Connect with us

NEWS

Google’s John Mueller Answers if MUM Makes SEO Obsolete

Published

on

Google’s John Mueller Answers if MUM Makes SEO Obsolete

Google’s John Mueller responded to a Reddit discussion about whether MUM will make SEO obsolete. Given that the purpose of MUM is to provide answers from multiple languages, answers not currently answered by ten blue links, it’s not an unreasonable question to ask.

Google MUM

MUM is an acronym for Multitask Unified Model. It’s a way of answering complex questions that cannot be answered with just a few sentences in a featured snippet or with current technology.

Google refers to MUM as a significant event in the evolution of search technologies, calling it a milestone that is 1,000 times more powerful than the BERT algorithm.

Is MUM SE-Un-optimizable?

One astounding way MUM solves answers is to use the total sum of knowledge about a topic, even if that knowledge is in a different language.

Google said that it can source answers from across different languages. And that makes sense because answers in other languages may be more authoritative that the limited content produced in your local language.

In the recipe niche, an article about how to make a paella that was written in Spanish by a Spanish chef might be considered more authoritative than an article written by a stay at home mom in California who has little to no lived experience with Spanish cooking.

Advertisement

Who would you trust for an authentic Spanish recipe? The stay at Home Mom in California or the fourth generation Spanish chef?

Google uses the example of using native Japanese content for search queries related to hiking Mount Fuji, which can also drill down to subtopics that only a native might know about.

Keyword Based SEO?

Another feature is that MUM can find answers to questions that are a mix of images and text and provide answers to that mix.

How would an SEO optimize an answer to a question that is partially in the form of an image?

An image is not a word. It’s a representation of a thing, an entity.

Here’s what Google says:

Advertisement

“Eventually, you might be able to take a photo of your hiking boots and ask, “can I use these to hike Mt. Fuji?”

MUM would understand the image and connect it with your question to let you know your boots would work just fine. It could then point you to a blog with a list of recommended gear.”

In the MUM search paradigm, optimizing for keywords seems to break down because MUM is answering a complex question comprised of multiple subtopics.

Here’s how Google’s announcement explains it:

“Since MUM can surface insights based on its deep knowledge of the world, it could highlight that while both mountains are roughly the same elevation, fall is the rainy season on Mt. Fuji so you might need a waterproof jacket.

MUM could also surface helpful subtopics for deeper exploration — like the top-rated gear or best training exercises — with pointers to helpful articles, videos and images from across the web.”

It does not seem unreasonable to conclude that the above described MUM search result is drawn from multiple websites from different languages.

And if that’s the case, how would you even visualize which website is top ranked for a MUM search query when the query draws from multiple “helpful subtopics?”

Advertisement
  • If your primary language is English and part of your answer is from a Japanese website, is the Japanese site considered top ranked?
  • Will the blog post with the article about “top-rated gear” be the winner?
  • Or is the winner of that search query the publisher of the “best training exercises” article?
  • Can all five sites, one of which is in a foreign language, be considered top ranked?
  • Will MUM redefine what it means to be top ranked for certain search queries?

Sourcing answers from multiple websites seems like selecting five winners and breaking off five pieces of the trophy for them to take home with them.

If we accept the scenario of five sites have the opportunity to be top ranked, how would you, as an SEO, attempt to optimize for that?

Not an Unreasonable Question

We don’t know what MUM will look like once it rolls out in months or years as Google’s announcement said. We’re limited to drawing conclusions from the limited information that Google has shared.

And what they announced does not seem to fit the contours of search results as we know it.

Does that mean SEO has to adapt?

John Mueller Comments on Impact of MUM on SEO

Google’s John Mueller responded to the Reddit thread by affirming that SEO will always be needed.

Mueller’s answer referenced a joke about keyword stuffing:

Advertisement

“How many SEO experts does it take to change a light bulb, lightbulb, light, bulb, lamp, lighting, switch, sex, xxx, hardcore”

This is Mueller’s response:

“I don’t really see how this would reduce the need for SEO.

Things always evolve.

Remember the SEO joke about changing the lightbulb? None of that’s been necessary for a while now, which is due to developments like these, and yet, people still have enough to do as SEO.”

The Work of SEO Evolves

Mueller’s right. The nature of the work associated with SEO is under constant evolution. Some in the SEO community have a hard time changing and continue clinging to the idea of ranking for search results comprised of ten blue links.

But the truth is that the age of ten blue links has been replaced by a hybrid that is responsive to the context of the question being asked.

Google’s MUM algorithm could be said to be a way to respond to a search question with a complex context.

Advertisement

If the answer is best served with content originally written in Japanese or Spanish, then that may be a part of the answer.

At this point in time, given that there is no actual product, it may be premature to begin shouting that the sky is falling.

The prudent thing may be to reserve judgment until Google actually rolls out a product.

Citation

MUM Will Replace SEO?

Searchenginejournal.com

Advertisement
Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

NEWS

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

Published

on

By

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.

Advertisement

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.

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

GOOGLE

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

Published

on

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.

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

FACEBOOK

Facebook Faces Yet Another Outage: Platform Encounters Technical Issues Again

Published

on

By

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.

Advertisement

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.

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending