 2015.

As the name suggests, RankBrain’s purpose is to figure out the best order for search results by ranking them according to relevance.

Despite being Google’s first deep learning model, RankBrain continues to play a major role in search results today.

RankBrain helps Google understand how words in a search query relate to real-world concepts.

Nayak illustrates how RankBrain works:

“For example, if you search for ‘what’s the title of the consumer at the highest level of a food chain,’ our systems learn from seeing those words on various pages that the concept of a food chain may have to do with animals, and not human consumers.

By understanding and matching these words to their related concepts, RankBrain understands that you’re looking for what’s commonly referred to as an “apex predator.”

Screenshot from blog.google/products/search/, February 2022

Neural Matching

Google introduced neural matching to search results in 2018.

Neural matching allows Google to understand how queries relate to pages using the knowledge of the broader concepts.

Rather than looking at individual keywords, neural matching examines whole queries and pages to identify the concepts they represent.

With this AI model, Google is able to cast a wider net when we scanning its index for content that’s relevant to a query.

Nayak illustrates how neural matching works:

“Take the search “insights how to manage a green,” for example. If a friend asked you this, you’d probably be stumped. But with neural matching, we’re able to make sense of it.

By looking at the broader representations of concepts in the query — management, leadership, personality and more — neural matching can decipher that this searcher is looking for management tips based on a popular, color-based personality guide.”

How Google Search Understands Human LanguageScreenshot from blog.google/products/search/, February 2022

BERT

BERT was first introduced in 2019 and is now used in all queries.

It’s designed to accomplish two things — retrieve relevant content and rank it.

BERT can understand how words relate to each other when used in a particular sequence, which ensures important words aren’t left out of a query.

This complex understanding of language allows BERT to rank web content for relevance faster than other AI models.

Nayak illustrates how BERT works in practice:

“For example, if you search for “can you get medicine for someone pharmacy,” BERT understands that you’re trying to figure out if you can pick up medicine for someone else.

Before BERT, we took that short preposition for granted, mostly sharing results about how to fill a prescription. Thanks to BERT, we understand that even small words can have big meanings.”

How Google Search Understands Human LanguageScreenshot from blog.google/products/search/, February 2022

MUM

Google’s latest AI milestone in Search — Multitask Unified Model, or MUM, was introduced in 2021.

MUM is a thousand times more powerful than BERT, and capable of both understanding and generating language.

It has a more comprehensive understanding of information and world knowledge, being trained across 75 languages and many different tasks at once.

MUM’s understanding of language spans images, text, and more in the future. That’s what it means when you hear MUM being referred to as “multi-modal.”

Google is in the early days of realizing MUM’s potential, so it’s use in search is limited.

Currently, MUM is being used to improve searches for COVID-19 vaccine information. In the coming months it will be utilized in Google Lens as a way to search using a combination of text and images.

Summary

Here’s a recap of what Google’s major AI systems are and what they do:

  • RankBrain: Ranks content by understanding how keywords relate to real-world concepts.
  • Neural matching: Gives Google a broader understanding of concepts, which expands the amount of content Google is able to search through.
  • BERT: Allows Google to understand how words can change the meaning of queries when used in a particular sequence.
  • MUM: Understands information and world knowledge across dozens of languages and multiple modalities, such as text and images.

These AI systems all work together to find and rank the most relevant content for a query as fast as possible.

Source: Google


Featured Image: IgorGolovniov/Shutterstock




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Google’s AI Overviews Avoid Political Content, New Data Shows

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Google's AI Overviews Avoid Political Content, New Data Shows

Study reveals Google’s cautious approach to AI-generated content in sensitive search results, varying across health, finance, legal, and political topics.

  • Google shows AI Overviews for 50% of YMYL topics, with legal queries triggering them most often.
  • Health and finance AI Overviews frequently include disclaimers urging users to consult professionals.
  • Google avoids generating AI Overviews for sensitive topics like mental health, elections, and specific medications.

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Executive Director Of WordPress Resigns

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WordPress Executive Director Josepha Haden Chomphosy resigns,

Josepha Haden Chomphosy, Executive Director of the WordPress Project, officially announced her resignation, ending a nine-year tenure. This comes just two weeks after Matt Mullenweg launched a controversial campaign against a managed WordPress host, which responded by filing a federal lawsuit against him and Automattic.

