Can Google Dominate the AI Landscape?

In my recent exploration of various large language models (LLMs), I embarked on a project to create an AI agent capable of generating comprehensive reports. The specific task was to compile a list of every website associated with a given company and prioritize them, ensuring that official and relevant links appeared at the top.

To assess their performance, I utilized a variety of AI tools, including ChatGPT, Deep Search, Perplexity Pro, Claude 3.7 Sonnet, Deepseek DeepThink R1, Grok Deeper Research, QWEN QWEN3-235B-A22B, Mistral Web Search, Manus High-Effort, and Gemini Deep Research equipped with Flash 2.5.

Performance Highlights

From my testing, Gemini Deep Research clearly outshone the competition, providing around 60 active links, many of which included pertinent PDFs. It exceeded my expectations by effectively going beyond the basic assignment.

In comparison, ChatGPT offered 16 links—solid, but nothing groundbreaking—and the retrieval process took significantly longer than that of Gemini.

Unfortunately, the other tools in this analysis struggled, producing results riddled with inaccuracies, broken or non-functional links, and missing essential connections.

The Google Paradox

It’s noteworthy that Google has had a mixed track record in recent AI initiatives. Despite this, their unparalleled expertise in search technology and access to the latest web data raises an intriguing question: Can we anticipate a “last mover advantage” for Google in the AI sector?

With a wealth of knowledge at their disposal, the potential for Google to leverage its vast resources and improve upon their current AI capabilities remains a tantalizing prospect. Only time will tell if they can reshape their position in the evolving AI landscape, but their search engine supremacy offers a glimmer of hope for future breakthroughs in Artificial Intelligence.