Gemini, GPT, Perplexity: Three Ways to Think (and Make Us Think) About Artificial Intelligence
Some people use AI to ask for a recipe, others use it to build strategies. Today, tools like Gemini, GPT, and Perplexity’s Comet Plus are no longer novelties to experiment with—they’ve become real colleagues, reshaping the way we search for, read, and create information.
Google is pushing multimodality with Gemini, OpenAI keeps advancing linguistic interaction with GPT, and Perplexity AI is introducing a model that merges research, business, and information into a single seamless experience. Three different approaches, one shared goal: making knowledge more accessible, conversational, and—why not—a little smarter than we are.
It’s no longer about “using a model,” but about understanding how the model itself thinks.
A Bit of Context: A New Way of Approaching Information
In just the past few years, large language models (LLMs) have rewritten the rules of the game. They no longer simply generate text—today they interpret, connect, and synthesize. In other words, they think with us. This shift has transformed the way we experience information. A piece of content is no longer just something to read, but a starting point for a dialogue with an intelligence that reworks it, translates it into other languages, and places it within broader contexts. For those working in the vast world of communication and digital marketing, it means completely rethinking the relationship between people, content, and technology.
In this new ecosystem, Gemini, GPT, and Comet Plus embody three different visions of the same revolution: the pursuit of AI that can not only respond, but truly understand. Google, OpenAI, and Perplexity follow different paths—multimodality, language, and information—but share a common goal: turning knowledge into experience..
Gemini: Google’s Multimodal Model
With Gemini, Google has decided to raise the bar.
It’s not just an upgrade to its language models, but a true evolution—an intelligence capable of understanding text, images, audio, and code in an integrated, coherent way. Described by Google’s own team as “the most capable and general model ever built,” Gemini is designed to adapt to different levels of complexity. From the power of Ultra—built for advanced reasoning tasks—to the lightness of Nano, optimized for mobile devices, and the versatility of Pro, the model powering many current applications.
Its defining feature is native multimodality: the ability to process information from multiple sources—an image, a voice, a piece of code—and combine them to produce more contextual and “human” responses. It’s a step forward that marks the end of models that merely read and the beginning of those that interpret the world.
It’s no longer enough to create well-crafted content; now, information must be designed to interact with systems that see, listen, and reason. Quality remains essential, but the new competitive edge lies in the ability to speak the language of multimodal models—the one that connects words to data, and ideas to experiences.
GPT: The Evolution of Language Generation
Among all language models, GPT is the one that truly made artificial intelligence accessible. Originally born as the Generative Pre-trained Transformer, it has evolved from a simple automatic writing model into a general-purpose reasoning engine—capable of understanding, creating, analyzing, and interacting across multiple languages: verbal, visual, and code.
Trained on vast amounts of data, GPT stands out for its cognitive flexibility: it can translate text, generate scenarios, write code, solve logic problems, summarize documents, or explain complex concepts. With GPT-4o, OpenAI introduced real-time multimodality, enabling interaction through voice, images, and text within a single seamless conversation. Now, attention is turning to GPT-5, which goes beyond content generation. It’s a model designed to reason more autonomously, integrate context, plan logical steps, and collaborate with other systems. More than just an assistant, it’s a kind of cognitive agent capable of tackling complex tasks and dynamically adapting to the user.
In this sense, GPT is no longer a tool that simply “produces answers,” but an interface that understands goals and helps achieve them—combining language, data, and logic. Whether it’s writing an article, analyzing a dataset, or designing a strategy, the model’s true power lies in its ability to think with us.
Perplexity and Comet Plus: When Search Meets the Information Economy
Perplexity AI has taken a different path. Its goal isn’t just to build language models, but to reinvent the way people access and interact with knowledge. In essence, it’s an AI-powered answer engine: unlike traditional search engines, it doesn’t return links—it delivers well-reasoned summaries built on verifiable sources, cited in real time. Every query becomes a mini scientific research process, where AI analyzes, synthesizes, and attributes information.
This focus on transparency and informational quality is what sets Perplexity apart.
Its ambition is clear: to build an AI that doesn’t just respond, but helps us think, bridging the gap between the public knowledge of the web and the individual needs of users. From this vision comes Comet Plus, the natural evolution of the project. Introduced as a premium subscription, Comet Plus offers access to high-quality content from selected publishers and journalists. Users can consult trusted sources, while their AIs (or “cognitive agents”) draw directly from verified material—enhancing the accuracy and credibility of their answers.
But the real turning point lies in its new compensation model for publishers. Comet Plus recognizes the value of three types of traffic:
- Human, when a person visits a site;
- Search, when the content is cited in results;
- Agent, when an AI uses or reworks that content to generate responses.
In other words, AI stops being merely a consumer of information and becomes an active part of the economy that sustains it. It’s a step toward a fairer web—one where those who create knowledge are rewarded, even when the audience is an intelligent machine.
For anyone working with content, marketing, or data, Perplexity and Comet Plus send a clear message: the next step isn’t just to create high-quality information, but to understand how AI uses it, cites it, and distributes it.
Model
Core Strength
Implications for Search
Implications for Marketing
Native multimodality and contextual reasoning
AI Overview and AI Mode are reshaping the SERP: content must be clear, structured, and optimized for model comprehension.
Smarter targeting in Google Ads products and adaptive campaigns based on context and language.
Integration with Workspace and BigQuery enables multimodal predictive analysis and advanced textual insights.
GPT (OpenAI)
Linguistic mastery and adaptability
Useful for semantic analysis, topic clustering, and content brief generation. Improves consistency and tone across pages.
Supports personalized copy creation, large-scale A/B testing, and dynamic optimization of ad messaging.
Generates reports, narrative dashboards, and qualitative insights from raw data, accelerating strategic analysis.
Perplexity + Comet Plus
Cognitive search and a sustainable information model
Shifts Search toward a citability-based model: the most authoritative content is highlighted by AI for accuracy and transparency.
Opens opportunities for editorial partnerships and branded content integrated into AI information streams.
Introduces emerging metrics (human, search, and agent traffic) that anticipate new KPIs for visibility in the post-AI web.
It’s no longer just about ranking for a keyword, but about being recognized as a trustworthy and “readable” source by AI models. Artificial intelligence doesn’t replace marketing channels—it connects them, creating a continuous flow of data, language, and context. That’s why at Navla, we see Gemini, GPT, and Perplexity not as competing tools, but as three distinct lenses through which to read the future of digital marketing.