Google To Prioritize AI Overviews Ads Over Organic Search via @sejournal, @martinibuster

Speakers at Google’s Marketing Live event demonstrated how they will utilize user search queries and AI Overviews content to show interactive shopping ads that will push organic search results even lower, stating that Google is “focused on opening up new opportunities for your business.

Google: We’re Not Building A Better Search Engine

The first speaker, Philipp Schindler, SVP & Chief Business Officer at Google, said out loud what Googlers normally don’t when he said that the purpose of search results is to show advertising.

He made the remark in the context of a new AI video tool that will help YouTube creators make more content.

At the 18:19 minute mark of the event, Schindler boasted:

“We’ve been collaborating with some really talented film makers, musicians and artists, and the results have been simply incredible. Soon we’ll bring video to shorts, opening up a whole new world of creative possibilities for you and your brands. Just imagine every creator with the power of AI in their pocket.

So what does all of this mean for you? More creators creating more quality content attracts more viewers, which means more reach, engagement and ROI for you. We’re not just building a better search engine or a better YouTube. We’re focused on opening up new opportunities for your business.”

Screenshot Of Google Marketing Event

The statement that Google is using AI Overviews and Search to build reach and ROI for advertisers is not the only one. The next two speakers made the same point.

Search And Shopping Ads In AI Overviews

The next speaker was Vidhya Srinivasan, VP/GM, Advertising at Google. She begins by describing how search experiences will drive traffic to websites. Then quickly switches gear to show how interactive advertising will push organic search listings literally beyond the view of users who are making the search queries.

At the 30 minute mark of the video, Srinivasan explained:

“AI overviews will appear in search results when they are particularly helpful beyond what search offers today. As we continue to test and evolve the search experience, we are going to stay super focused on sending valuable traffic to publishers and creators. But then, more avenues for user exploration leads to more choice and more choice leads to more opportunities for advertisers.

You may have noticed that we already show ads above and below AI overviews. These ads are matched to the user’s search query. We will now start testing, Search and Shopping ads ads in AI overviews for users in the US.

What is also new with this is we are going to match these ads not just to the query context, but also to the information within the AI Overviews. And, as always, ads will be clearly labeled.”

1. AI Overviews – No Organic Listings

2. Scroll Down For Shopping Ads

She next went on to describe an example of wrinkled clothes while traveling and turning to Google Search to find ways to prevent the wrinkles. She shows a search activity for travel hacks and shows how organic search results are pushed beneath the AI Overviews feature and new Search and Shopping ads that contain product images and pop out far more than any search results do.

She explained how the new AI Overviews shopping ads will be there to convert searchers:

“With the AI overview, I quickly found some common travel hacks that sounded promising. As I browsed the many options that showed up, I found a really nice fix, a wrinkle release spray that I’d never heard of before. So perfect. I want to try that.

Now, with this feature, I can just click on this ad right away, right there, and buy it.

So as you can see, we’re just making it easier and faster for consumers so that they can take action right away. So this is just one example of how we are using Gen AI. There are many more, and we’re going to start with more applications in search ads.”

3. Targeted Ads Based On AI Overviews

Google Search Is The Bait

Google search engineers are using the most advanced technology and data to create the most useful search results of any time in Google’s history, this is the best it’s ever been. But according to the people who are really in charge at Google, the purpose of Search is not “to organize the world’s information and make it universally accessible and useful” but to build more “reach, engagement and ROI” for advertisers. Sam Altman was right to call what Google is doing dystopian.

SEOs Were Social Engineered

Social engineering is the management of people’s behavior in order to get them to perform a certain way.  Google got a huge chunk of the web ecosystem bought into concepts like Core Web Vitals and also Experience, Expertise, Authoritativeness and Trustworthiness in order to satisfy users that Google apparently never intended for them.

It’s not the fault of the Googlers who put their hearts into perfecting search. They do a good job. But it’s clear that Google’s mission is no longer to make information accessible and useful. Perhaps what can only feel like a dystopian horror, Google succeeded in social-engineering the search community and publishers to focus on creating  helpful content so that those on the advertising side can use it to build more ROI for advertisers.

It’s not just SEOs and publishers that were used for the benefit of advertisers.

Watch the Google Marketing Live Keynote 2024

Featured Image by Shutterstock/pikselstock

7 Ways AI Took My Job [To The Next Level] via @sejournal, @CallRail

With AI-powered call attribution, you can gain valuable insights into which channels are driving the most conversions.

How Call Attribution Works

  • Step 1: Assign – Select unique call tracking numbers to assign to each campaign or listing.
  • Step 2: Track – Potential customers see your ad or listing and call the associated phone number.
  • Step 3: Forward –The calls ring directly into your main business phone, regardless of which number they use.
  • Step 4: Analyze – Because they used one of your tracking numbers, you instantly know which ad or campaign inspired them to call.

With AI-powered call tracking, gone are the days of wondering how your digital marketing efforts are tied to high-value inbound calls.

For agencies, this helps prove the real value of your services and extend the life of your client relationships.

2. AI Can Help You Save Time On Manually Reviewing Calls

Listening to and analyzing phone calls manually can be time-consuming and inefficient for agencies.

However, it’s an important part of understanding the customer experience and sales team performance.

With AI-powered call analysis tools, you get quality, keyword-tagged transcriptions with near-human-level accuracy.

Not only can this technology help you save over 50% of the time spent listening to phone calls, but it can also help you deliver actionable recommendations to clients and drive better results.

Conversation Intelligence, for instance, is trained on over 1.1M hours of voice data and enables real-time analysis for instantaneous results.

This advanced tool provides opportunities for you to improve your strategy through the following granular insights:

  • Spotting disparities in the industry-specific lingo your sales team uses, compared to the lingo your prospects are using to describe their business challenges and goals.
  • Identifying trends or gaps in your service offerings based on what your prospects are asking for.
  • Identifying frequently asked questions and other important topics to address through content marketing.
  • Setting goals for lead qualification — not just the quantity of leads generated for your business.

Conversational AI is perfectly suited to summarize the content of long conversations – however, the call summaries still require a human to read them and determine the main takeaways.

But if you work in a bustling small business, it’s unlikely you’d have the bandwidth for tasks such as call transcription, summaries, keyword spotting, or trend analysis.

Rather than displacing human labor, conversational AI is assisting businesses in taking on tasks that may have been overlooked and leveraging data that would otherwise remain untapped.

