Google's latest AI model, Gemini 3, is making OpenAI's position increasingly precarious, according to Wall Street analyst Jim Cramer. Unlike ChatGPT's groundbreaking debut, Google has systematically integrated AI into profitable businesses like search, advertising, and cloud services—a strategy Cramer believes ensures long-term sustainability.
Following the industry buzz around Gemini 3 and Nano Banana Pro, Google CEO Sundar Pichai (affectionately called "劈柴哥" in Chinese) sat down for an exclusive interview with Logan Kilpatrick, a former OpenAI developer relations lead now at Google. They discussed Google's AI strategy, covering models, infrastructure, and product integration.
Pichai emphasized Google's "long-term engineering" approach, explaining that Gemini 3's success wasn't accidental but the result of years of groundwork. He traced Google's AI evolution back to 2012, when the "Cat Face Paper" from Google Brain first hinted at deep learning's potential. Key milestones followed: the 2014 DeepMind acquisition, AlphaGo's 2016 breakthrough, and the debut of TPUs—laying the foundation for today's AI dominance.
Unlike competitors fixated on marginal model performance gains, Google focused on building a "full-stack AI engine." Pichai described this as the "multiplier effect": stronger infrastructure amplifies pretraining, reinforcement learning, and product capabilities. Despite past compute shortages, Google quietly strengthened its foundation, enabling Gemini’s rapid deployment across Search, YouTube, Gmail, and cloud services.
Logan Kilpatrick likened Gemini 3 to "replacing all of Google’s product nervous systems with one brain." Pichai agreed, calling it the clearest embodiment of Google’s "AI-first" strategy. The synchronized rollout—updating billions of users’ core products simultaneously—was "hellishly difficult" but created a unique synergy: one model upgrade improves everything.
Google’s engineering cadence now follows a rigorous six-month breakthrough cycle, as seen with Gemini 2.5 Pro at I/O 2025. While competitors close the gap, DeepMind pushes efficiency limits. Pichai highlighted the upcoming Flash model, a lightweight yet powerful project targeting the Pareto Frontier—balancing performance, speed, and cost for scalable deployment.
Behind the scenes, Google’s innovation thrives in micro-kitchens, where scientists like DeepMind’s Demis Hassabis and Google AI’s Jeff Dean spark breakthroughs over coffee. Pichai cherishes this culture, recalling how Sergey Brin and Noam Shazeer once debugged code together in these spaces.
On launch days, Pichai obsessively tracks user feedback via social media and real-time dashboards, calling it his "ritual." He shared an example of "Vibe Coding"—where a non-technical colleague used Gemini 3 to create an educational animation, democratizing software creation.
Looking ahead, Google bets on quantum computing, Waymo’s autonomous driving "inflection point," and Project Suncatcher (space-based data centers). Pichai’s 27-step roadmap aims for orbital TPUs by 2027. Meanwhile, tools like NotebookLM gain traction, signaling Google’s next long-term bets.
Jim Cramer notes a market shift: from "best model" to "best integration." While OpenAI struggles to monetize, Google seamlessly embeds AI into profitable ecosystems like Workspace and Cloud. Investors, he warns, should prioritize sustainable integration over raw performance.
For OpenAI, Cramer outlines three scenarios: 1. **Optimistic**: Government-backed loans revive growth. 2. **Neutral**: Microsoft acquires OpenAI at a premium. 3. **Pessimistic**: A funding crunch triggers a dot-com-style crash.
In related news, Intel gains momentum as Nvidia invests $5 billion, and Google adopts Intel’s EMIB packaging for TPU v9, challenging TSMC’s dominance. With AI compute demand soaring, Google’s TPUs emerge as a viable alternative to Nvidia GPUs.