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Google MUM Algorithm Can Do More than Rank Websites via @sejournal, @martinibuster

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john mueller discusses google mum algorithm 615aaaea4e889 sej

Google’s John Mueller was asked about how many search queries the MUM algorithm was affecting. John said he didn’t know and then explained that the Google MUM algorithm is multi-purpose and could be used in contexts beyond just ranking.

Question About Google Application of MUM Technology

The MUM algorithm is impressive because it can search for answers across web documents regardless of language and can even use images as part of the search query.

So it’s understandable that the person asking the question wanted to know how much MUM was affecting the search results.

Google’s John Mueller answered the question and then tried to put MUM into perspective without any hype.

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This is the question that was asked:

“A couple years ago Google noted that when it came to ranking results BERT would better understand and impact about ten percent of searches in the U.S.

My question is two-fold:

Has that percentage changed for BERT?

…What percentage is MUM expected to better understand and impact searches?”

How Many Searches Does MUM Affect?

John Mueller admitted that he didn’t know how many searches MUM affected and then explained why it might be difficult to put a number to the influence of MUM in the search results.

His answer first addressed the numbers for BERT and then addressed MUM.

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John Mueller answered:

“I have no idea…

I’m pretty sure that the percentage changed since then because everything is changing.

But I don’t know if we have a fixed number that goes for BERT or that goes for MUM.”

Related: Google Announces Search Redesign Using MUM Algorithm

Mum is Like a Multi-purpose Machine Learning Library

John Mueller next followed up with thoughts about MUM and said that it can be applied to a wide range of tasks that go beyond ranking.

He said:

“Mum, as far as I understand it is more like a multi-purpose machine learning library anyway.

So it’s something that can be applied to lots of different parts of search.

It’s not so much that you would isolate it to just ranking.

But rather you might be able to use it for understanding things on a very fine grained level and then that’s kind of interwoven in a lot of different kinds of search results.

But I don’t think we have any fixed numbers.”

Google is Happy with MUM

The person asking the question asked a follow-up question that John answered with a non-hype description of MUM that portrayed it as doing things that aren’t necessarily as flashy as it might seem from the outside looking in.

The follow-up question:

“It seemed to me like it was going to open up more opportunities actually for different products or queries to be discovered.

It seemed like it was just sort of exponentially going to blow it out what one could learn.”

John Mueller responded:

“I don’t know… we’ll see.

I think it’s always tricky to look at the marketing around machine learning algorithms, because it’s very easy to find …very exponential examples.

But that doesn’t mean that everything is as flashy as that.

…In talking with some of these search quality folks, they’re really happy with the way that these kinds of machine learning models are working.”

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Google’s Mum Algorithm is More Than Just Ranking

John Mueller added a little bit more information about Google’s MUM algorithm by explaining that it’s more than just applicable for ranking purposes.

He indicated that there are other tasks that it can perform that are beyond the ranking part of Google’s algorithms and that it can play a role in other parts of search.

Mueller also described MUM as being able to understand things with a fine-grained level of detail.

Related: Google MUM is Coming to Lens

Citation:

Google MUM Algorithm Does More than Just Rank Websites

Watch John Mueller discuss the MUM algorithm at the 2:13 minute mark:

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NEWS

OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

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OpenAI Introduces Fine-Tuning for GPT-4 and Enabling Customized AI Models

OpenAI has today announced the release of fine-tuning capabilities for its flagship GPT-4 large language model, marking a significant milestone in the AI landscape. This new functionality empowers developers to create tailored versions of GPT-4 to suit specialized use cases, enhancing the model’s utility across various industries.

Fine-tuning has long been a desired feature for developers who require more control over AI behavior, and with this update, OpenAI delivers on that demand. The ability to fine-tune GPT-4 allows businesses and developers to refine the model’s responses to better align with specific requirements, whether for customer service, content generation, technical support, or other unique applications.

Why Fine-Tuning Matters

GPT-4 is a very flexible model that can handle many different tasks. However, some businesses and developers need more specialized AI that matches their specific language, style, and needs. Fine-tuning helps with this by letting them adjust GPT-4 using custom data. For example, companies can train a fine-tuned model to keep a consistent brand tone or focus on industry-specific language.

Fine-tuning also offers improvements in areas like response accuracy and context comprehension. For use cases where nuanced understanding or specialized knowledge is crucial, this can be a game-changer. Models can be taught to better grasp intricate details, improving their effectiveness in sectors such as legal analysis, medical advice, or technical writing.

Key Features of GPT-4 Fine-Tuning

The fine-tuning process leverages OpenAI’s established tools, but now it is optimized for GPT-4’s advanced architecture. Notable features include:

  • Enhanced Customization: Developers can precisely influence the model’s behavior and knowledge base.
  • Consistency in Output: Fine-tuned models can be made to maintain consistent formatting, tone, or responses, essential for professional applications.
  • Higher Efficiency: Compared to training models from scratch, fine-tuning GPT-4 allows organizations to deploy sophisticated AI with reduced time and computational cost.