She posted an upbeat notice on her personal blog, reaffirming her belief in the open source community as  positive economic force as well as the importance of strong opinions that are “loosely  held.”

She wrote:

“This week marks my last as the Executive Director of the WordPress project. My time with WordPress has transformed me, both as a leader and an advocate. There’s still more to do in our shared quest to secure a self-sustaining future of the open source project that we all love, and my belief in our global community of contributors remains unchanged.

…I still believe that open source is an idea that can transform generations. I believe in the power of a good-hearted group of people. I believe in the importance of strong opinions, loosely held. And I believe the world will always need the more equitable opportunities that well-maintained open source can provide: access to knowledge and learning, easy-to-join peer and business networks, the amplification of unheard voices, and a chance to tap into economic opportunity for those who weren’t born into it.”

Turmoil At WordPress

The resignation comes amidst the backdrop of a conflict between WordPress co-founder Matt Mullenweg and the managed WordPress web host WP Engine, which has brought unprecedented turmoil within the WordPress community, including a federal lawsuit filed by WP Engine accusing Mullenweg of attempted extortion.

Resignation News Was Leaked

The news about the resignation was leaked on October 2nd by the founder of the WordPress news site WP Tavern (now owned by Matt Mullenweg), who tweeted that he had spoken with Josepha that evening, who announced her resignation.

He posted:

“I spoke with Josepha tonight. I can confirm that she’s no longer at Automattic.

She’s working on a statement for the community. She’s in good spirits despite the turmoil.”

Screenshot Of Deleted Tweet

Josepha tweeted the following response the next day:

“Ok, this is not how I expected that news to come to y’all. I apologize that this is the first many of you heard of it. Please don’t speculate about anything.”

Rocky Period For WordPress

While her resignation was somewhat of an open secret it’s still a significant event because of recent events at WordPress, including the resignations of 8.4% of Automattic employees as a result of an offer of a generous severance package to all employees who no longer wished to work  there.

Read the official announcement:

Thank you, WordPress

Featured Image by Shutterstock/Wirestock Creators

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8% Of Automattic Employees Choose To Resign

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8% Of Automattic Employees Choose To Resign

WordPress co-founder and Automattic CEO announced today that he offered Automattic employees the chance to resign with a severance pay and a total of 8.4 percent. Mullenweg offered $30,000 or six months of salary, whichever one is higher, with a total of 159 people taking his offer.

Reactions Of Automattic Employees

Given the recent controversies created by Mullenweg, one might be tempted to view the walkout as a vote of no-confidence in Mullenweg. But that would be a mistake because some of the employees announcing their resignations either praised Mullenweg or simply announced their resignation while many others tweeted how happy they are to stay at Automattic.

One former employee tweeted that he was sad about recent developments but also praised Mullenweg and Automattic as an employer.

He shared:

“Today was my last day at Automattic. I spent the last 2 years building large scale ML and generative AI infra and products, and a lot of time on robotics at night and on weekends.

I’m going to spend the next month taking a break, getting married, and visiting family in Australia.

I have some really fun ideas of things to build that I’ve been storing up for a while. Now I get to build them. Get in touch if you’d like to build AI products together.”

Another former employee, Naoko Takano, is a 14 year employee, an organizer of WordCamp conferences in Asia, a full-time WordPress contributor and Open Source Project Manager at Automattic announced on X (formerly Twitter) that today was her last day at Automattic with no additional comment.

She tweeted:

“Today was my last day at Automattic.

I’m actively exploring new career opportunities. If you know of any positions that align with my skills and experience!”

Naoko’s role at at WordPress was working with the global WordPress community to improve contributor experiences through the Five for the Future and Mentorship programs. Five for the Future is an important WordPress program that encourages organizations to donate 5% of their resources back into WordPress. Five for the Future is one of the issues Mullenweg had against WP Engine, asserting that they didn’t donate enough back into the community.

Mullenweg himself was bittersweet to see those employees go, writing in a blog post:

“It was an emotional roller coaster of a week. The day you hire someone you aren’t expecting them to resign or be fired, you’re hoping for a long and mutually beneficial relationship. Every resignation stings a bit.

However now, I feel much lighter. I’m grateful and thankful for all the people who took the offer, and even more excited to work with those who turned down $126M to stay. As the kids say, LFG!”

Read the entire announcement on Mullenweg’s blog:

Automattic Alignment

Featured Image by Shutterstock/sdx15

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