Ever wondered if AI chat interfaces could revolutionize your search experience? Imagine having a virtual assistant that not only answers your queries but understands the context and nuances behind them. In this episode, Philip Mastroianni takes you on a journey through the world of AI-powered chatbots like ChatGPT, shedding light on their growing popularity and transformative impact on traditional search engines like Google. We’ll discuss Perplexity AI, a unique search engine that combines conversational abilities with real-time data retrieval, offering a more personalized and interactive approach to finding information. Philip compares Perplexity's strengths and limitations against traditional search engines, providing a comprehensive look at how these advanced tools are changing the landscape of online searches.
Looking to the future, Philip explores the emerging trend of RAG custom chats and their potential to provide even more personalized and nuanced search experiences. While these specialized chats require substantial upfront effort to curate their knowledge base, the payoff can be significant for users within specific knowledge domains. The episode also tackles the critical issues of trust and credibility in AI-generated content, highlighting the necessary balance between innovative AI tools and traditional search engines. This conversation delves into how AI technology might revolutionize SEO and information retrieval while emphasizing the continued importance of a diverse ecosystem of search tools tailored to different user needs and preferences. Don’t miss this insightful discussion on the future of search technology!
Ever wondered if AI chat interfaces could revolutionize your search experience? Imagine having a virtual assistant that not only answers your queries but understands the context and nuances behind them. In this episode, Philip Mastroianni takes you on a journey through the world of AI-powered chatbots like ChatGPT, shedding light on their growing popularity and transformative impact on traditional search engines like Google. We’ll discuss Perplexity AI, a unique search engine that combines conversational abilities with real-time data retrieval, offering a more personalized and interactive approach to finding information. Philip compares Perplexity's strengths and limitations against traditional search engines, providing a comprehensive look at how these advanced tools are changing the landscape of online searches.
Looking to the future, Philip explores the emerging trend of RAG custom chats and their potential to provide even more personalized and nuanced search experiences. While these specialized chats require substantial upfront effort to curate their knowledge base, the payoff can be significant for users within specific knowledge domains. The episode also tackles the critical issues of trust and credibility in AI-generated content, highlighting the necessary balance between innovative AI tools and traditional search engines. This conversation delves into how AI technology might revolutionize SEO and information retrieval while emphasizing the continued importance of a diverse ecosystem of search tools tailored to different user needs and preferences. Don’t miss this insightful discussion on the future of search technology!
Speaker 1:
Welcome to the Opinionated SEO. I'm Philip Mastroianni, and today I want to talk about something that's been on my mind lately and that's really looking at the rise of these AI-powered chat bots and interfaces and how things have been shifting in the way we're searching online, and that really got me thinking. What does this really mean for search engines like Google? As someone who works in SEO, I'm always curious about how things might change the way we approach search in general. In this episode, I'm going to explore the idea that AI chats are going to erode the market share of traditional search engines, and not just by a few percentage points, but I mean like 10-20%. We're going to take a look at an example of an AI search engine Perplexity AI and discuss its strengths and weaknesses, compare it to some other traditional search engines like Google and also RAG interfaces, and how they step up. What's behind this potential shift in search behavior? Well, it's all about AI chats. You've probably heard of them, right? Chatgpt You've probably used them yourself. There are these conversational interfaces that can understand natural language and actually respond with helpful answers. Now AI chats are becoming increasingly popular. It's really not hard to see why they offer a more personalized and interactive experience compared to traditional search engines. You can ask follow-up questions, get more detailed explanations. You can even have a conversation that feels a lot more human-like. But what really sets these apart is their ability to be trained on specific data sets. This means you can have a highly tailored discussion that's focused on a particular topic or industry, and the best part is, you can refine your questions and get more precise answers without having to sift through a ton of irrelevant search results. It's like having a personal expert or researcher at your fingertips and they're providing exactly the information you need. I saw a great example of a chat that was trained on a very specific professional camera's manual and the person was asking the chatbot questions that didn't quite align with the right terminology. The chatbot understood the similarity with the topic and knew the information that they were actually looking for, and was able to retrieve and answer their question and help them understand how to achieve what they were looking for, even though they didn't know what the feature was called. This is like having a personal assistant that can help you find exactly what you're looking for without having to dig through a bunch of irrelevant search results. And that's what's so exciting about AI chats they have the potential to revolutionize the way we search for information online. Instead of relying on broad search queries, we can have more focused and targeted conversations that get us exactly what we need With the rise of these powerful AI chat interfaces, it got me thinking. What does this mean for the future of traditional search engines like Google?
