Perplexity AI’s CEO discussed the development of a personalized search engine combining chatbot and Wikipedia capabilities, emphasizing the importance of accurate and personalized answers through orchestrating multiple models. The conversation also touched on the future of AI and search technology, highlighting the shift towards multimodal search experiences and the evolving landscape of hardware and software for AI applications, including investments in AI startups.
In a recent conversation, Perplexity AI’s CEO discussed the journey of building a personalized search engine that combines the capabilities of chatbots and Wikipedia. The CEO highlighted the unique aspect of summarization in Perplexity, creating a personalized conversational experience for users. The company aims to combine large language models with existing search indexes to create an answer engine that provides accurate and readable information to users.
The CEO emphasized the importance of orchestrating multiple models within Perplexity to ensure accurate and personalized answers for users. While leveraging existing language models, the focus remains on optimizing search results and delivering a user-friendly experience. The goal is to make search more conversational, akin to chatting with a knowledgeable entity that can provide tailored information.
Discussing the future of AI and search technology, the CEO highlighted the shift towards multimodal search experiences that incorporate voice and visual inputs. The vision is to enable users to interact with search engines through various devices and input methods, ultimately enhancing the user experience. The company is exploring ways to adapt to evolving hardware and software landscapes to stay ahead in the search technology domain.
The conversation delved into the evolving landscape of hardware and software for AI applications, particularly in training and inference processes. While Nvidia remains a dominant player in cloud inference, the CEO discussed the emergence of new hardware companies like Groq that could potentially disrupt the market and drive down costs for AI inference. The importance of software stack development and hardware optimization was highlighted as crucial for companies aiming to compete in the AI hardware space.
In the final segment, the CEO shared insights on investing in AI startups, emphasizing the need for taking asymmetric bets on promising ideas and technologies. The CEO reflected on recent investments in companies like Groq, Llamas, and Mistry, showcasing the interconnectedness of these ventures with Perplexity’s own operations. The CEO also offered insights into potential startup ideas, suggesting a focus on on-device AI models and software development to enhance user experiences and drive innovation in the AI industry.