NEWS
Google MUM is Coming to Lens via @sejournal, @martinibuster
Google announced that their next generation super algorithm MUM is coming to their Google Lens product. This fulfills the promise of MUM which allows a user to search not just with text but with images as well.
This event will impact informational publishers and if more consumers use Google Lens as a result then this could be a boon to ecommerce companies as an important new sales channel.
Google’s Announcements About MUM
Google made an informal announcement on Twitter about MUM coming to Google Lens and also published an article about AI and visual search.
The article provides an example of the advanced search capabilities that are coming to the Google Lens app:
“With this new capability, you can tap on the Lens icon when you’re looking at a picture of a shirt, and ask Google to find you the same pattern — but on another article of clothing, like socks.
This helps when you’re looking for something that might be difficult to describe accurately with words alone.
You could type “white floral Victorian socks,” but you might not find the exact pattern you’re looking for. By combining images and text into a single query, we’re making it easier to search visually and express your questions in more natural ways.”
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Screenshot Showing How Google MUM Finds Answers
Google Lens
Google Lens is Google’s image search app for Android and iOS. It allows users to accomplish multiple image-based search tasks.
Typical Google Lens Tasks
- Scan Text, including phone numbers and event details to add to a calendar
- Translate text
- Copy and send text
- Identify plants and animals
- Search for similar products
The product search function is an important one because it allows online merchants to surface their products in Google Lens.
Google published a brand new ecommerce best practices SEO guide on September 28th that highlights Google Lens:
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“Google Lens
If you want your products to be found in Google Lens search results, make sure your product details are uploaded to Google Merchant Center, opt in to free product listings, and follow the Google Image best practices.”
Google MUM Algorithm
Google’s MUM algorithm allows users to conduct complicated searches that cannot ordinarily be answered with traditional search queries.
An important innovation in MUM is that it can take images instead of keywords as an input.
So instead of searching with just keywords a searcher can conduct searches with an image.
Remarkably, the algorithm is not limited to searching for the answer in one language. Google’s MUM algorithm can search for a complex answer across many popular languages in order to show the most helpful answer.
Google MUM is Coming to Google Lens
It’s not surprising that Google MUM is coming to the Lens product, it’s a natural fit and was inevitable to integrate the MUM algorithms into Google Lens.
According to today’s announcement:
“MUM, our advanced AI model, is coming to #GoogleLens early next year. You’ll be able to snap a photo AND ask a question, which can be helpful in those moments you need to fix a broken part and have no idea what it is”
The announcement was tweeted and was accompanied by an animated GIF showing a person snapping a photo of a bicycle part and typing the words “how to fix” in an accompanying search box.
MUM, our advanced AI model, is coming to #GoogleLens early next year. You’ll be able to snap a photo AND ask a question, which can be helpful in those moments you need to fix a broken part and have no idea what it is 🤷🔧 #SearchOn pic.twitter.com/cmedce3dB2
— Google (@Google) September 29, 2021
No Firm Date For When Google MUM Comes to Lens
MUM is scheduled to arrive in early 2022. That’s all the information that has been shared.
This will be the first widespread implementation of the new technology and could be seen as the opening act for a wider implementation, with the ultimate application arriving on Google’s search box.
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Google has been conservative about how MUM will be implemented and has been explicit that any implementation of this technology will respect publishers.
Publisher Fear of Google MUM
Some publishers don’t trust Google and fear that MUM will use their information and not send traffic to them by simply displaying the information.
This situation where Google displays publisher information without sending traffic is called a zero click search.
Google MUM Does Not Result in Zero Click Search
This implementation of MUM does not appear to display publisher information without attribution. The animated GIF accompanying the announcement clearly shows a searcher looking for information and being directed directly to a website.
Screenshot of Google MUM Search
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That should be good news for publishers who worry about how Google uses their web page information.
Google Lens and Shopping
Additionally, the addition of MUM should also be welcome news to ecommerce publishers who may continue to be able to surface their products in the new Google Lens search experience.
As mentioned earlier, if more consumers use Google Lens because of MUM then this can mean more consumers using Lens for shopping.
The animated GIF illustrating the new MUM experience clearly shows that shopping is prioritized.
Screenshot Showing Google Lens Search Experience
Google MUM Comes to Google Lens
This introduction of MUM is very important. It points to a future version of search that is beginning to become untethered from the keyword based question and answer box and moving further along the path toward the paradigm of an assistant that can help people do things.
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Citation
Read Google’s Explainer on Searching With MUM
How AI is Making Information More Useful
NEWS
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.
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.
Facebook Faces Yet Another Outage: Platform Encounters Technical Issues 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.