Yes, 3 is still a magic number like like in the early millennium ….

What is Gemini 3 & why it’s a big deal

• Google officially announced “A new era of intelligence with Gemini 3”. blog.google+2blog.google

• Key capabilities: much stronger reasoning, full multimodal input (text + image + video + other modalities). For example: “state-of-the-art reasoning and multimodality … our most intelligent model yet.” Google Cloud

• It’s built to be embedded not just in research playgrounds, but in core business products — e.g., search engine, enterprise products, developer tools. The Reuters piece says: “Gemini 3 integrated into Google’s search engine from launch.” Reuters

• For developers, the blog post points to features around “agentic” workflows: ability to call tools, manage context, integrate with open-source frameworks etc. Google Developers Blog

• Strategically, this is Google doubling down on competing with other AI players such as OpenAI. Some commentary: “stealth AI leap … redefines the race against OpenAI.” WebProNews

Why this matters:

• For Google, the margin between being “just a search/ads company” vs being a “platform that powers AI workflows” is shrinking. Gemini 3 is a bet on the latter.

• Multimodal + agentic reasoning is a frontier in AI: moving from “assistant to query” to “co-worker/agent that can reason across tools”.

• Embedding into search and enterprise means revenue and strategic leverage — not just “cool research”.

Sundar Pichai’s London / DeepMind visit & what it signals

The user asked about Pichai’s visit of DeepMind in London and the Nvidia / London angle. Here’s the context and what it implies:

• Pichai posted that he “spent time with the Google DeepMind team in London this week, including the people working on our next generation models.” X (formerly Twitter)

• He also publicly said that Alphabet is committed to investing in the UK, including “training our models” in the UK, and said UK will play a major role in their AI future. Telegrafi

• There’s also cross-company visible praise: e.g., Jensen Huang (CEO of Nvidia) praised a Google Gemini tool (Nano Banana image generator). That shows intersection of Google’s AI strategy with Nvidia’s hardware/compute world. The Times of India

What this likely signals behind the scenes:

• Compute & hardware partnerships: Google needs massive compute/hardware (GPUs/TPUs) to train models like Gemini 3. Nvidia is a key supplier and partner. The public praise and London-Nvidia-Google interplay hint at deeper ties or at least shared ecosystem signalling.

• Global model-training infrastructure: By emphasising UK/DeepMind London, Pichai is signalling that Google is diversifying beyond the U.S., both for regulatory reasons and talent/infrastructure reasons (e.g., data centres, training hubs).

• Research, talent, and strategic hubs: DeepMind London is a major research hub. Pichai’s presence underscores that the next-gen models are anchored there. Could also tie into EU/UK regulatory posture (data sovereignty, model governance).

• AI productisation & commercialisation: The Gemini 3 launch + visit suggests Google is shifting from “research lab” to “product mode”. DeepMind has historically been research-heavy. With Gemini 3, the pipelines are moving towards full-blown products.

• Competitive signalling: With rivals like OpenAI, Anthropic, Microsoft-OpenAI, Google wants to show leadership. The combination of product launch (Gemini 3) + strategic visits + ecosystem partnerships is a coordinated move.

Putting it together: behind the scenes strategy

Here’s how I’d summarise the bigger strategy:

• Platform transformation: Google is transforming its business from “search + ads” to “AI-first platform”. Gemini 3 is the flagship for this transformation.

• End-to-end vertical integration: From compute (Nvidia/TPUs), research (DeepMind London), model development (Gemini team), to product embedding (search, enterprise, apps) — Google is showing it can own or tightly coordinate the full stack.

• Global footprint & regulation readiness: By emphasising UK investment/training, Google is positioning itself favourably vis-à-vis global regulators, data-locality demands, and talent competition.

• Agentic future / new user workflows: The emphasis on “agentic coding”, “tool use”, “multimodal” suggests that Google sees a future where users will have AI agents solving tasks, not just answering queries. This aligns with deep relationships with developers/enterprises.

• Competing on execution: The “stealth” rollout of Gemini 3 (relatively quiet compared to spectacle) suggests Google wants to show substance, not just hype. The earlier criticism of Google in ML is being addressed.

What to watch for next

Here are some signals to monitor:

• How Google integrates Gemini 3 into search monetisation: will ads change? Will AI answers replace traffic? (Some worry about publishers) AP News

• Partnerships between Google and Nvidia: any compute infrastructure announcements, new hardware (TPUs) or special silicon.

• Regulatory/research announcements from the UK: training hubs, “AI superpower” declarations.

• Enterprise product launches built around Gemini 3 (e.g., “Gemini Enterprise”, “Gemini Studio”, developer tools).

• Long-term shift: is DeepMind becoming more product-oriented rather than purely research? Pichai’s visit may mark a shift.

• Speed of rollout: how fast Gemini 3 reaches global audience, how it scales in different languages/markets.