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The Future of AI Search and Its Implications on Web3

The Future of AI Search and Its Implications on Web3

Photo: Rawpixel / Freepik
Photo: Rawpixel / Freepik

The search experience will soon undergo a significant transformation, with the emergence of new AI language models like ChatGPT, causing disruption and shaking up the status quo.

As more people begin to realize the potential of these advanced search engines, many are looking towards the future of Web3 to take advantage of the latest developments in search technology.

In this article, we’ll explore the impact that ChatGPT has had on the search industry and how Web3 search is poised to capitalize on this disruption, ushering in a new era of search technology.

The AI Search Engine Arms Race is On

The introduction of ChatGPT, a highly advanced and innovative language model, has fundamentally altered the search industry, sparking a technological shift not seen since the rise of the iPhone. ChatGPT’s capabilities represent a significant leap forward in natural language processing and have paved the way for search tools that can deliver better results to users.

Unlike traditional search engines, which rely on a combination of keywords, links, and other signals to understand what a user is looking for, ChatGPT can process natural language queries and provide highly relevant results. This has led many people to view it as a potentially viable alternative to established search engines like Google.

One of the key advantages of ChatGPT is that it is able to generate search results that are highly personalized, taking into account the context of the query and the user’s previous input. This level of sophistication has proven popular with users who are looking for a more streamlined and personal approach.

Google Search vs. ChatGPT when searching for "how to bake chocolate chip cookies."
Google Search vs. ChatGPT when searching for “how do i bake chocolate chip cookies”

Microsoft’s recent plans to integrate ChatGPT technology into its Bing search interface has had a significant impact on the market cap of Google, which posted a recent loss of $100 billion in value. While it is not entirely clear whether this was the sole cause of Google’s decline, it has certainly been attributed to the move by some in the press.

With the tremendous reach of these big tech companies, spanning millions and billions of users, there is a lot of risk associated with Big Tech pushing the envelope too far. As they look to remain competitive, these companies must weigh the potential benefits of new technologies against the risk of alienating their user base or triggering a significant market decline.

The Threat to Online Advertising

The rise of artificial intelligence in the search industry is causing concern for the digital advertising market. With the ability to provide instant, accurate answers to queries, AI has the potential to make the traditional search business model redundant, which could have profound implications for the internet economy and wider society.

The impact on digital advertising revenues could be significant, as the current model relies heavily on users clicking through pages of results to view personalized ads. If AI can provide complete answers, users may not need to click through to other pages, which could make it more challenging for websites to generate revenue from search. This could also create barriers for new websites that rely on search traffic to support their business, making it even more difficult to be seen.

Google, the dominant player in the search industry with a 90% market share, is acutely aware of the AI threat and has invested heavily in research to maintain its position as a global search leader. However, even Google may not be immune to the challenges posed by AI in search.

The search engine of the future may not be suitable for delivering digital ads, as if it provides complete answers to user queries, there may be little incentive to click on ads. This could result in a cannibalization of the existing search engine, with potential consequences for both the advertising market and the wider economy.

What Makes Web3 Search Different?

Web3 search engines are often driven by a community of users who contribute to the platform’s development and maintenance. This means that users have a greater say in how the search engine operates and what features are added. Web3 search engines often utilize token economics to incentivize participation and reward users for contributing to the platform.

For some, the emergence of ChatGPT represents a significant opportunity for a re-birth in the search engine space. There may be an opportunity to build out AI models that are truly open and integrate them into a decentralized system.

Presearch is one of the leading decentralized search engines that features a blockchain-based platform, aiming to provide a privacy-focused and community-driven alternative to traditional search providers like Google.

Presearch allows users to search several different major search engines in one place.
Presearch allows users to search several different major search engines in one place.

It allows users to search the web and access various websites from a single interface. Presearch operates on a token system, with its own cryptocurrency called PRE tokens, which can be used to incentivize users and developers for their participation and contributions to the platform.

Presearch also has a referral program that allows users to earn tokens by referring others to the platform. This program is designed to help grow the community and increase the adoption of the Presearch search engine.

The platform aims to provide greater privacy and control to its users, allowing them to decide which search engines and sources to use and even providing the option to run their own nodes. Overall, Presearch is designed to be a more transparent and community-driven alternative to traditional search engines and plans to soon implement functionality like ChatGPT.

The Dangers of AI Search

As with any emerging technology, there are challenges that need to be addressed before users can fully realize the benefits of AI. For example, there are concerns around bias in AI algorithms, as well as questions about how to ensure that AI systems operate ethically and transparently.

AI-generated results are created by using mathematical patterns and machine learning algorithms that analyze vast amounts of data to find patterns and make predictions. While these results can be very efficient in providing suggestions and recommendations, they should be interpreted with caution, as they may not always be entirely accurate or factual. The results can also be manipulated by their creators through re-training of the model.

While AI text generators can be a valuable resource for research, they should not be relied upon as the sole source of information for decision-making. Instead, they should be used as a starting point for further research and investigation, and should be combined with other sources of information to ensure that you have a well-rounded understanding of the topic at hand.

In a recent project update video posted to YouTube, Presearch founder Colin Pape discussed the responsibility that search engines have in communicating these dangers to prevent the spread of inaccurate or misinformation:

“We need to be cautious around the AI experience to ensure that we’re not leading people astray, which is really what can happen as AI is basically making up or hallucinating almost these answers. It’s artificial intelligence, it’s not real until intelligence. It’s very much based on just kind of predictive language and it’s not necessarily developing the deep understanding that a human is capable of, or that a larger Collective of humans is able to generate.”

The Advantages of a Web3 Search Engine

Search aggregators like Presearch allows users to add their own custom engines to a list of available providers. This means that users can access specific resources and websites that may not be available on traditional search engines.

Web3 search aggregators like Presearch are poised for an advantage in the future search war because they make it easy to verify AI generated responses across several search providers in a single place. This makes the task of search engine bouncing and results comparison more efficient.

Presearch results page example.

The token based economy provides incentive for its users and is supported by a decentralized network of operator nodes, meaning that they operate on a peer-to-peer network rather than relying on a central server or authority. This helps to promote transparency and eliminates the risk of a central point of failure or censorship.

Decentralized search aims to provide unbiased results by allowing users to choose their own combination of sources. This means that users can avoid the filter effect that can occur on traditional search engines where users are only presented with results that match their previous search history.

When it comes to search engines, AI can help to aggregate and analyze data from across the web, which can lead to more relevant and accurate results. By combining data from different search engines, AI algorithms can identify patterns and connections that might not be apparent. This can lead to more comprehensive and nuanced insights, which can be especially valuable in fields such as marketing and finance.