3. AI Can Help You Lower Cost Per Lead / Save Money On Tools & Ad Spend

Ever wonder why certain campaigns take off while others fall flat? It’s all in the data!

Even failed campaigns can offer invaluable insights into your client’s audience and messaging.

But if you can’t spot the underperformers quickly enough, you risk wasting your ad budget on ineffective tactics.

The quicker you can identify what’s working and what’s not, the quicker you can pivot and adjust your marketing strategy.

With AI-powered tools, agencies can access instant insights that enable them to reduce wasteful spending and improve overall campaign efficiency.

How To Deliver More Value With AI

  • Make a bigger impact in less time: AI-powered technology creates a force multiplier within your agency, allowing you to make more of an impact with the same level of inputs you’re already using.
  • Unlock actionable insights from call data: AI is revolutionizing the way companies leverage call data by enabling them to gain insights at scale. As a result, businesses can increase their ROI and deliver greater value to their clients by analyzing hundreds of calls efficiently.
  • Foster alignment with data-driven strategies: By analyzing customer conversations with AI, businesses can align their marketing strategy with data-driven recommendations, enhancing overall coherence. Additionally, the ability to create triggers based on specific phrases enables automated analysis and reporting, further streamlining the alignment process.
  • Drive effectiveness with rapid insights: Leveraging Conversation Intelligence enables agencies to deliver better insights faster, increase conversion rates, refine keyword strategies, and develop robust reporting capabilities.

With the right AI-powered tools, you can access the insights you need to ensure maximum ROI for your clients.

4. AI Can Help You Improve Overall Agency Efficiency

Are you spending too much valuable time on tasks that produce minimal results?

Many agencies find themselves bogged down by routine, administrative tasks that don’t contribute much to their bottom line.

But with AI automation, agencies can streamline their operations and redirect their energy towards more strategic endeavors.

From email scheduling and social media posting to data entry and report generation, AI can handle a wide array of tasks with precision and efficiency – giving you time to focus on high-impact activities that drive growth and deliver tangible results.

Ways Your Business Can Benefit From Automation

  1. Automatically transcribe your calls to boost close rates: See how your team is handling difficult objections and ensure that they’re delivering your businessʼ value proposition in an effective manner.
  2. Score calls based on quality and opportunity: Take the time-consuming work out of scoring your calls and determine which campaigns drive the best calls to your business.
  3. Classify calls by your set criteria: Qualify, score, tag, or assign a value to the leads that meet your criteria, automatically.
  4. Automatically redact sensitive information: Protect your customers by removing billing or personal information. Keep your data safe and secure through complete HIPAA compliance.
  5. Monitor your teamsʼ performance: Use Conversation Intelligence as a valuable sales training tool to ensure your team doesn’t miss any key messaging marks.
  6. Know your customersʼ needs: Identify conversation trends in your phone calls and stay privy to evolving customer needs.
  7. Improve your digital marketing strategy: Use AI-powered insights to inform your digital marketing strategy and boost your online presence.

By automating mundane tasks, agencies can optimize workflows, increase productivity, and improve efficiency across the board.

Looking for 5 – 7? Download The Full Guide

Rather than fearing AI, the future belongs to those who embrace it.

By strategically combining human creativity with artificial intelligence, you can unlock capabilities that transcend what either could achieve alone.

Want to discover even more ways to level up your agency with AI?

Get the full guide here.

Google’s AI Vision Driven By Panic, Not User Needs: Former Product Manager via @sejournal, @MattGSouthern

A 16-year Google veteran is raising concerns about the company’s current focus on AI, labeling it a “panic reaction” driven by fear of falling behind competitors.

Scott Jenson, who left Google last month, took to LinkedIn to critique the tech giant’s AI projects as “poorly motivated and driven by this mindless panic that as long as it had ‘AI’ in it, it would be great.”

Veteran’s Criticism Of Google’s AI Focus

Jenson stated that Google’s vision of creating an AI assistant for its ecosystem is “pure catnip” fueled by the fear of letting someone else get there first.

He parallels the ill-fated Google+ product, which he calls a “similar hysterical reaction” to Facebook’s rise.

Jenson wrote:

“This exact thing happened 13 years ago with Google+ (I was there for that fiasco as well). That was a similar hysterical reaction but to Facebook.”

Lack Of User-Driven Motivation

Jenson argues that Google’s strategy lacks motivation driven by genuine user needs, a sentiment echoed by a recent Gizmodo article that described this year’s Google I/O developer conference as “the most boring ever.”

The article, which Jenson linked to in his post, criticized Google for failing to clarify how Gemini’s new AI technology would integrate into its existing products and enhance the user experience.

See Jenson’s full post below:

Can You Turn Off Google’s AI Overviews?

One prime example of Google’s AI overreach is the AI overviews feature, which generates summaries to directly answer search queries by ingesting information from across the web.

This controversial move has sparked legal battles, with publishers accusing Google of violating intellectual property rights and unfairly profiting from their content without permission.

Turning Off AI Overviews

While Google doesn’t provide an official setting to turn off AI overviews, a viral article from Tom’s Hardware suggests using browser extensions.

Alternatively, you can configure Chrome to go directly to web search results, bypassing the AI-generated overviews.

Here are the steps:

  • Open Chrome settings by clicking the three dots in the top-right corner and selecting “Settings” from the menu.
  • In the Settings window, click on the “Search Engine” tab on the left side.
  • Under the “Search Engine” section, click “Manage search engines and site search.”
  • Scroll down to the “Site search” area and click “Add” to create a new entry.

In the new entry, enter the following details:

  • Name: Google (Web)
  • Shortcut:
  • URL: {google:baseURL}/search?udm=14&q=%s
  • Click “Add
Screenshot from: chrome://settings/searchEngines, May 2024.

Lastly, click the three dots next to the new “Google (Web)” entry and select “Make default.”

Screenshot from: chrome://settings/searchEngines, May 2024.

After following these steps, Chrome will now default to showing regular web search results instead of the AI overview summaries when you perform searches from the address bar.

Tensions Over Data Usage

The controversy surrounding AI overviews creates tension between tech companies and content creators over using online data for AI training.

Publishers argue that Google’s AI summaries could siphon website traffic, threatening independent creators’ revenue streams, which rely on search referrals.

The debate reflects the need for updated frameworks to balance innovation and fair compensation for content creators, maintaining a sustainable open internet ecosystem.


What concerns has Scott Jenson raised about Google’s AI focus?

