Ecommerce Management Advisors
Ecommerce Management Advisors
Reddit partners with OpenAI to integrate content into ChatGPT.
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 You.com, 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.
Screenshot from Wikipedia, May 2024At 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.
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.
Image from 2024 AI Index Report from Stanford University, May 2024For 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:
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.
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:
Image from author, May 2024As more overlays and overlaps occur, the definitions of what constitutes a chatbot, an AI assistant, and a search engine may need to be redefined.
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:
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.
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, You.com, 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.
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.
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.
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.
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.
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.
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.
Ensure your content is authoritative and well-researched. Being a primary source will increase the likelihood of citations that drive traffic and enhance credibility.
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.
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.
Ultimately, the quality of your content will determine your success. Invest in creating the best possible user experience, from engaging visuals to informative text.
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.
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
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.
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.” “
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.”
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.”
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.”
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.
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.”
Featured Image by Shutterstock/Piotr Swat
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 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.
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.
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.
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:
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:
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
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”.
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.”
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.
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:
Featured Image by Shutterstock/Photo For Everything
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.
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.”
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.
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 (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.
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 .
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.
Featured Image by Shutterstock/photosince
Eric Schmidt, former CEO of Google, said in an interview that Google’s mission is to organize the world’s information, not to provide blue links. Schmidt’s pragmatic statements seem to describe a future where websites are unnecessary and advertising is increasingly effective.
The ex-CEO’s prediction of the future of Google may seems to contradict statements by Google’s current CEO that assert that search and the web will continue to coexist as well as by Danny Sullivan who has many times said that a healthy web ecosystem is important to Google.
There are many actions taken by Google in the past that indicate that Eric Schmidt’s prediction fit perfectly with how Google has ranked sites in the past.
The early days of the web were navigated not just by search engines but by curated web directories that served as starting places for Internet users to go find information, hopping from link to link in a hyperlinked Internet. The idea was that hyperlinks was how users could find information.
Google Search not only ranked webpages from web directories, Google itself hosted a version of DMOZ, an open source web directory that was curated by thousands of volunteers much like Wikipedia is maintained by volunteer editors today.
But a day came when Google stopped ranking directories and the reason given was that it was a better user experience show answers and not links to pages with more links (this event is likely archived somewhere on the WebmasterWorld forum, it happened a long time ago).
Then there are Google’s answers for flight tracking, package tracking, stock quotes, the time and weather information that has zero links.
Eric Schmidt’s assertion that Google will take advantage of AI to show answers fits into Google’s design principle that showing answers is a good user experience if it fully satisfies the query.
The only difference between the old days and now is that Google is that AI has (mostly) unlocked the ability to show answers without linking to any websites.
So it’s not far-fetched that Google may decide that showing answers is a good user experience, there is precedence for that approach.
AI Is Underhyped
Schmidt put forward the idea that AI is not overhyped but in fact is underhyped.
He observed:
“I hate to tell you but I think this stuff is underhyped not overhyped. Because the arrival of intelligence of a non-human form is really a big deal for the world.
It’s coming. It’s here. It’s about to happen. It happens in stages. …the reason I’m saying it’s underhyped is you’re seeing the future of reasoning, the future of human interaction, the future of research, the future of planning is being invented right now.
There’s something called infinite context windows, which means that you can — it’s like having an infinite short-term memory, which I certainly don’t have, where you can basically keep feeding it information and it keeps learning and changing.”
The interviewer asked Schmidt about a future where AI answers questions without links to sources on the web.
The interviewer asked this question:
“In a world where the AI provides the answer, and doesn’t necessarily need to send you to 12 places where you’re going to go find it yourself… what happens to all of that?
Eric Schmidt answered:
“It’s pretty important to understand that Google is not about blue links, it’s about organizing the world’s information. What better tool than the arrival of AI to do that better.
Do you think you can monetize that? You betcha.”
It has to be reiterated that Eric Schmidt (LinkedIn profile) is no longer the CEO at Google or Executive Chairman & Technical Advisor at Alphabet (for four years now). His opinions may not reflect the current thinking within Google.
However it’s not unreasonable to speculate that maybe he is saying out loud what those within Google cannot officially discuss.
The most solid information we have now is that Google Search will continue to have links but that Google (and others like Apple) are moving ahead with AI assistants on mobile devices that can answer questions and perform tasks.
