OpenAI Saga Continues
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In the latest saga that is OpenAI’s evolution, Microsoft and OpenAI agreed to restructure their long-term partnership, turning the latter into an independent for-profit entity and giving Microsoft a 27% stake (valued at $135B).
It’s a not-insignificant change, as it gives Microsoft access to key AI models until 2032, allowing them a significant competitive advantage in embedding the tech into its own products such as Copilot. They will likely use this power to compete more effectively against Google’s search business and Amazon’s cloud business.
For OpenAI’s part, it allows them to raise funding and pursue broader commercial ambitions. They are also no longer tied to Microsoft’s Azure cloud. It allows CEO Sam Altman greater authority over strategic direction of the company, previously a long-standing point of contention.
If you’ve been following our “OpenAI will rule the internet” serial discussion (here, here, and here) then it should be clear why this is a crucial step for their grand plan. OpenAI needs to make a lot more deals and will need a lot of money to become the centerpiece of the internet. The next step will be changing its revenue model to ad-supported. They already announced an IPO in the not-too-distant future. We watch OpenAI’s evolution with interest.
Nvidia's Industrial Revolution
By now, most readers know that we think the AI bubble is not over. Largely because we have yet to witness the full extent of AI’s capabilities. On Tues, Nvidia CEO Jensen Huang gave us a glimpse into this AI-driven future in his keynote speech at GTC 2025.
Jensen announced a host of new hardware, software, collaborations, and strategic investments to shape the next industrial revolution. Key to this are:
Collab with the US Department of Energy to build supercomputers
Telecommunications that will embed AI (6G wireless and wireless data centers)
Foundational models for robots
A shift from human-written software to AI-generated
Quantum computing platform and “QPU” — will impact fields like drug discovery, materials science, financial modeling, and more
Platform for autonomous driving and robotaxi development
Whereas previously industries were built around tools (MS Excel is a tool, a car is a tool) AI is the worker that uses the tool. AI is the chauffeur, the accountant, the programmer. That means AI’s market size potential is much more expansive than what was previously limited to just “tools”.
He also envisions the concept of “AI factories”, data centers that are specialized and optimized for AI tasks. These factories do nothing but output tokens in the most efficient way. This will require orders of magnitude more computational power compared to traditional data processing. The old world didn’t need a lot of computation, but in the new world, the AI understands context which changes at every step. That’s why it’s so computationally intensive.
Thinking about AI in this way (as a real-world, reasoning, self-teaching agent) shows why investors are still underestimating AI’s potential. There is a gap between AI’s current, limited real-world usage (mostly chatbots) and the enormous future potential at maturity. Paradoxically, AI is incredibly hyped yet underestimated, leading to skepticism and mispricing in the short-term. Investors’ lack of imagination means they fail to grasp the full scale and economic payoff of AI.
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