Scott Jenson, a former Google product manager, has expressed concerns that Google’s current AI focus is more of a “panic reaction” to stay ahead of competitors rather than addressing user needs. He critiques Google’s AI initiatives as poorly motivated and driven by a fear of letting others get ahead.

How does Scott Jenson compare Google’s AI strategy to past projects?

Jenson parallels Google’s current AI focus and the company’s response to Facebook years ago with Google+. He describes both as “hysterical reactions” driven by competition, which, in the case of Google+, resulted in a product that failed to meet its objectives.

Why are content creators concerned about Google’s AI overviews?

Content creators worry that Google’s AI overviews, which generate summaries by ingesting web content, could reduce site traffic. They argue that this practice is unfair as it uses their content without permission and impacts their revenue streams that rely on search referrals.

How can users turn off Google’s AI overviews in Chrome?

Although no official setting exists to disable AI overviews, users can use a workaround by enabling a specific Chrome setting.

Here are the steps:

  • Open Chrome settings by clicking the three dots in the top-right corner and selecting “Settings” from the menu.
  • In the Settings window, click on the “Search Engine” tab on the left side.
  • Under the “Search Engine” section, click “Manage search engines and site search.”
  • Scroll down to the “Site search” area and click “Add” to create a new entry.

In the new entry, enter the following details:

    • Name: Google (Web)
    • Shortcut:
    • URL: {google:baseURL}/search?udm=14&q=%s
    • Click “Add

This will force Chrome to skip AI-generated overviews and show the classic list of web links.

Featured Image: Sira Anamwong/Shutterstock

Using AI Ethically In SEO via @sejournal, @wburton27

AI can help brands and marketers be more efficient and productive and do things quicker, but it is not perfect and does have some drawbacks.

With the rise and adoption of AI into SEO workflows, processes, and tools, SEO pros must take an ethical approach to artificial intelligence.

What exactly does an ethical approach to AI mean?

An ethical approach involves using AI technologies transparently, fairly, and responsibly while respecting user privacy and ensuring the accuracy and integrity of information.

We are all aware that using AI is imperfect and can be full of inaccurate, biased, fluffy information, etc., which can cause many problems for agencies and marketers that rely on AI to create content.

With the March core update, sites that use AI content that was not edited, original, or helpful lost a substantial portion of organic traffic.

Here are some ways we can use AI to be more ethical.

Be Transparent And Provide Disclosure

Do not use generative AI to create content for publishing. If you use generative AI in parts of your process, you should be fully transparent to the brands you work with about how you use AI in your SEO practices.

Maintain Accuracy And Integrity

If you’re going to use AI, you should take a human-led approach to writing long-form content. Humans should always do the content creation, but AI can be helpful for brainstorming, organizing, rewording, transcription, and reworking content. In each case, outputs must be checked for originality using Copyscape or the tool of your choice.

Additionally, the information must be trustworthy and accurate. With the HCU being incorporated into the March core update, it’s more important than ever to focus on people-first content rather than content that is not helpful, useful, or satisfying the end user’s intent.

Be Original and Useful

With Google focusing on a good user and people-first content experience, we should not rely on AI content because of the inadequacy in training data, and a lack of originality. AI could be great for compiling a list of notes from people with first-hand experience and pulling them into a cohesive article, for example, but not to produce the list and facts, even with fact-checking.

Follow Compliance With Search Engine Guidelines

It’s imperative that we follow search engine guidelines and ethical standards.

AI should not be used to engage in practices like keyword stuffing, cloaking, or creating doorway pages. Instead, it should support the creation of high-quality and useful content.

Take a look at Google AI Principles – Google AI.

Promote Positive Impact

Ethically using AI in SEO also means considering the broader impact on society. This entails promoting trustworthy, useful content that contributes positively to users’ knowledge and well-being.

Develop Safely & Respect Privacy

If you build your own tools and platforms with AI, ensure you have strong security protocols and practices to prevent causing any harm.

Always assess your technologies before launching them into the production environment to ensure they are safe and secure. Ensure to continue monitoring it after it is released to the general public.

LLMs are not secure. It may be necessary to get legal advice before implementing certain types of AI, like generative AI, in processes that include user/customer information. Updating a privacy policy may not be enough.

Never put proprietary and confidential information into a generative AI chatbot like ChatGPT.  Most LLMs save all user inputs and the information could be used to generate responses to other users.

Respect Intellectual Property & Originality

One of the biggest issues with AI is intellectual property (IP). If I create some content using ChatGPT, who owns it?

We need to ensure that when AI recommends content, it is original and not taken from anywhere else. This can be problematic because some AI platforms don’t list the source of the information unless you specify chatbots to do so.

ChatGPT can tell you where the content sources are coming from if you list them in your prompt. For example, I asked ChatGPT to write me a 750-word blog post on the top things to do in NY and list the sources, and it did.

 listing top sightseeing spots in new york city with descriptions, hyperlinks, and a dialog boxScreenshot from ChatGPT, April 2024

If you’re getting some information from ChatGPT, you need to credit the source and ensure they’re not copying other people’s content. Also, setting clear rules for using AI in making content can help avoid legal problems and ensure you’re fair and honest.

I checked the content that I created in ChatGPT, and according to Copyscape, it is full of similar text.

Screenshot of a web search page displaying results for historic public parks in new york city. the results highlight multiple links and brief summaries about parks like the high line and hamilton park.

Screenshot from Copyscape, April 2024

Note: Please keep in mind that asking LLMs to cite sources doesn’t guarantee you’re citing the right content or that the content is original. The best and safest way to avoid accidental plagiarism is for humans to do the research and write the content.

Google Is Not About Content That Is Artificial And Lacking In Originality

With the rapid growth of AI-based tools entering the market and AI being incorporated into a lot of platforms and being used in daily SEO tasks,  it is extremely important for us to adhere to ethical AI principles to ensure that the use of AI in SEO supports a fair, equitable, and user-focused search ecosystem.

Google has always been about quality and original content that offers value to end users and not content that is fully artificial, offers no value, lacks trust, is thin, duplicate, lacks originality, etc.

In order to compete in today’s competitive and ever-changing SERPs, focusing on improving E-E-A-T is more important than ever before because it is a quality signal that shows Google and end users that you’re the subject matter expert and authority in your niche.

It’s highly recommended to have thought leaders and experts in your niche create your content and show their expertise on your site.

Additionally, it’s important to focus on user experience and ensure that your site loads quickly, is easy to navigate, and helps users find exactly what they came to your site for.

