NVIDIA Is Rewriting the Rules

Today we are going to see, AI isn’t slowing down. It’s getting cheaper, faster, and more embedded. NVIDIA is cutting token costs dramatically. Also, Micron is spending billions to meet demand. Alongside Infosys is turning AI into enterprise-grade products. The race is no longer about potential. It’s about production.

In today’s post:

• NVIDIA just crushed AI token costs

• The $200B race to fix AI’s memory problem

• Infosys bets big on enterprise AI

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AI AGENTS

AI agents scale on economics and not intelligence alone.

NVIDIA just unveiled new Blackwell Ultra data. And the numbers are hard to ignore.

Here’s everything you need to know:

• The NVIDIA Blackwell Ultra platform delivers up to 50x higher throughput per megawatt than Hopper.

• That translates into 35x lower cost per token for agentic AI workloads.

• Agentic coding queries jumped from 11% to nearly 50% last year.

• These systems demand low latency and massive context windows.

• The GB300 NVL72 systems are built for exactly that.

• Microsoft, CoreWeave, and Oracle Cloud are deploying them at scale.

• Lower token costs unlock entirely new real-time AI products.

The AI race is shifting from model quality to unit economics. Cheaper tokens mean more experimentation. More experimentation means new product categories. When costs drop 35x, behavior changes. Teams stop rationing compute. They start building differently. What would you build if inference was almost free?

STRATEGY

AI isn’t limited by intelligence anymore

Micron Technology is blasting through bedrock in Boise. Not for symbolism, but for survival.

Here’s everything you need to know:

• Micron is spending $200 billion to expand memory production.

• For decades, memory chips were low-margin commodities.

• AI flipped that equation almost overnight.

• Data centers now devour high-bandwidth memory at historic levels.

• The bottleneck isn’t computing power, but data movement speed.

• Without faster memory, advanced AI models simply stall.

• The companies controlling memory now control AI’s pace.

We obsess over models. We ignore infrastructure. AI breakthroughs grab headlines. Memory constraints quietly shape reality. The real power shift isn’t happening in chat interfaces. It’s happening in factories pouring concrete and blasting rock. If AI is the brain, memory is the bloodstream. And whoever owns the bloodstream sets the limits.

BREAKTHROUGH

Infosys just made a quiet move that signals where enterprise AI is heading

Infosys announced a partnership with Anthropic this week. It’s not just another AI press release.

Here’s everything you need to know:

• Infosys is teaming up with Anthropic to deliver enterprise-grade AI solutions built around safety and reliability.

• Anthropic’s models, including Claude, are known for guardrails, which matter deeply in regulated industries.

• This signals a shift from AI experimentation to production-level deployment inside large enterprises.

• Enterprises don’t just want intelligence; they want compliance, auditability, and predictable behavior.

• Infosys brings the distribution muscle, long-term client trust, and systems integration expertise.

• Anthropic brings frontier models that can reason, summarize, and automate complex workflows.

• Together, they’re positioning AI as infrastructure, not just a tool.

This isn’t about hype. It’s about maturity. The AI race is no longer just about who has the smartest model. It’s about who can safely plug that intelligence into real businesses. When global consulting firms start embedding AI into enterprise systems, the experimentation phase is ending. Will companies use AI to automate yesterday’s work? Or redesign how work happens altogether?

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