From Search to Direct answer and how (soon) we will skip the research stage with 10 blue links

Imagine a world where every online search instantly connects you with exactly what you need to know, no endless scrolling required. This isn't a future scenario—it's happening now

The quest for information has evolved dramatically from the era of the "10 blue links" to a new horizon where AI-driven tools deliver not just search results but direct answers and insights. This shift marks a pivotal moment in how we interact with the digital world. In the past 15 months, a seismic shift has occurred in the landscape of online search and user expectations. Traditionally, we turned to Google, scanning through pages of links, clicking on a few, and piecing together the information we needed. However, the introduction of OpenAI's ChatGPT has ushered in a new era of direct answers and comprehensive insights. This new? approach to information retrieval has not only changed the way we ask questions but also led to a significant shift in user expectations, steering them towards innovative tools like ChatGPT and Perplexity. We're standing at the precipice of a new age , where the journey from query to answer is more direct, intuitive, and enriched than ever before.

Who are the main players?

• Google continues to lead, constantly adapting to these changes.
• ChatGPT updated its knowledge base last year, with GPT-4 now having internet access.
• Perplexity combines elements of both, offering summaries of web pages based on your search query, complete with clickable links for further exploration.

What is the latest from Google?

Google is at the forefront of integrating AI into search experiences, pioneering the use of AI-generated summaries for complex queries in the US. This innovation, aimed at enriching user experience by providing comprehensive answers from multiple sources, is currently in the testing phase for a select number of users. Unlike previous functionalities limited to those enrolled in the Google Search Generative Experience (SGE), this test extends to a broader audience, allowing Google to gather valuable feedback on its utility and effectiveness.

As competition in the AI space heats up, with entities like OpenAI and Microsoft making strides but not significantly denting Google's market share, Google's introduction of SGE last year marks a significant step forward. SGE enhances user interaction through direct AI responses, follow-up queries, and chatbot-like conversations, alongside generating images and summarising web content. This move not only positions Google as a leader in AI-assisted search but also sparks discussions about the future role of search engines as intermediaries to the web or as gatekeepers of a more enclosed digital ecosystem.

Google's tests are part of a broader strategy to refine and evolve its search offerings in response to the challenges and opportunities presented by AI technologies. By doing so, Google aims to remain at the forefront of the search industry, ensuring its platform remains relevant and valuable in an increasingly AI-driven world. This development raises intriguing questions about the balance between innovation and responsibility, particularly regarding the impact of AI-generated content on the digital information landscape and Google's expanding role within it.

What is the latest from Open AI

OpenAI's CEO, Sam Altman, sees the integration of ChatGPT with search technologies as a thrilling opportunity to redefine internet search, rather than merely attempting to replicate Google's success. In a interview with Lex Fridman, Altman critiqued the current search result presentation model as being somewhat obsolete, clarifying his aspiration not to mimic Google but to pioneer in the search domain.

Altman envisions a transformative search mechanism that transcends the traditional, offering nuanced assistance—be it through generating answers, summarizing information, or providing references. This vision challenges the conventional search service model, underlining the technical and branding complexities of surpassing Google's dominance. Nevertheless, Altman maintains that the objective isn't to outdo Google but to innovate within the realm of language models and internet search capabilities, aiming for a synergy yet to be fully realized.

Moreover, Altman advocates for an ad-free AI search experience, underscoring OpenAI's commitment to unbiased, user-funded interactions. This stance reflects a broader critique of advertising's role on the internet, suggesting a shift towards more user-centric models. The development of a web search product by OpenAI, potentially in collaboration with Microsoft's Bing, signifies a step towards diversifying search engine market dynamics and enhancing user experience with AI-driven search functionalities.

OpenAI's exploration into web search aims not only to carve out a niche against Google but also to redefine user interactions with digital information, promising a future where AI enhances the search experience without compromising on ethical standards or user autonomy.

Sam Altman on OpenAI vs Google Search

More about Perplexity?

Perplexity harnesses a blend of proprietary Large Language Models (LLMs), contributions from third parties such as OpenAI's GPT-4 and Anthropic's Claude 2, along with sophisticated web crawlers. This amalgamation ensures the delivery of results that are not only highly pertinent but also meticulously referenced. The cornerstone of Perplexity's innovation is its adoption of Retrieval-Augmented Generation (RAG), a form of AI adept at identifying the most relevant documents online to enable LLMs to generate answers that are both contextualised and precise. This technique particularly excels with broad questions like "How should I prepare for my vacation in Rome?" However, it may not be as effective for queries seeking specific details such as local business hours or live sports results.

Perplexity has made its platform accessible through both web and mobile applications, with the iOS app launching in March 2023 and its Android counterpart in May. With over 2 million downloads, these apps now process in excess of 1 million queries daily. The company has also been chosen as the search solution for the eagerly anticipated R1 AI device by Rabbit, set to be released this spring.

Perplexity’s cofounder and CEO, Aravind Srinivas, asserts that competing directly with Google for search market share isn't necessary for the company's success. He believes that by carving out a niche within the emerging sectors of AI assistants, chatbots, and answer bots, Perplexity is well-positioned for growth in a market that continues to evolve and expand.

Latest from Perplexity?

• Last week Perplexity was recognized in the Top 50 Innovative Companies by Fast Company along with NVIDIA, OpenAI, Google, Microsoft, Youtube, Whatsapp and others
• Perplexity AI is finalizing a funding round expected to value the company at $1 billion, achieving unicorn status.
• This valuation is a significant increase from $520 million two months ago, following a $73.6 million Series B funding led by IVP, with contributions from Nvidia and Jeff Bezos.

Challenges and Unknowns of the New Search

Adapting to this new approach for consuming and finding information presents several challenges. Here is a revised and expanded list of the issues I'm currently seeing:

• Data Selection by LLMs for Summarization: The criteria and algorithms used by Large Language Models (LLMs) to select data for summarization are complex and not fully transparent. This raises concerns about how these decisions are made and the factors that influence them.
• Valuation of Data: Assessing the value of the data selected by LLMs is a multifaceted challenge. It involves not only determining the relevance and accuracy of the information but also considering its utility to different stakeholders. This valuation process is crucial for ensuring that the data serves the interests of a broad audience.
• Accuracy of Data: Given the potential for errors inherent in all LLM outputs, ensuring the accuracy of summarized data is paramount. This requires rigorous validation mechanisms to identify and correct inaccuracies, thereby maintaining the credibility of the information provided.
• Optimization of Content for Businesses: With the rise of LLMs, businesses must rethink their content optimization strategies. To stay competitive and visible in this new digital environment, adapting content to be more compatible with LLM summarization and selection processes is essential.
• Impact on the Global Advertising Ecosystem: The integration of LLMs into our digital infrastructure has significant implications for the global advertising ecosystem, particularly concerning Google and search marketing. The potential changes in content visibility and discoverability could radically alter advertising strategies and the distribution of ad revenues.

As we witness this evolution in real-time, it's crucial to engage with these new tools, understand their potential, and consider the broader implications for information retrieval, privacy, and digital literacy.

What's your perspective on this shift towards AI-powered research tools? Are you excited about the possibilities these innovations bring, or do you have reservations about the changes they herald?