More resources: 

Featured Image: aniqpixel/Shutterstock

As Chatbots And AI Search Engines Converge: Key Strategies For SEO

A lot is happening in the world of search right now, and for many, keeping pace with these changes can be overwhelming.

The rise of chatbots and AI assistants – like ChatGPT and its new model GPT-4o, along with Google’s rollout of AI Overviews and Search Generative Experience (SGE) – is blurring the lines between chatbots and search engines.

New AI-first entrants, such as Perplexity and, also fragment the search space.

While this causes some confusion and necessitates that marketers pivot and optimize for multiple types of “engines,” it also presents a whole new array of opportunities for SEO pros to optimize for both traditional and AI-driven search engines in a new multisearch universe.

This evolution raises a broader question – perhaps for another day – about redefining what we call SEO to encompass terms like Artificial Intelligence Optimization (AIO) and Generative Engine Optimization (GEO).

Currently, every naming convention seems subject to change, which is something to consider as I write this article.

Either way, this evolution opens up tremendous opportunities for disruption in the overall search landscape.

What Is A Chatbot Or AI Assistant?

chatbot definitionScreenshot from Wikipedia, May 2024

At the most basic level, chatbots use natural language processing (NLP) and large language models (LLMs) that are trained to extract data from online information, sources, and specific datasets. They then classify and fine-tune text and visual outputs based on a user’s prompt or question.

Chatbots are often used within specific applications or platforms, such as customer service websites, messaging apps, or ecommerce sites. They are designed to address specific queries or tasks within these defined contexts.

Right now, we see many crossovers between LLM-based chatbots and search engines. Rapid developments in these areas can cause confusion.

In this article, we’ll focus on the development of AI models in chatbots and their relation to search, with an inferred reference between chatbots and AI assistants.

The Evolution Of Chatbots And AI Models

Since ChatGPT emerged in November 2022, we’ve seen a significant boom in chatbots and AI assistants. Now, generative AI allows users to interact directly with AI and engage in human-like conversations to ask questions and complete various tasks.

For example, these AI tools can assist with SEO tasks, create content, compose emails, write essays, and even handle coding and programming tasks.

As they evolve, chatbots become multimodal (MMLLMs), improving capabilities beyond text to include images, audio, and more.

LLMs and LLMMsImage from 2024 AI Index Report from Stanford University, May 2024

For those interested in digging deeper into these models, the 2024 AI Index Report from Stanford University is a great resource for SEJ readers.

While many chatbots and AI models serve similar purposes, they also have distinct applications and use cases, such as content creation, image generation, and voice recognition.

Here are a few examples with some interesting differentiators and points:

  • ChatGPT: Conversational AI for research, ideation, text, image content, and more.
  • Google Gemini and Gemma: Uses Google’s LLM to connect and find sources within Google.
  • Microsoft Bing: Uses ChatGPT for conversational web search in Bing.
  • Anthropic Claude: Various AI models for content generation, images, and coding.
  • Stability AI: Suite of models and AI assistants for text, image, audio, and coding.
  • Meta Llama3: Utilizes Facebook’s social graph, its own Llama 3 model, and real-time data from Google.
  • Microsoft’s Copilot: AI assistant for business creativity and productivity apps.
  • Amazon LLM and Codewhisperer: Enhances customer and employer experiences.
  • Perplexity AI: Provides quick answers, sources of information, and citations.

Perplexity AI (which I will touch on later in this article) acts more like a search engine than many other chatbots and AI assistants.

Beyond their primary use cases, many companies are making their models available to a wider audience and broader ecosystems, allowing users to customize their own AI assistants.

For example, Amazon’s Bedrock enables AWS customers to use Anthropic and other LLMs, including Amazon’s own model, to create custom AI agents. Companies like Lonely Planet, Coda, and United Airlines are already using it.

On May 13, OpenAI launched its new flagship model, GPT-4. This model is a combination of AI technologies, bringing together what OpenAI calls “text, vision, and audio.” It also opens up access to its application programming interface (API), allowing developers to build their own applications.

All of this convergence has a lot of people wondering.

What’s The Difference Between Chatbots And Search Engines?

The first thing to note is that both chatbots and search engines are designed to provide information.

Search engines and some chatbot models share many similarities, which means their definitions can blur, and the relationships between them converge and collide.

However, at the moment (but it is changing), there is still a distinct difference between the two:

Search Engines

  • Search engines are better for exploring a wide range of topics.
  • They provide diverse perspectives from multiple sources.


  • Chatbots are better for quick answers, task completion, and personalized interactions.
  • They enhance the efficiency of the average searcher, making them much more effective at finding information.
Search engines vs chatbotsImage from author, May 2024

As more overlays and overlaps occur, the definitions of what constitutes a chatbot, an AI assistant, and a search engine may need to be redefined.

How Chatbots And Search Engines Work Together

Conversational search is a key area where search engines increasingly integrate chatbot features to provide a more interactive search experience.

You can ask questions in natural language, and the search engine may respond with direct answers or engage in a dialogue to refine your query.

Chatbots and AI assistants often utilize search engine technology to access information from the web, enhancing their ability to provide accurate and comprehensive answers.

This integration allows chatbots to go beyond their programmed knowledge base and tap into a broader range of information.

Here are a few examples:

  • Google: Integrates its own chatbot features into its search engine through SGE, providing direct answers and engaging in conversational search for some queries.
  • Bing: Incorporates a chatbot called “Bing Chat” that uses ChatGPT, conversational AI, and search technology to answer questions and provide information.
  • YouChat: A search engine that provides conversational responses to queries and allows for follow-up questions.
  • Meta: Utilizes its social graph and Google’s real-time data in its chatbot/AI assistant.
  • Perplexity AI: A chatbot that functions like a search engine, focusing on informational sources, sites, and citations.

These examples illustrate how the lines between chatbots and search engines are blurring. Thousands more instances show this convergence, highlighting the evolving landscape of digital search and AI.

How “Traditional” Search Engines Are Evolving As AI-First Entrants Arrive

The rise of generative AI and chatbots has caused significant upheaval in the traditional search space.

Traditional search engines are evolving into “answer engines.” This transformation is driven by the need to provide users with direct, conversational responses rather than just a list of links.

The line between chatbot engines and AI-led search engines is becoming increasingly blurred.

While AI in search is not a new concept, the introduction of generative AI and chatbots has necessitated a seismic shift in how search engines operate. For the first time, users can interact with AI in a conversational way, prompting giants like Google and Microsoft to adapt.