Speaker 1:
One platform that's trying to blend the best of both worlds is Perplexity AI. Perplexity is an AI-powered search engine designed to provide a more conversational and interactive search experience. So, unlike a typical Google search, perplexity aims to understand the context and nuance much more behind your queries and deliver very specific, tailored responses that feel much more like talking to a knowledgeable expert. One of the other things that they have that's outside of many other types of chatbots is they pull real-time data. So let's take a little bit of a closer look at Perplexity what they have to offer and maybe how it compares to the search experience that we're more familiar with on Google.
Speaker 1:
Perplexity is an AI-powered search engine that aims to provide a more conversational and interactive search experience. But what does that actually look like in practice? One of Perplexity's key strengths is its ability to excel at in-depth research and analysis, unlike a traditional search engine that may just return a list of links. Perplexity can provide answers by synthesizing that information from multiple sources in real time. So, for example, let's say you need to do some thorough research on a complex topic like environmental impact of cryptocurrency mining.
Speaker 1:
With Perplexity, you could ask a detailed question and it would respond with a well-structured summary, citing relevant data and studies, to give you a holistic understanding of the issue. It can help you understand it better by teaching you what certain terms are, as well as giving you the information in different ways. It allows you to keep following up with those questions and asking to help change the response so that you can understand it easier. And this is how the tool shines in these types of conversational queries Its natural language processing abilities allow you to ask follow-up questions and engage in a back and forth dialogue so you can really fully explore a topic. And this is great for those times when you have a lot of nuanced questions on your mind and want a more guided research experience, or don't quite understand the topic and need additional guidance to really truly understand and to dig in, so to give an idea of how a search might be performed that ends up tailoring to your specific needs for a real world scenario.
Speaker 1:
Let's say you have an upcoming job interview for a senior marketing manager role at a tech company. You could ask perplexity something like what are the most important things I should know and prepare for in a job interview for a senior marketing manager position at a tech company? I'm currently a senior manager and looking to move to a different company. Well, rather than just returning a generic list of interview tips, perplexity would try to understand the specific context of your situation the seniority level, the industry, your own background. Context of your situation, the seniority level, the industry, your own background. The content is much different, based on the context of your question, and it allows for follow-ups that continue to adhere to that context.
Speaker 1:
Now, perplexity is not without its limitations. It's an AI-powered system, it can sometimes have biases, blind spots, and it's knowledge-based. And though it does pull from a wide range of sources, there could be certain niche or specific topics where its coverage is just not as comprehensive or it doesn't have that information. It doesn't know where to search to find it. So, while perplexity represents like a really interesting evolution in search, it's important to be aware of both its strengths and weaknesses and when it might be the optimal tool compared to a more traditional approach like a Google search. Now you're also getting mostly summarized data from third-party sources and you may want to fact check with the citations given. Now, in many cases, this isn't an issue, but in more critical areas it may be better to just go straight to the source. So if you're looking to do a quick factual lookup finding business hours, addresses, weather forecasts Google search results may be more straightforward and immediately useful.
Speaker 1:
Perplexity excels at providing more of the nuanced, synthesized information, but sometimes you just need a simple, direct answer found from a website. Google search also tends to be better suited for things like localized search, finding nearby restaurants, shops or services and because of its deep integration with maps, reviews and other local data, it really makes it the go-to for those kinds of location-based searches and for certain tasks like online shopping or travel planning, google search results often are more directly actionable. It's tight connections to e-commerce platforms and travel booking sites can make it more convenient for those types of use cases. If you're not sure where you want to travel to, perplexity may be a great way to start asking those kinds of questions and narrowing things down, but actually booking your flight and coming up with some of those nuanced components to your search, google may be the way to go. Sometimes you're just trying to access a specific website or online resource, and Google can usually get you there much more efficiently than an AI chat interface like Perplexity. The direct search results and website links are often the quickest path. Especially if you don't know the right domain for a brand or restaurant, google may be the fastest solution. Perplexity shines for in-depth research analysis, conversational queries where you need a more tailored, nuanced response, but Google remains the optimal choice for quick factual lookups, localized search, e-commerce and directly accessing websites. Now, understanding the strengths and limitations of each approach really is going to help you determine the right type of tool for the job.