A new report by Microsoft and LinkedIn reveals the rapid adoption of AI tools and skills in the marketing industry.
According to the 2024 Work Trend Index Annual Report, which surveyed over 31,000 people across 31 countries, marketing professionals who leverage AI enjoy a competitive advantage.
Employers recognize the efficiency gains AI capabilities provide in marketing roles and increasingly seek applicants with those skills.
Karim R. Lakhani, Chair of the Digital Data Design Institute at Harvard, states in the report:
“Marketers are harnessing the power of AI to work smarter, not just faster. It’s enabling them to focus on higher-value, creative work while automating more routine tasks.”
Here are some highlights from the report illustrating the need to develop an AI skill set to remain competitive.
The survey data reveals a strong preference among business leaders for candidates and employees with AI skills.
A majority, 66%, stated they wouldn’t consider hiring candidates lacking AI proficiency.
Further, 71% expressed a preference for less experienced job seekers with AI skills over more seasoned professionals without that expertise.
This inclination was pronounced in creative fields like marketing and design.
Michael Platt, a neuroscience professor at the Wharton School, states in the report:
“AI is redefining what it means to be a competitive marketer in today’s digital landscape. Professionals who can effectively integrate AI into their work are positioning themselves as invaluable assets to their organizations.”
The report indicates that early-career marketers who develop AI skills could benefit significantly.
77% of leaders reported that employees adept at leveraging AI would be trusted with greater responsibilities earlier in their careers than their peers without AI skills.
Data from LinkedIn shows that job postings highlighting AI tools and applications have seen a 17% increase in application growth compared to those that don’t mention AI.
Additionally, 54% of early-career employees cited access to AI technologies as a key factor influencing their choice of employer.
Organizations that provide AI training and support for their marketing teams likely have an advantage in attracting top talent.
The widespread adoption of AI in marketing signifies a shift in the skills and capabilities necessary for succeeding in this rapidly evolving industry.
As AI transforms marketing approaches, professionals who fail to adapt risk being left behind.
The 2024 Work Trend Index Annual Report’s findings are relevant to marketing professionals at all levels. They demonstrate that AI proficiency is necessary for career advancement and job market competitiveness.
Additionally, the report highlights businesses’ role in fostering an AI-driven culture.
Companies investing in AI tools, training, and employee support will be better positioned to attract and retain top talent, drive innovation, and achieve better results.
For marketing professionals to succeed in the AI era, the report suggests:
These recommendations can help you future-proof your career and advance in an increasingly competitive field.
Featured Image: eamesBot/Shutterstock
A report based on independently verified accounts notes that Apple’s Safari 18 will come with an Intelligent Search feature that summarize webpages in response to search queries and there may be a new feature called Web Eraser that allows users to permanently remove text, images, advertisements from webpages.
Apple has been gathering website data for years through its Internet crawler that uses the user agent, Applebot. The harvested data has in the past been used in the context of Siri and Apple’s Spotlight Suggestions feature.
Many in the search community have been aware of Applebot and have welcomed the prospect of a new search engine from Apple but despite constant crawling Apple has not released a search engine. A reason Apple has not released a standalone search engine may be that it’s become apparent that the best way to challenge Google Search is with a technology that replaces search engines altogether, much like how the Apple iPhone made digital cameras obsolete.
The latest news coming out about Safari 18 appears to confirm that supplanting Google is the strategy that Apple is pursuing.
Duane Forrester, formerly of Bing and now at Yext, commented on the potentially disruptive quality of Apple’s new technology:
“Intelligent Search could change how iOS consumers get, see and interact with content and answers. We are likely to see Apple taking a big step forward, into the consumer-accessible AI conversation which has been dominated by OpenAI, Microsoft, and Google et al to this point. Our phones are about to become AI-enabled and that could be ground zero for AI Agents. It’s going to impact and potentially change consumer behavior and be the gateway to new experiences.“
The approach Apple is taking has the potential to disrupt not just search engines but also the search optimization and publishing industry, who have have been waiting years for an Apple search engine. But the extent of that disruption depends on how Apple implements their AI web search summarizer.
Although news reports didn’t provide details as to how the new search result summaries will appear, it seems reasonable to speculate that Apple will provide attribution in the form of a link to websites so that users can click through to the website.