On May 14 at Google IO, Google announced the roll-out of AI Overviews as it integrates AI features into its search engine. It is also making upgrades to SGE.

The ultimate goal is to enhance its ability to provide direct answers and engage in conversational search. This evolution signifies Google’s commitment to maintaining its leadership in the search space by leveraging AI to meet user expectations.

In a recent interview on Wired Magazine titled It’s the End of Google Search As We Know It, Google Head of Search, Liz Reid, was clear that:

“AI Overviews like this won’t show up for every search result, even if the feature is now becoming more prevalent.”

As my co-founder, Jim Yu, states in the same article:

“The paradigm of search for the last 20 years has been that the search engine pulls a lot of information and gives you the links. Now the search engine does all the searches for you and summarizes the results and gives you a formative opinion.”

Beyond Google, we are seeing a rise in new, AI-driven search engines like Perplexity,, and Brave, which act more like traditional search engines by providing informational sources, sites, and citations.

These platforms leverage generative AI to deliver comprehensive answers and facilitate follow-up questions, challenging the dominance of established players.

Meta is also entering the fray by utilizing its social graph and real-time data from Google in its AI assistant, further contributing to the convergence of search and AI technologies.

At the same time, according to Digiday, TikTok is starting to reward what it calls “search value.”

Going forward, it’s important to remember that people have diverse needs, and we turn to different platforms for specific purposes.

Just as we go to Amazon for products, Yelp for restaurant suggestions, and YouTube for videos, the rise of AI will only amplify this trend. Each search engine will find its niche, leveraging its strengths to cater to particular user requirements.

ChatGPT is an intriguing case that stands out not for its research capabilities but for its prowess in content creation. While it excels in crafting high-quality content, its research functionalities fall short.

Effective research relies on real-time data, which platforms like ChatGPT currently lack. As we move forward, we expect to see search engines specialize even further, each excelling in specific areas based on its unique strengths and features.

What Does It All Mean For Marketers?

This fast-moving landscape and the convergence of search and AI presents both challenges and opportunities for marketers.

Optimizing for one engine is no longer sufficient; it’s essential to target multiple platforms – each with unique users, demographics, and intents.

Here’s how marketers can adapt and thrive in this dynamic environment.

Optimizing For Different Platforms


  • Strength: Dominates the traditional search space with a vast user base and comprehensive data sources.
  • Tip: Focus on core technical SEO, including schema markup and mobile optimization. Google’s Search Generative Experience means direct answers are becoming more prevalent, so structured data and high-quality content are vital.

Perplexity AI

  • Strength: Provides detailed citations and emphasizes source material, driving referral traffic back to original sites.
  • Tip: Ensure your content is authoritative and well-cited. Being a reliable source will increase the likelihood of your site being referenced, which can drive traffic and enhance brand trust.


  • Strength: Excels in conversational AI, making it suitable for quick answers and personalized interactions.
  • Tip: Create engaging, concise content that answers common questions directly. Utilize conversational language in your SEO strategy to match the style of ChatGPT interactions.

Key Strategies For Marketers

From optimizing technical SEO to harnessing the power of semantic understanding and creativity, these strategies provide a roadmap for success in the era of AI-driven search.

Core Technical SEO

Basics like site speed, mobile-friendliness, and proper schema markup remain crucial. Ensuring your site is technically sound helps all search engines index and rank your content effectively.

Semantic Understanding

Search engines and conversational AI are increasingly focused on semantic search. Optimize for natural language queries and long-tail keywords to match user intent more accurately.

Content And Creativity

High-quality, creative content is more important than ever. Unique, valuable content that engages users will stand out in both traditional and AI-driven search results.

Expanded Role Of SEO

SEO now encompasses content creation, branding, public relations, and AIO. Marketers who can adapt to these roles will be more successful in the evolving search landscape.

Be The Source That Gets Cited

Ensure your content is authoritative and well-researched. Being a primary source will increase the likelihood of citations that drive traffic and enhance credibility.

Get Predictive

Anticipate follow-up questions and provide comprehensive answers. This will not only improve user experience but also increase the chances of your content being highlighted in AI-driven search results.

Brand Authority

Focus on areas where your brand excels. AI search engines prioritize authoritative sources, so build and maintain your reputation in key areas to stay competitive.

The Best Content That Provides The Best Experience Wins

Ultimately, the quality of your content will determine your success. Invest in creating the best possible user experience, from engaging visuals to informative text.

Key Takeaways

Today, search encompasses a dual purpose: It can serve as a standalone assistant-based application or integrate into search engines for AI-led conversational experiences.

This fusion presents marketers with a unique opportunity to elevate their brands by creating accurate and authoritative content that positions them as trusted sources in their respective fields.

Ranking on the first page and being recognized as the go-to source cited by AI engines is no less important than 10 or 20 years ago but is exponentially more difficult.

The good news is that whether it’s Google’s AI engine or newcomers like Perplexity, brands that establish themselves as authorities in their niche stand to benefit immensely.

Marketers need to embrace creativity and collaboration across omnichannel teams. Ensure that your website is visible and accessible to all types of engines, whether traditional or AI-driven.

I’d like to leave you with a few questions to consider as you find your way forward in this complex environment. Pardon the pun, but no one has all the right answers yet.

  • Are chatbots morphing into search engines?
  • How do social platforms differentiate as younger generations look to them as search engines?
  • How would you define a search engine?
  • Who will win the race for user loyalty – traditional search engines infused with AI or new entrants built on generative AI from the beginning?
  • How would you redefine your role as an SEO – are you AI first?

While you consider that, stay proactive and adaptable and position yourself and your company to leverage the diversity and complexity of the search ecosystem to your advantage. In a world of ChatGPT, chatbots, and AI in search, you’re not optimizing for one channel, such as Google or Bing.

Successful optimization in this multifaceted landscape calls for a holistic approach. It’s not about keyword rankings or click-through rates; it’s about unraveling the intricacies of each platform and adjusting your strategies accordingly.

This means optimizing your content for conversational search, tapping into the capabilities of AI to tailor user experiences, and seamlessly integrating across different channels and devices.

Leverage the strengths of each platform to amplify your message by use case and engage with your audience on a deeper level, and you’ll ultimately drive more meaningful results for your business.