Speaker 1:
And while perplexity and Google search each have their own strengths and weaknesses, there's another category of AI-powered interfaces that are worth exploring, and this is the general knowledge chatbot. So you've got platforms like ChatGPT, anthropics, cloud. They've really captured just a ton of attention for their ability to engage in free-flowing conversation on a wide range of topics, unlike search engines that result lists of results or more specialized AI assistants like Perplexity, which work to summarize those results. Generally, these general knowledge chatbots are designed to be knowledgeable companions that can help you explore ideas, answer questions and even tackle complex tasks. One thing to note is that there are open source models that can be run locally on your computer as well, and so you could have these types of conversations with these general knowledge chatbots without even having internet.
Speaker 1:
The key differentiator as well is the breadth of knowledge base. Rather than being trained on a specific domain or dataset, these chatbots have been exposed to a massive amount of information spanning science, history, some current events, past events, creative writing, history you name it. This allows them to converse on just about any subject, and they can draw insights and make connections that a traditional search just might miss. But it's important to note that, while these general chatbots have impressive depths of knowledge, that information is not nearly or necessarily as up-to-date as something like Perplexity's real-time data pulled directly from the web. The free versions of these chatbots, like your chat GPTs in particular, may have knowledge bases that can become stale over time, especially when it comes to rapidly evolving current events or time-sensitive information. If you're running a local model, it is literally when that model is created is the last cutoff, so it doesn't have any new information that it can add to it. That said, these general knowledge.
Speaker 1:
Chatbots aren't without their strengths. Their ability to converse on a vast array of subjects, making connections and providing nuanced insights can be incredibly valuable for open-ended exploratory queries where you're looking to dive deep into a topic. When weighing the different AI-powered search and conversational options, it's important to understand the unique strengths and trade-offs of each approach. Perplexity, google search and general chatbots all have their place in the evolving landscape of how we find and engage with information. We've explored the capabilities of perplexity, which provides a more specialized data-driven search experience, as well as the broad knowledge and conversational abilities of general AI chatbots.
Speaker 1:
But there's another interesting category of AI-powered interfaces worth discussing RAG custom chats. Rag stands for Retrieval, augmented Generation, and it refers to the type of AI system that can take a specific piece of knowledge or information and then engage in a customized question and answer dialogue around that content. For example, let's say there's a detailed industry report on the impact of artificial intelligence on business strategy and operation. With RAG Custom Chat Interface, you could upload that report and then ask the AI a series of follow-up questions, everything from high-level summaries to drilling down into specific data points, emerging trends and recommended approaches. The AI would leverage the information in the report to provide answers, clarifications and even suggest additional areas for exploration. It could walk you through key findings, help you interpret the data and even brainstorm how the insights from the report could be applied to your own business challenges.
Speaker 1:
The key strength of RAG custom chats is their ability to provide a truly personalized interactive experience. Unlike a general search engine or chatbot, which may struggle to give comprehensive or contextual responses, these AI assistants are laser focused on a specific knowledge domain. This allows them to have a more nuanced back and forth discussion, really helps users get the most out of the available information. However, rag custom chats aren't without limitation, so for one, they require the upfront work of actually curating and getting that knowledge base that the AI is going to draw from. This can be possibly time consuming and could limit the breadth of topics available compared to a more open-ended chatbot. Additionally, the quality of the response is still dependent on the depth and accuracy of the underlying data. So bad data in, bad data out, and it's really important to note that the more quality data you put in there, the more that it's going to have to work with. But when you start asking questions outside of that data set, it's going to have to fall back onto its just general knowledge base, and so it's really important to make sure that that stays focused.
Speaker 1:
Now, the RAC systems can provide very tailored insights, but they aren't immune to biases or gaps in their knowledge base. So when you're comparing the different RAC custom chats to other AI-powered tools that we discussed, the key distinction is really that level of focus and customization. Perplexity excels at providing wide-ranging, up-to-date information. General chatbots are great at open-ended exploration. Rag custom chats, on the other hand, aim to deliver a highly curated interactive experience centered around a unique, specific knowledge domain. So, ultimately, each approach has its own strengths and weaknesses, and the optimal choice will really depend on the user's specific needs and the type of information they're seeking. Understanding the unique capabilities of RAC, perplexity, general chatbots and Google can help you determine the right tool for the job. We covered a lot of ground here AI chatbots, perplexity chat, gpt, google search, how they all kind of have their own nuanced ways of searching, even the specialized capabilities of RAG custom chats. It's really that dive into the evolving world of information, discovery and search. But the big question is what does all of this mean for the future, and especially the future of Google search? So let's be real Traditional search engines like Google have pretty much dominated the game for the past couple of decades and they've certainly tried to stay ahead of the curve, rolling out their own AI-powered search features like SGE and, more recently, ai overviews.