Duane Forrester speculated:
“Apple was just in court for Google’s anti-trust trial and likely isn’t keen to dive into “monopoly” waters themselves. My guess is that any “result” will have a source.”
This is what was reported:
“With the release of Safari 18, Apple is expected to introduce article summarization through a new Intelligent Search feature — meaning users will have the option to generate a brief summary of any webpage currently on screen.
Apple’s built-in AI software can analyze the keywords and phrases within a webpage or document and generate a short summary containing only the most important information.”
SEOs have been giddy about the prospect of an Apple search engine for years. It now appears that the Google Killer they’ve been waiting for could possibly result in less traffic from search queries but to what extent it’s impossible to tell at this point.
One search marketing expert mused in a private chat that if Intelligent Search summarizes more than it links out then that may signal it’s time to start selling off the domain names they’ve invested in.
An interesting feature of the text summarization is that the technology that creates the summary (called Ajax) resides on the mobile device itself. What Ajax does is extract keywords, entities, and use the data to identify the topic and a loose summary of a webpage which is then turned into a text summary for the user.
This is how the functionality is described:
“In analyzing texts, the software takes into account all relevant information available. It can recognize and classify entities such as companies, people, and locations. For instance, if a name appears at the top of a text, the software will likely recognize the name as belonging to the text’s author.”
As if an Apple search summarizer isn’t bad enough Apple reportedly has a “Web Eraser” functionality planned for Safari. Web Eraser is a feature that removes content from webpages so that site visitors don’t have to look at it anymore. Things like advertising, videos, comments, suggested reading and maybe even popups could be permanently blocked by the Web Eraser. Once a user “erases” a block of content from a webpage that block stays erased for the site visitor on subsequent visits.
According to the a report about the Apple Web Eraser:
“The feature is expected to build upon existing privacy features within Safari and will allow users to erase unwanted content from any webpage of their choosing. Users will have the option to erase banner ads, images, text or even entire page sections, all with relative ease.”
It’s a natural response to experience anxiety in the face of changes. For many, the dawning of AI Search is their first experience of a major change. But for those of us who have been in search for 25+ years we have experienced and grown accustomed to sudden and transformative changes that alter publishing and SEO. Like Duane, I tend to feel that Apple’s implementation of an AI search engine that summarizes websites will be disruptive but not to the point that it harms websites. It’s in Apple’s self-interest to not disrupt the Internet to the point of extinction.
Featured Image by Shutterstock/frantic00
Anthropic announced a new Team plan that gives businesses the opportunity to access more powerful features with increased management and security controls that make it a strong option for companies to consider.
Modern SaaS technologies for businesses generally come with a team version that allows collaboration within a company and also gives security and control to management so that proprietary documents don’t accidentally leak to the public.
Open AI launched their ChatGPT Team plan in January 2024, which offered a secured workspace for users within a company at a reasonable monthly and yearly subscription model. Anthropic has finally launched their own Team version of Claude with features that exceed what’s offered by ChatGPT Teams.
Claude is known as a great model for creative purposes and a team version that’s more powerful than the regular paid version makes it even more attractive but the important question is how does it compare to ChatGPT Team?
ChatGPT Team is $5/month cheaper (on the yearly billing plan) than Anthropic’s collaborative plan. Otherwise they are both priced at $30/month per user.
Claude Team is a step up from ChatGPT’s Team in one important way and that’s the context window. A context window is a metric of how much data a model can process at one time. The larger the context window the more data the model can analyze in one batch.
ChatGPT Team offers a context window of 32k but Anthropic Claude Team users enjoy a whopping 200k context window which is about 150,000 words or 500 pages of text.
When it comes to collaborating within a company, Claude Team is a better value than the regular Pro version because it provides more usage than the regular Pro plan which means that individual users can do more work than users on the Pro plan. The Team version also offers collaborative features like the ability to create a shared database that can be used for projects. Beyond that it offers administrative tools for managing users and billing.
More features are on the way according to the official announcement:
“In the coming weeks, we will be releasing additional collaboration features, including citations from reliable sources to verify AI-generated claims, integrations with data repositories like codebases or CRMs, and iterating with colleagues on AI-generated documents or projects—all while maintaining the highest standards of security and safety.”
Read the announcement here: