Encrypt models on Google Private AI

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Google has rolled out its new Private AI Compute offering—an enterprise-grade setup that lets companies train and run AI models inside fully isolated, encrypted environments. Integrated with Vertex AI, it promises zero data egress, key-control transparency, and strong compliance-ready infrastructure.

For CMOs, AI leads, and compliance teams, this is a pivot toward secure AI at scale—especially in regulated industries. It strengthens Google Cloud’s position in the privacy-first enterprise AI market and raises the stakes for how your organization picks its cloud AI infrastructure.

SoftBank sold its $5.8 billion stake in Nvidia and redirected capital into OpenAI and its expansive infrastructure plans, marking one of the most significant investment shifts in AI capital to date. The move signals that compute access and AI platform dominance are becoming strategic battlegrounds.

For enterprise buyers, this highlights a deeper trend: major players are locking in infrastructure advantage, which may impact pricing, vendor concentration, and your organization’s AI vendor-risk profile heading into 2026.

China’s centralized strategy—subsidized energy, streamlined data-center permitting, and government backing—is creating momentum in AI infrastructure that the U.S. and Western companies must watch closely. While not immediate for Western operations, it’s a structural shift in global AI competitiveness.

For enterprise strategy, it means keeping an eye on supply, regulation, and regional power dynamics. Global supply chains and energy constraints might not dominate next quarter’s plan, but they’re building the context for where the AI platform advantage will live in the coming years.

📝 Granola – AI notepad that captures every meeting detail and turns it into clear, useful notes.

🎨 FLUX.1 AI – Text-to-image model that creates high-quality, on-point visuals in any style.

🎥 Trupeer – Turns screen recordings into polished product videos or guides instantly.

LLM Vendor usage over time

Rocket.new is a vibe solutioning platform that turns natural language into production-ready web apps through prompt-first design.

They also have a prompting framework that helps you get from idea to working UI with minimal friction. It combines simple instructions with strategic prompting techniques that scale. Here are a few ways to get better results:

Each prompt stays short but compound strategies make it robust. It’s not about writing more, it’s about thinking in moves.

Start with the guide: https://docs.rocket.new/prompt-engineering

Prompt Used:

Output:

Commands:

Rocket.new has commands that lets you make scoped, repeatable edits directly from chat. You can rename elements, fix layout spacing, generate assets, or restructure a page by targeting specific components or files. This keeps iteration focused and fast.

Examples:

Docs for more details: 

P.S. Get more such prompts in the Prompting Playbook (free for you)

Q. What percentage of sales or marketing workflows is expected to be automated by AI across the industry by the end of 2026?

^{Answer: By the end of 2026, it is expected that AI will automate approximately 35% of sales and marketing workflows across the industry.}