More resources: 

Featured Image: Memory Stockphoto/Shutterstock

New Google AI Overviews Documentation & SEO via @sejournal, @martinibuster

Google published new documentation about their new AI Overviews search feature which summarizes an answer to a search query and links to webpages where more information can be found. The new documentation offers important information about how the new feature works and what publishers and SEOs should consider.

What Triggers AI Overviews

AI Overviews shows when the user intent is to quickly understand information, especially when that information need is tied to a task.

“AI Overviews appear in Google Search results when our systems determine …when you want to quickly understand information from a range of sources, including information from across the web and Google’s Knowledge Graph.”

In another part of the documentation it ties the trigger to task-based information needs:

“…and use the information they find to advance their tasks.” “

What Kinds Of Sites Does AI Overviews Link To?

An important fact to consider is that just because AI Overviews is triggered by a user’s need to quickly understand something doesn’t mean that only queries with an informational need will trigger the new search feature. Google’s documentation makes it clear that the kinds of websites that will benefit from AI Overviews links includes “creators” (which implies video creators), ecommerce stores and other businesses. This means that far more than informational websites that will benefit from AI overviews.

The new documentation lists the kinds of sites that can receive a link from the AI overviews:

“This allows people to dig deeper and discover a diverse range of content from publishers, creators, retailers, businesses, and more, and use the information they find to advance their tasks.”

Where AI Overviews Sources Information

AI Overviews shows information from the web and the knowledge graph. Large Language Models currently need to be entirely retrained from the ground up when adding significant amounts of new data. That means that the websites chosen to be displayed in Overviews feature are selected from Google’s standard search index which in turn means that Google may be using Retrieval-augmented generation (RAG).

RAG is a system that sits between a large language model and a database of information that’s external to the LLM. This external database can be a specific knowledge like the entire content of an organization’s HR policies to a search index. It’s a supplemental source of information that can be used to double-check the information provided by an LLM or to show where to read more about the question being answered.

The section quoted at the beginning of the article notes that AI Overviews cites sources from the web and the Knowledge Graph:

“AI Overviews appear in Google Search results when our systems determine …when you want to quickly understand information from a range of sources, including information from across the web and Google’s Knowledge Graph.”

What Automatic Inclusion Means For SEO

Inclusion in AI Overviews is automatic and there’s nothing specific to AI Overviews that publishers or SEOs need to do. Google’s documentation says that following their guidelines for ranking in the regular search is all you have to do for ranking in AI Overviews. Google’s “systems” determine what sites are picked to show up for the topics surfaced in AI Overviews.

All the statements seem to confirm that the new Overviews feature sources data from the regular Search Index. It’s possible that Google filters the search index specially for AI Overviews but offhand I can’t think of any reason Google would do that.

All the statements that indicate automatic inclusions point to the likely possibility that Google uses the regular search index:

“No action is needed for publishers to benefit from AI Overviews.”

“AI Overviews show links to resources that support the information in the snapshot, and explore the topic further.”

“…diverse range of content from publishers, creators, retailers, businesses, and more…”

“To rank in AI Overviews, publishers only need to follow the Google Search Essentials guide.

“Google’s systems automatically determine which links appear. There is nothing special for creators to do to be considered other than to follow our regular guidance for appearing in search, as covered in Google Search Essentials.”

Think In Terms Of Topics

Obviously, keywords and synonyms in queries and documents play a role. But in my opinion they play and oversized role in SEO. There are many ways that a search engine can annotate a document in order to match a webpage to a topic, like what Googler Martin Splitt referred to as a centerpiece annotation. A centerpiece annotation is used by Google to label a webpage with what that webpage is about.

Semantic Annotation

This kind of annotation links webpage content to concepts which in turn gives structure to a unstructured document. Every webpage is unstructured data so search engines have to make sense of that. Semantic Annotation is one way to do that.

Google has been matching webpages to concepts since at least 2015. A Google webpage about their cloud products talks about how they integrated neural matching into their Search Engine for the purpose of annotating webpage content with their inherent topics.

This is what Google says about how it matches webpages to concepts:

“Google Search started incorporating semantic search in 2015, with the introduction of noteworthy AI search innovations like deep learning ranking system RankBrain. This innovation was quickly followed with neural matching to improve the accuracy of document retrieval in Search. Neural matching allows a retrieval engine to learn the relationships between a query’s intentions and highly relevant documents, allowing Search to recognize the context of a query instead of the simple similarity search.

Neural matching helps us understand fuzzier representations of concepts in queries and pages, and match them to one another. It looks at an entire query or page rather than just keywords, developing a better understanding of the underlying concepts represented in them.”

Google’s been doing this, matching webpages to concepts, for almost ten years. Google’s documentation about AI Overviews also mentions that showing links to webpages based on topics is a part of determining what sites are ranked in AI Overviews.

Here’s how Google explains it:

“AI Overviews show links to resources that support the information in the snapshot, and explore the topic further.

…AI Overviews offer a preview of a topic or query based on a variety of sources, including web sources.”

Google’s focus on topics has been a thing for a long time and it’s well past time SEOs lessened their grip on keyword targeting and start to also give Topic Targeting a chance to enrich their ability to surface content in Google Search, including in AI Overviews.

Google says that the same optimizations described in their Search Essentials documentation for ranking in Google Search are the same optimizations to apply to rank in Google Overview.

This is exactly what the new documentation says:

“There is nothing special for creators to do to be considered other than to follow our regular guidance for appearing in search, as covered in Google Search Essentials.”

Read Google’s New SEO Related Documentation On AI Overviews

AI Overviews and your website

Featured Image by Shutterstock/Piotr Swat

Was OpenAI GPT-4o Hype A Troll On Google? via @sejournal, @martinibuster

OpenAI managed to steal the attention away from Google in the weeks leading up to Google’s biggest event of the year (Google I/O). When the big announcement arrived there all they had to show was a language model that was slightly better than the previous one with the “magic” part not even in Alpha testing stage.

OpenAI may have left users feeling like a mom receiving a vacuum cleaner for Mothers Day but it surely succeeded in minimizing press attention for Google’s important event.

The Letter O

The first hint that there’s at least a little trolling going on is the name of the new GPT model, 4 “o” with the letter “o” as in the name of Google’s event,  I/O.

OpenAI says that the letter O stands for Omni, which means everything, but it sure seems like there’s a subtext to that choice.

GPT-4o Oversold As Magic

Sam Altman in a tweet the Friday before the announcement promised “new stuff” that felt like “magic” to him:

“not gpt-5, not a search engine, but we’ve been hard at work on some new stuff we think people will love! feels like magic to me.”