Speaker 1:
Bing has partnered up with OpenAI and they've got their own going, but the reception to these efforts has really been lukewarm at best. A big part of the challenge is that these AI-infused search results don't quite capture the nuanced and conversational flow of a true chatbot experience. The responses can feel a bit stilted and disconnected, lacking that fluidity and contextual understanding that makes platforms like Perplexity, a RAG, custom chat or your just general chat GPTs just so compelling. There's also the issue of trust and credibility. Google's search results have long been seen as a gold standard for authoritative, up-to-date information, but when you start injecting more AI generated content into the mix, users can start to question the reliability and accuracy of what they're seeing. Remember, google presented us with what they felt was the best result and we made the choice of which ones we were going to look at.
Speaker 1:
The AI powering these search features, while impressive the technology is incredibly impressive they still exhibit biases. They have gaps in their knowledge. They lack the nuance that traditional search engines have largely been able to avoid, and users may be wary of relying on AI curated results, especially for important decisions or those high-stake queries. I don't foresee Google ever going away for those types of requests, so the idea of blending the best of traditional search and conversational AI is enticing. The execution has sucked. No one has been impressed with it so far. The user experience just doesn't feel as seamless or trustworthy as a truly dedicated AI interface or a well-established search engine.
Speaker 1:
At the end of the day, I think the key is having a diverse ecosystem of search and discovery tools, each catering to different needs and preferences. Ai chatbots may never fully replace traditional search, but they could become powerful companions, really enhancing our ability to find, understand and apply information in more personalized, efficient ways. The search landscape's evolving. It's going to be fascinating to see how Google and other players adapt, but for now, the melding of these two approaches doesn't quite seem to be resonating with users in the way that the tech giants had likely hoped. It's a challenge they'll need to continue refining and perfecting.
Speaker 1:
Well, there you have it. That's my dive into the evolving world of AI-powered search and discovery, from conversational chatbots to specialized capabilities of tools like Perplexity and RAG, it's clear that are offering compelling alternatives that could start chipping away at their market share. The ability to have natural back and forth dialogues, get tailored insights and explore knowledge in more interactive ways is actually really exciting. But, of course, each approach has its own strengths and weaknesses, and really it's important that you understand the nuances between the different platforms like perplexity, these general chatbots, rag interfaces, because it's going to be crucial to find the right tool for the job, and as people use these systems more and more, they're going to know where they're going to go and more and more people are going to go away from Google to search in these more conversational ways, because the future of search isn't blending all of these together, but it's really making them the best for the type of search that you have.
Speaker 1:
So, personally, I think it's a big mistake for Google to double down on AI overviews in their search results. The data they're pulling isn't always vetted. Anyone can post their opinion or even satirical content that may look accurate. The kind of unfiltered information can be dangerous, especially for queries around important, time-sensitive topics, and it's the kind of things that we've trained ourselves to spot, but these AI overview systems just haven't been able to figure it out. So generalized chatbots, on the other hand, great for getting custom information on less time-critical subjects, and specialized AI search engines like Perplexity have a real place where you want more nuanced responses that leverage real-time data. In the end, I believe Google is going to lose double-digit market share as people migrate away from them for many types of queries.
Speaker 1:
The appeal of having conversational contextual search experience is just too strong and in the future, because of the technology advances, these local models, like Apple's new AI, is going to run locally on your phone and not even require internet access to run. I wouldn't be surprised to see more and more users creating their own custom chatbots, trained on their emails, company wikis or personal knowledge base, or just built into things like their phone, where it has all of their data already and you could ask it questions, and it's going to have that as its data source. The future of search is exciting, but it's also a bit unnerving, especially if you're an SEO. So we need to be vigilant about the quality and integrity of the information we're relying on. Really, make sure you're looking at those citations, but the potential of these AI-powered tools to revolutionize how we find, understand and apply knowledge is pretty undeniable.
Speaker 1:
So what do you think? Are you as bullish as I am on the rise of AI, chats and custom search experience, or do you think the old school search engine will remain king? I'd love to hear your thoughts and opinions Reach out to me. Hello at opinionatedseocom. Let me know In the meantime, stay tuned for some more future episodes. I got a couple people lined up we're going to be interviewing, who are going to talk about SEO and AI and some other things that are really exciting, and we'll unpack it all and see what that means for digital marketing and SEO.