Additionally, OpenAI has emphasized ease of use with this feature. The fine-tuning workflow is designed to be accessible even to teams with limited AI experience, reducing barriers to customization. For more advanced users, OpenAI provides granular control options to achieve highly specialized outputs.

Implications for the Future

The launch of fine-tuning capabilities for GPT-4 signals a broader shift toward more user-centric AI development. As businesses increasingly adopt AI, the demand for models that can cater to specific business needs, without compromising on performance, will continue to grow. OpenAI’s move positions GPT-4 as a flexible and adaptable tool that can be refined to deliver optimal value in any given scenario.

By offering fine-tuning, OpenAI not only enhances GPT-4’s appeal but also reinforces the model’s role as a leading AI solution across diverse sectors. From startups seeking to automate niche tasks to large enterprises looking to scale intelligent systems, GPT-4’s fine-tuning capability provides a powerful resource for driving innovation.

OpenAI announced that fine-tuning GPT-4o will cost $25 for every million tokens used during training. After the model is set up, it will cost $3.75 per million input tokens and $15 per million output tokens. To help developers get started, OpenAI is offering 1 million free training tokens per day for GPT-4o and 2 million free tokens per day for GPT-4o mini until September 23. This makes it easier for developers to try out the fine-tuning service.

As AI continues to evolve, OpenAI’s focus on customization and adaptability with GPT-4 represents a critical step in making advanced AI accessible, scalable, and more aligned with real-world applications. This new capability is expected to accelerate the adoption of AI across industries, creating a new wave of AI-driven solutions tailored to specific challenges and opportunities.

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GOOGLE

This Week in Search News: Simple and Easy-to-Read Update

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This Week in Search News: Simple and Easy-to-Read Update

Here’s what happened in the world of Google and search engines this week:

1. Google’s June 2024 Spam Update

Google finished rolling out its June 2024 spam update over a period of seven days. This update aims to reduce spammy content in search results.

2. Changes to Google Search Interface

Google has removed the continuous scroll feature for search results. Instead, it’s back to the old system of pages.

3. New Features and Tests

  • Link Cards: Google is testing link cards at the top of AI-generated overviews.
  • Health Overviews: There are more AI-generated health overviews showing up in search results.
  • Local Panels: Google is testing AI overviews in local information panels.

4. Search Rankings and Quality

  • Improving Rankings: Google said it can improve its search ranking system but will only do so on a large scale.
  • Measuring Quality: Google’s Elizabeth Tucker shared how they measure search quality.

5. Advice for Content Creators

  • Brand Names in Reviews: Google advises not to avoid mentioning brand names in review content.
  • Fixing 404 Pages: Google explained when it’s important to fix 404 error pages.

6. New Search Features in Google Chrome

Google Chrome for mobile devices has added several new search features to enhance user experience.

7. New Tests and Features in Google Search

  • Credit Card Widget: Google is testing a new widget for credit card information in search results.
  • Sliding Search Results: When making a new search query, the results might slide to the right.

8. Bing’s New Feature

Bing is now using AI to write “People Also Ask” questions in search results.

9. Local Search Ranking Factors

Menu items and popular times might be factors that influence local search rankings on Google.

10. Google Ads Updates

  • Query Matching and Brand Controls: Google Ads updated its query matching and brand controls, and advertisers are happy with these changes.
  • Lead Credits: Google will automate lead credits for Local Service Ads. Google says this is a good change, but some advertisers are worried.
  • tROAS Insights Box: Google Ads is testing a new insights box for tROAS (Target Return on Ad Spend) in Performance Max and Standard Shopping campaigns.
  • WordPress Tag Code: There is a new conversion code for Google Ads on WordPress sites.

These updates highlight how Google and other search engines are continuously evolving to improve user experience and provide better advertising tools.

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FACEBOOK

Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again

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Facebook Problem Again

Uppdated: It seems that today’s issues with Facebook haven’t affected as many users as the last time. A smaller group of people appears to be impacted this time around, which is a relief compared to the larger incident before. Nevertheless, it’s still frustrating for those affected, and hopefully, the issues will be resolved soon by the Facebook team.

Facebook had another problem today (March 20, 2024). According to Downdetector, a website that shows when other websites are not working, many people had trouble using Facebook.

This isn’t the first time Facebook has had issues. Just a little while ago, there was another problem that stopped people from using the site. Today, when people tried to use Facebook, it didn’t work like it should. People couldn’t see their friends’ posts, and sometimes the website wouldn’t even load.

Downdetector, which watches out for problems on websites, showed that lots of people were having trouble with Facebook. People from all over the world said they couldn’t use the site, and they were not happy about it.

When websites like Facebook have problems, it affects a lot of people. It’s not just about not being able to see posts or chat with friends. It can also impact businesses that use Facebook to reach customers.

Since Facebook owns Messenger and Instagram, the problems with Facebook also meant that people had trouble using these apps. It made the situation even more frustrating for many users, who rely on these apps to stay connected with others.

During this recent problem, one thing is obvious: the internet is always changing, and even big websites like Facebook can have problems. While people wait for Facebook to fix the issue, it shows us how easily things online can go wrong. It’s a good reminder that we should have backup plans for staying connected online, just in case something like this happens again.

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