Google has launched Gemini 3, described as its most intelligent AI model yet, bringing state-of-the-art reasoning capabilities to billions of users while revolutionizing scientific research through breakthrough applications in drug discovery and biomedical research, according to Google DeepMind analysis.
Revolutionary AI Capabilities Reach Massive Scale
Nearly two years after Google kicked off the Gemini era, the company is now shipping Gemini at unprecedented scale, with the new model available today in the Gemini app, developers in AI Studio and Vertex AI, according to Blog research. The impact has been transformative: AI Overviews now serve 2 billion users every month, while the Gemini app surpasses 650 million users per month, data from Blog shows.
The development represents a significant milestone in Google's AI journey, with more than 70% of Google Cloud customers now using Google's AI and 13 million developers having built with Google's generative models, according to Blog analysis. This massive adoption underscores the practical value these AI systems are delivering across industries.
Advanced AI Co-Scientist Accelerates Biomedical Breakthroughs
Building on recent AI advances, Google has developed an AI co-scientist system powered by Gemini 2.0 that is designed to function as a collaborative tool for scientists, according to Research findings. The system operates as a multi-agent AI system intended to formulate demonstrably novel research hypotheses and proposals, mirroring the reasoning process underpinning the scientific method.
The AI co-scientist has already demonstrated remarkable capabilities in real-world applications. In collaboration with Stanford University and Imperial College London, the system successfully proposed a new gene transfer mechanism linked to antimicrobial resistance, according to Drugtargetreview analysis. This insight was independently verified by Imperial College researchers after years of study, validating the AI's ability to generate genuinely novel scientific hypotheses.
Additionally, the system identified potential drug candidates for liver fibrosis, which Stanford scientists later validated in laboratory experiments, Drugtargetreview reported. These breakthroughs illustrate how AI can accelerate the traditionally lengthy process of scientific discovery by synthesizing complex information across multiple domains.
Building on Proven Scientific Integration Models
The development of AI co-scientist draws inspiration from successful transdisciplinary scientific endeavors. Modern breakthroughs often emerge from combining expertise across multiple fields, as evidenced by Emmanuelle Charpentier and Jennifer Doudna's 2020 Nobel Prize in Chemistry for their CRISPR work, which combined expertise from microbiology, genetics, and molecular biology, according to Research data.
This multi-domain approach addresses a critical challenge in modern scientific discovery: navigating the rapid growth in scientific publications while integrating insights from unfamiliar domains. The AI co-scientist is designed to overcome these breadth and depth challenges by synthesizing across complex subjects and performing long-term planning and reasoning.
Platform Evolution Supports Advanced Development
Google's Vertex AI platform now provides developers access to over 200 foundation models, with new customers receiving up to $300 in free credits to explore the technology, according to Cloud analysis. The platform offers comprehensive AI development tools, including access to the latest Gemini models through Vertex AI Studio, where developers can experiment with text, images, video, or code inputs.
The platform's capabilities extend beyond basic AI functionality, offering first-party models like Gemini, Imagen, Chirp, and Veo, alongside third-party options including Anthropic's Claude Model Family and open models such as Gemma and Llama 3.2, Cloud data shows. This diverse ecosystem enables developers to select optimal models for specific use cases while providing enterprise-grade evaluation tools for objective assessment.
Drug Discovery Revolution Through AlphaFold 3
Google DeepMind's broader AI-driven drug discovery efforts are further supported by AlphaFold 3, which extends predictive capabilities beyond protein folding to modeling interactions between proteins, DNA, RNA, and small molecules, according to Drugtargetreview research. These enhancements are expected to significantly improve drug target identification and therapeutic compound design.
Isomorphic Labs, Alphabet's subsidiary dedicated to AI-driven pharmaceutical research, is set to advance its first AI-designed drug candidate into clinical trials by the end of 2025, Drugtargetreview reported. The company is actively collaborating with pharmaceutical leaders such as Eli Lilly to accelerate treatment discovery for oncology and cardiovascular applications.
Market Leadership and Future Trajectory
Gemini's market position has been strengthened by consistent performance improvements, with Gemini 2.5 Pro topping LMArena for over six months, demonstrating sustained technical leadership, according to Blog analysis. Each generation of Gemini has built incrementally: Gemini 1 introduced native multimodality and long context windows, while Gemini 2 added thinking, reasoning, and tool use capabilities.
Gemini 3 represents the culmination of these advances, combining all previous capabilities into what Google describes as its most intelligent model. The system excels at grasping depth and nuance, whether perceiving subtle clues in creative ideas or analyzing overlapping layers of complex problems, with improved contextual understanding that requires less prompting from users.
As Google continues to scale these capabilities across its product ecosystem, the integration of advanced AI reasoning into scientific research, drug discovery, and everyday applications signals a fundamental shift in how artificial intelligence can augment human capabilities across multiple domains. The combination of massive user adoption, proven scientific applications, and continued technical advancement positions Gemini 3 as a significant milestone in the evolution of generative AI technology.