OpenAI co-founder Greg Brockman tweeted:

“Introducing GPT-4o, our new model which can reason across text, audio, and video in real time.

It’s extremely versatile, fun to play with, and is a step towards a much more natural form of human-computer interaction (and even human-computer-computer interaction):”

The announcement itself explained that previous versions of ChatGPT used three models to process audio input. One model to turn audio input into text. Another model to complete the task and output the text version of it and a third model to turn the text output into audio. The breakthrough for GPT-4o is that it can now process the audio input and output within a single model and output it all in the same amount of time that it takes a human to listen and respond to a question.

But the problem is that the audio part isn’t online yet. They’re still working on getting the guardrails working and it will take weeks before an Alpha version is released to a few users for testing. Alpha versions are expected to possibly have bugs while the Beta versions are generally closer to the final products.

This is how OpenAI explained the disappointing delay:

“We recognize that GPT-4o’s audio modalities present a variety of novel risks. Today we are publicly releasing text and image inputs and text outputs. Over the upcoming weeks and months, we’ll be working on the technical infrastructure, usability via post-training, and safety necessary to release the other modalities.

The most important part of GPT-4o, the audio input and output, is finished but the safety level is not yet ready for public release.

Some Users Disappointed

It’s inevitable that an incomplete and oversold product would generate some negative sentiment on social media.

AI engineer Maziyar Panahi (LinkedIn profile) tweeted his disappointment:

“I’ve been testing the new GPT-4o (Omni) in ChatGPT. I am not impressed! Not even a little! Faster, cheaper, multimodal, these are not for me.
Code interpreter, that’s all I care and it’s as lazy as it was before!”

He followed up with:

“I understand for startups and businesses the cheaper, faster, audio, etc. are very attractive. But I only use the Chat, and in there it feels pretty much the same. At least for Data Analytics assistant.

Also, I don’t believe I get anything more for my $20. Not today!”

There are others across Facebook and X that expressed similar sentiments although many others were happy with what they felt was an improvement in speed and cost for the API usage.

Did OpenAI Oversell GPT-4o?

Given that the GPT-4o is in an unfinished state it’s hard not to miss the impression that the release was timed to coincide with and detract from Google I/O. Releasing it on the eve of Google’s big day with a half-finished product may have inadvertently created the impression that GPT-4o in the current state is a minor iterative improvement.

In the current state it’s not a revolutionary step forward but once the audio portion of the model exits Alpha testing stage and makes it through the Beta testing stage then we can start talking about revolutions in large language model. But by the time that happens Google and Anthropic may already have staked a flag on that mountain.

OpenAI’s announcement paints a lackluster image of the new model, promoting the performance as on the same level as GPT-4 Turbo. The only bright spots is the significant improvements in languages other than English and for API users.

OpenAI explains:

  • “It matches GPT-4 Turbo performance on text in English and code, with significant improvement on text in non-English languages, while also being much faster and 50% cheaper in the API.”

Here are the ratings across six benchmarks that shows GPT-4o barely squeaking past GPT-4T in most tests but falling behind GPT-4T in an important benchmark for reading comprehension.

Here are the scores:

  • MMLU (Massive Multitask Language Understanding)
    This is a benchmark for multitasking accuracy and problem solving in over fifty topics like math, science, history and law. GPT-4o (scoring 88.7) is slightly ahead of GPT4 Turbo (86.9).
  • GPQA (Graduate-Level Google-Proof Q&A Benchmark)
    This is 448 multiple-choice questions written by human experts in various fields like biology, chemistry, and physics. GPT-4o scored 53.6, slightly outscoring GPT-4T (48.0).
  • Math
    GPT 4o (76.6) outscores GPT-4T by four points (72.6).
  • HumanEval
    This is the coding benchmark. GPT-4o (90.2) slightly outperforms GPT-4T (87.1) by about three points.
  • MGSM (Multilingual Grade School Math Benchmark)
    This tests LLM grade-school level math skills across ten different languages. GPT-4o scores 90.5 versus 88.5 for GPT-4T.
  • DROP (Discrete Reasoning Over Paragraphs)
    This is a benchmark comprised of 96k questions that tests language model comprehension over the contents of paragraphs. GPT-4o (83.4) scores nearly three points lower than GPT-4T (86.0).

Did OpenAI Troll Google With GPT-4o?

Given the provocatively named model with the letter o, it’s hard to not consider that OpenAI is trying to steal media attention in the lead-up to Google’s important I/O conference. Whether that was the intention or not OpenAI wildly succeeded in minimizing attention given to Google’s upcoming search conference.

Does a language model that barely outperforms its predecessor worth all the hype and media attention it received? The pending announcement dominated news coverage over Google’s big event so for OpenAI the answer is clearly yes, it was worth the hype.

Featured Image by Shutterstock/BeataGFX

OpenAI Announces ChatGPT 4o Omni via @sejournal, @martinibuster

ChatGPT announced a new version of ChatGPT that can accept audio, image and text inputs and also generate outputs in audio, image and text. OpenAI is calling the new version of ChatGPT 4o, with the “o” standing for “omni” which is a combining form word that means “all”.

ChatGPT 4o (Omni)

OpenAI described this new version of ChatGPT as a progression toward more natural human and machine interactions which responds to user inputs at the same speed as a human to human conversations. The new version matches ChatGPT 4 Turbo in English and significantly outperforms Turbo in other languages. There is a significant improvement in API performance, increasing in speed and operating 50% less expensively.

The announcement explains:

“As measured on traditional benchmarks, GPT-4o achieves GPT-4 Turbo-level performance on text, reasoning, and coding intelligence, while setting new high watermarks on multilingual, audio, and vision capabilities.”

Advanced Voice Processing

The previous method for communicating with voice involved bridging together three different models to handle transcribing voice inputs to text where the second model (GPT 3.5 or GPT-4) processes it and outputs text and a third model that transcribes the text back into audio. That method is said to lose nuances in the various translations.

OpenAI described the downsides of the previous approach that are (presumably) overcome by the new approach:

“This process means that the main source of intelligence, GPT-4, loses a lot of information—it can’t directly observe tone, multiple speakers, or background noises, and it can’t output laughter, singing, or express emotion.”

The new version doesn’t need three different models because all of the inputs and outputs are handled together in one model for end to end audio input and output. Interestingly, OpenAI states that they haven’t yet explored the full capabilities of the new model or fully understand the limitations of it.

New Guardrails And An Iterative Release

OpenAI GPT 4o features new guardrails and filters to keep it safe and avoid unintended voice outputs for safety. However today’s announcement says that they are only rolling out the capabilities for text and image inputs and text outputs and a limited audio at launch. GPT 4o is available for both free and paid tiers, with Plus users receiving 5 times higher message limits.

Audio capabilities are due for a limited alpha-phase release for ChatGPT Plus and API users within weeks.

The announcement explained:

“We recognize that GPT-4o’s audio modalities present a variety of novel risks. Today we are publicly releasing text and image inputs and text outputs. Over the upcoming weeks and months, we’ll be working on the technical infrastructure, usability via post-training, and safety necessary to release the other modalities. For example, at launch, audio outputs will be limited to a selection of preset voices and will abide by our existing safety policies.”

Read the announcement:

Hello GPT-4o

Featured Image by Shutterstock/Photo For Everything

OpenAI Expected to Integrate Real-Time Data In ChatGPT via @sejournal, @martinibuster

Sam Altman, CEO of OpenAI, dispelled rumors that a new search engine would be announced on Monday, May 13. Recent deals have raised the expectation that OpenAI will announce the integration of real-time content from English, Spanish, and French publications into ChatGPT, complete with links to the original sources.

OpenAI Search Is Not Happening

Many competing search engines have tried and failed to challenge Google as the leading search engine. A new wave of hybrid generative AI search engines is currently trying to knock Google from the top spot with arguably very little success.

Sam Altman is on record saying that creating a search engine to compete against Google is not a viable approach. He suggested that technological disruption was the way to replace Google by changing the search paradigm altogether. The speculation that Altman is going to announce a me-too search engine on Monday never made sense given his recent history of dismissing the concept as a non-starter.

So perhaps it’s not a surprise that he recently ended the speculation by explicitly saying that he will not be announcing a search engine on Monday.

He tweeted:

“not gpt-5, not a search engine, but we’ve been hard at work on some new stuff we think people will love! feels like magic to me.”

“New Stuff” May Be Iterative Improvement

It’s quite likely that what’s going to be announced is iterative which means it improves ChatGPT but not replaces it. This fits into how Altman recently expressed his approach with ChatGPT.

He remarked:

“And it does kind of suck to ship a product that you’re embarrassed about, but it’s much better than the alternative. And in this case in particular, where I think we really owe it to society to deploy iteratively.

There could totally be things in the future that would change where we think iterative deployment isn’t such a good strategy, but it does feel like the current best approach that we have and I think we’ve gained a lot from from doing this and… hopefully the larger world has gained something too.”

Improving ChatGPT iteratively is Sam Altman’s preference and recent clues point to what those changes may be.

Recent Deals Contain Clues

OpenAI has been making deals with news media and User Generated Content publishers since December 2023. Mainstream media has reported these deals as being about licensing content for training large language models. But they overlooked a a key detail that we reported on last month which is that these deals give OpenAI access to real-time information that they stated will be used to give attribution to that real-time data in the form of links.

That means that ChatGPT users will gain the ability to access real-time news and to use that information creatively within ChatGPT.

Dotdash Meredith Deal

Dotdash Meredith (DDM) is the publisher of big brand publications such as Better Homes & Gardens, FOOD & WINE, InStyle, Investopedia, and People magazine. The deal that was announced goes way beyond using the content as training data. The deal is explicitly about surfacing the Dotdash Meredith content itself in ChatGPT.

The announcement stated:

“As part of the agreement, OpenAI will display content and links attributed to DDM in relevant ChatGPT responses. …This deal is a testament to the great work OpenAI is doing on both fronts to partner with creators and publishers and ensure a healthy Internet for the future.

Over 200 million Americans each month trust our content to help them make decisions, solve problems, find inspiration, and live fuller lives. This partnership delivers the best, most relevant content right to the heart of ChatGPT.”

A statement from OpenAI gives credibility to the speculation that OpenAI intends to directly show licensed third-party content as part of ChatGPT answers.

OpenAI explained:

“We’re thrilled to partner with Dotdash Meredith to bring its trusted brands to ChatGPT and to explore new approaches in advancing the publishing and marketing industries.”

Something that DDM also gets out of this deal is that OpenAI will enhance DDM’s in-house ad targeting in order show more tightly focused contextual advertising.

Le Monde And Prisa Media Deals

In March 2024 OpenAI announced a deal with two global media companies, Le Monde and Prisa Media. Le Monde is a French news publication and Prisa Media is a Spanish language multimedia company. The interesting aspects of these two deals is that it gives OpenAI access to real-time data in French and Spanish.

Prisa Media is a global Spanish language media company based in Madrid, Spain that is comprised of magazines, newspapers, podcasts, radio stations, and television networks. It’s reach extends from Spain to America. American media companies include publications in the United States, Argentina, Bolivia, Chile, Colombia, Costa Rica, Ecuador, Mexico, and Panama. That is a massive amount of real-time information in addition to a massive audience of millions.

OpenAI explicitly announced that the purpose of this deal was to bring this content directly to ChatGPT users.

The announcement explained:

“We are continually making improvements to ChatGPT and are supporting the essential role of the news industry in delivering real-time, authoritative information to users. …Our partnerships will enable ChatGPT users to engage with Le Monde and Prisa Media’s high-quality content on recent events in ChatGPT, and their content will also contribute to the training of our models.”

That deal is not just about training data. It’s about bringing current events data to ChatGPT users.

The announcement elaborated in more detail:

“…our goal is to enable ChatGPT users around the world to connect with the news in new ways that are interactive and insightful.”

As noted in our April 30th article that revealed that OpenAI will show links in ChatGPT, OpenAI intends to show third party content with links to that content.

OpenAI commented on the purpose of the Le Monde and Prisa Media partnership:

“Over the coming months, ChatGPT users will be able to interact with relevant news content from these publishers through select summaries with attribution and enhanced links to the original articles, giving users the ability to access additional information or related articles from their news sites.”

There are additional deals with other groups like The Financial Times which also stress that this deal will result in a new ChatGPT feature that will allow users to interact with real-time news and current events .

OpenAI’s Monday May 13 Announcement

There are many clues that the announcement on Monday will be that ChatGPT users will gain the ability to interact with content about current events.  This fits into the terms of recent deals with news media organizations. There may be other features announced as well but this part is something that there are many clues pointing to.

Watch Altman’s interview at Stanford University

Featured Image by Shutterstock/photosince